From 71d7e1bbc0c1fd75ce640c6c14883a56ecc0f9f3 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 17 Aug 2022 15:57:28 -0400
Subject: [PATCH 01/17] new faster expected full in sandbox

---
 cooltools/sandbox/obs_over_exp_cooler.py      | 432 ++++++++-
 .../observed_over_expected_example.ipynb      | 820 +++++++++++++++---
 2 files changed, 1131 insertions(+), 121 deletions(-)

diff --git a/cooltools/sandbox/obs_over_exp_cooler.py b/cooltools/sandbox/obs_over_exp_cooler.py
index 777bac02..35fc9e80 100644
--- a/cooltools/sandbox/obs_over_exp_cooler.py
+++ b/cooltools/sandbox/obs_over_exp_cooler.py
@@ -16,20 +16,47 @@
 
 import numpy as np
 import pandas as pd
+import multiprocess as mp
 
 import cooler
 from cooler.tools import partition
 
+from itertools import (
+    tee,
+    chain,
+    combinations_with_replacement
+)
+
+from functools import reduce, partial
+
 from cooltools import (
     expected_cis,
     expected_trans
 )
 from cooltools.lib.common import (
     assign_supports,
-    make_cooler_view
+    make_cooler_view,
+)
+
+from cooltools.lib import (
+    is_compatible_viewframe,
+    is_cooler_balanced
+)
+
+from cooltools.api.expected import make_block_table, make_diag_tables
+
+from cooltools.lib.schemas import (
+    diag_expected_dtypes,
+    block_expected_dtypes
 )
 
 
+# common expected_df column names, take from schemas
+_REGION1 = list(diag_expected_dtypes)[0]
+_REGION2 = list(diag_expected_dtypes)[1]
+_DIST = list(diag_expected_dtypes)[2]
+_NUM_VALID = list(diag_expected_dtypes)[3]
+
 logging.basicConfig(level=logging.INFO)
 
 
@@ -121,7 +148,7 @@ def expected_full(
     )
     # pretend that they also have a "dist"
     # to make them mergeable with cvd
-    cpb["dist"] = 0
+    cpb["dist"] = -1
     time_elapsed = time.perf_counter() - time_start
     logging.info(f"Done calculating trans expected in {time_elapsed:.3f} sec ...")
 
@@ -174,6 +201,407 @@ def expected_full(
     return expected_df
 
 
+def make_pairwise_expected_table(clr, view_df, clr_weight_name):
+    """
+    create a DataFrame for accumulating expected summaries (blocks and diagonal ones)
+    it also contains "n_valid" column for dividing summaries by.
+    """
+    
+    # create pairwise combinations of regions from view_df
+    cis_combs, trans_combs = tee(
+        combinations_with_replacement(view_df.itertuples(), 2)
+    )
+    # filter cis
+    cis_combs = ((r1, r2) for r1, r2 in cis_combs if (r1.chrom == r2.chrom))
+    # filter trans
+    trans_combs = ((r1, r2) for r1, r2 in trans_combs if (r1.chrom != r2.chrom))
+
+    # cis dtables ...
+    # unzip regions1 regions2 defining the blocks for summary collection
+    regions1, regions2 = zip(*cis_combs)
+    regions1 = pd.DataFrame(regions1).drop(columns=["Index"])
+    regions2 = pd.DataFrame(regions2).drop(columns=["Index"])
+    # prepare dtables: for every region a table with diagonals, number of valid pixels, etc
+    dtables = make_diag_tables(clr, regions1, regions2, clr_weight_name=clr_weight_name)
+
+    # trans btables ...
+    # unzip regions1 regions2 defining the blocks for summary collection
+    regions1, regions2 = zip(*trans_combs)
+    regions1 = pd.DataFrame(regions1).drop(columns=["Index"])
+    regions2 = pd.DataFrame(regions2).drop(columns=["Index"])
+    btables = make_block_table(clr, regions1, regions2, clr_weight_name=clr_weight_name)
+
+    # rearrange dtables and btables to prepare their concatenation:
+    _tables = []
+    for _r1, chrom1, name1 in view_df[["chrom","name"]].itertuples():
+        for _r2, chrom2, name2 in view_df[["chrom","name"]].itertuples():
+            # upper triangle
+            if (_r2 >= _r1):
+                if (chrom1==chrom2):
+                    df = dtables[(name1, name2)].reset_index()
+                    df.insert(0, "r2", _r2)
+                    df.insert(0, "r1", _r1)
+                    _tables.append(df.set_index(["r1", "r2", _DIST]))
+                if (chrom1 != chrom2):
+                    df = pd.DataFrame(btables[(name1, name2)], index=[0])
+                    df.insert(0, _DIST, -1)  # special trans-value for distance
+                    df.insert(0, "r2", _r2)
+                    df.insert(0, "r1", _r1)
+                    _tables.append(df.set_index(["r1", "r2", _DIST]))
+
+    # return all concatenated DataFrame for cis and trans blocks:
+    return pd.concat( _tables )
+
+
+def _sum_(clr, fields, transforms, clr_weight_name, regions, span):
+    """
+    calculates summaries for every pixel block defined by pairwise
+    combinations of the specified regions: calculates per-diagonal
+    sums for intra-chromosomal blocks and overall sums for inter-
+    chromosomal blocks.
+
+    pixels in the blocks are labeled with regions' serial numbers,
+    and groupby-s are used grouping.
+
+    Trans-values have a special value for their diagonal/dist -1
+
+    Return:
+    dictionary of DataFrames with diagonal sums and overall sums
+    for the "fields", indexed with the (i,j) combinations of serial
+    numbers of the regions.
+    """
+    lo, hi = span
+    bins = clr.bins()[:]
+    bins["r"] = assign_supports(bins, regions)  # astype float
+    # subset a group of pixels abd annotate it with with the region-labeled bins
+    pixels = clr.pixels()[lo:hi]
+    pixels = cooler.annotate(pixels, bins, replace=False)
+
+    # pre-filter unannotated pixels and masked out by balancing weights
+    if clr_weight_name is None:
+        pixels = pixels.dropna(subset=["r1", "r2"])
+    else:
+        pixels = pixels.dropna(
+            subset=["r1", "r2", clr_weight_name + "1", clr_weight_name + "2"]
+        )
+
+    # cast to int, as there are no more NaNs among r1/r2
+    pixels = pixels.astype({"r1":int, "r2":int})
+
+    # create a cis-mask, trans-mask
+    cis_mask = pixels["chrom1"] == pixels["chrom2"]
+
+    # initialize _DIST as 0 for all pixels
+    # consider using -1 as a special value to distinguish trans data easily ...
+    pixels.loc[:, _DIST] = -1
+    # calculate actual genomic _DIST for cis-pixels:
+    pixels.loc[cis_mask, _DIST] = pixels.loc[cis_mask, "bin2_id"] - pixels.loc[cis_mask, "bin1_id"]
+    # apply requested transforms, e.g. balancing:
+    for field, t in transforms.items():
+        pixels[field] = t(pixels)
+    
+    # perform aggregation by r1, r2 and _DIST
+    _blocks = pixels.groupby(["r1", "r2", _DIST])
+    
+    # calculate summaries and add ".sum" suffix to field column-names
+    return _blocks[fields].sum().add_suffix(".sum")
+
+
+def sum_pairwise(
+    clr,
+    view_df,
+    transforms={},
+    clr_weight_name="weight",
+    ignore_diags=2,
+    chunksize=10_000_000,
+    map=map,
+):
+    """
+
+    Intra-chromosomal diagonal summary statistics for asymmetric blocks of
+    contact matrix defined as pairwise combinations of regions in "view_df.
+
+    Note
+    ----
+    This is a special case of asymmetric diagonal summary statistic that is
+    efficient and covers the most important practical case of inter-chromosomal
+    arms "expected" calculation.
+
+    Parameters
+    ----------
+    clr : cooler.Cooler
+        Cooler object
+    view_df : viewframe
+        view_df of regions for intra-chromosomal diagonal summation, has to
+        be sorted according to the order of chromosomes in cooler.
+    transforms : dict of str -> callable, optional
+        Transformations to apply to pixels. The result will be assigned to
+        a temporary column with the name given by the key. Callables take
+        one argument: the current chunk of the (annotated) pixel dataframe.
+    clr_weight_name : str
+        name of the balancing weight vector used to count "bad"
+        pixels per diagonal. Set to `None` not to mask
+        "bad" pixels (raw data only).
+    chunksize : int, optional
+        Size of pixel table chunks to process
+    map : callable, optional
+        Map functor implementation.
+
+    Returns
+    -------
+    Dataframe of diagonal statistics for all intra-chromosomal blocks defined as
+    pairwise combinations of regions in the view
+
+    """
+    spans = partition(0, len(clr.pixels()), chunksize)
+    fields = list(chain(["count"], transforms))
+    # names of summary results
+    summary_fields = [f"{field}.sum" for field in fields]
+
+    # check viewframe
+    try:
+        _ = is_compatible_viewframe(
+            view_df,
+            clr,
+            check_sorting=True,  # required for pairwise combinations
+            raise_errors=True,
+        )
+    except Exception as e:
+        raise ValueError("provided view_df is not valid") from e
+
+    # prepare an expected table: for every pairwise region combination a table with diagonals,
+    # number of valid pixels, etc. Inter-chromosomal entries all have dist=0 value.
+    exp_table = make_pairwise_expected_table(clr, view_df, clr_weight_name=clr_weight_name)
+
+    # initialize columns to store summary results in exp_table
+    for agg_name in summary_fields:
+        exp_table[agg_name] = 0
+
+    # apply _diagsum_pairwise to chunks of pixels
+    job = partial(
+        _sum_, clr, fields, transforms, clr_weight_name, view_df.to_numpy()
+    )
+    results = map(job, spans)
+
+    # accumulate every chunk of summary results to exp_table
+    result_df = reduce(lambda df1,df2: df1.add(df2, fill_value=0), results, exp_table)
+
+    # following can be done easily, when _DIST has a special value for trans ...
+    if ignore_diags:
+        for _d in range(ignore_diags):
+            # extract fist "ignore_diags" from DataFrame and fill them with NaNs
+            _idx = result_df.xs(_d, level=_DIST, drop_level=False).index
+            result_df.loc[_idx, summary_fields] = np.nan
+
+    # # returning a pd.DataFrame for API consistency:
+    result_df.reset_index(level=_DIST, inplace=True)
+    # region1 for the final table
+    result_df.insert(0, _REGION1, view_df.loc[result_df.index.get_level_values("r1"), "name"].to_numpy())
+    # region2 for the final table
+    result_df.insert(1, _REGION2, view_df.loc[result_df.index.get_level_values("r2"), "name"].to_numpy())
+    # drop r1/r2 region labels
+    result_df.reset_index(level=["r1", "r2"], drop=True, inplace=True)
+
+    return result_df
+
+
+def expected_full_fast(
+        clr,
+        view_df=None,
+        smooth_cis=False,
+        aggregate_smoothed=False,
+        smooth_sigma=0.1,
+        aggregate_trans=False,
+        expected_column_name="expected",
+        ignore_diags=2,
+        clr_weight_name='weight',
+        chunksize=10_000_000,
+        nproc=4,
+    ):
+    """
+    Generate a DataFrame with expected for *all* 2D regions
+    tiling entire heatmap in clr.
+    Such 2D regions are defined as all pairwise combinations
+    of the regions in view_df. Average distance decay is calculated
+    for every cis-region (e.g. inter- and intra-arms), and
+    a "simple" average over each block is caculated for trans-
+    regions.
+
+    When sub-chromosomal view is provided, trans averages
+    can be aggregated back to the level of full chromosomes.
+
+    Parameters
+    ----------
+    clr : cooler.Cooler
+        Cooler object
+    view_df : viewframe
+        expected is calculated for all pairwise combinations of regions
+        in view_df. Distance dependent expected is calculated for cis
+        regions, and block-level average is calculated for trans regions.
+    smooth_cis: bool
+        Apply smoothing to cis-expected. Will be stored in an additional column
+    aggregate_smoothed: bool
+        When smoothing cis expected, average over all regions, ignored without smoothing.
+    smooth_sigma: float
+        Control smoothing with the standard deviation of the smoothing Gaussian kernel.
+        Ignored without smoothing.
+    aggregate_trans : bool
+        Aggregate trans-expected at the inter-chromosomal level.
+    expected_column_name : str
+        Name of the column where to store combined expected
+    ignore_diags : int, optional
+        Number of intial diagonals to exclude for calculation of distance dependent
+        expected.
+    clr_weight_name : str or None
+        Name of balancing weight column from the cooler to use.
+        Use raw unbalanced data, when None.
+    chunksize : int, optional
+        Size of pixel table chunks to process
+    nproc : int, optional
+        How many processes to use for calculation
+    Returns
+    -------
+    expected_df: pd.DataFrame
+        cis and trans expected combined together
+    """
+
+    if view_df is None:
+            # Generate chromosome-wide viewframe from clr.chromsizes:
+            view_df = make_cooler_view(clr)
+    else:
+        # Make sure view_df is a proper viewframe
+        try:
+            _ = is_compatible_viewframe(
+                view_df,
+                clr,
+                # (?) must be sorted for asymmetric case
+                check_sorting=True,
+                raise_errors=True,
+            )
+        except Exception as e:
+            raise ValueError("view_df is not a valid viewframe or incompatible") from e
+
+    # define transforms - balanced and raw ('count') for now
+    if clr_weight_name is None:
+        # no transforms
+        transforms = {}
+    elif is_cooler_balanced(clr, clr_weight_name):
+        # define balanced data transform:
+        weight1 = clr_weight_name + "1"
+        weight2 = clr_weight_name + "2"
+        transforms = {"balanced": lambda p: p["count"] * p[weight1] * p[weight2]}
+    else:
+        raise ValueError(
+            "cooler is not balanced, or"
+            f"balancing weight {clr_weight_name} is not available in the cooler."
+        )
+
+    # execution details
+    if nproc > 1:
+        pool = mp.Pool(nproc)
+        map_ = pool.map
+    else:
+        map_ = map
+
+    # using try-clause to close mp.Pool properly
+    try:
+        result = sum_pairwise(
+            clr,
+            view_df=view_df,
+            transforms=transforms,
+            clr_weight_name=clr_weight_name,
+            ignore_diags=ignore_diags,
+            chunksize=chunksize,
+            map=map_,
+        )
+    finally:
+        if nproc > 1:
+            pool.close()
+
+
+    # calculate actual averages by dividing sum by n_valid:
+    for key in chain(["count"], transforms):
+        result[f"{key}.avg"] = result[f"{key}.sum"] / result[_NUM_VALID]
+
+    # # additional smoothing and aggregating options would add columns only, not replace them
+    # if smooth:
+    #     result_smooth = expected_smoothing.agg_smooth_cvd(
+    #         result,
+    #         sigma_log10=smooth_sigma,
+    #     )
+    #     # add smoothed columns to the result (only balanced for now)
+    #     result = result.merge(
+    #         result_smooth[["balanced.avg.smoothed", _DIST]],
+    #         on=[_REGION1, _REGION2, _DIST],
+    #         how="left",
+    #     )
+    #     if aggregate_smoothed:
+    #         result_smooth_agg = expected_smoothing.agg_smooth_cvd(
+    #             result,
+    #             groupby=None,
+    #             sigma_log10=smooth_sigma,
+    #         ).rename(columns={"balanced.avg.smoothed": "balanced.avg.smoothed.agg"})
+    #         # add smoothed columns to the result
+    #         result = result.merge(
+    #             result_smooth_agg[["balanced.avg.smoothed.agg", _DIST]],
+    #             on=[
+    #                 _DIST,
+    #             ],
+    #             how="left",
+    #         )
+
+    return result
+
+
+    # # annotate expected_df with the region index and chromosomes
+    # view_label = view_df \
+    #             .reset_index() \
+    #             .rename(columns={"index":"r"}) \
+    #             .set_index("name")
+
+    # # which expected column to use, based on requested "modifications":
+    # cis_expected_name = "balanced.avg" if clr_weight_name else "count.avg"
+    # if smooth_cis:
+    #     cis_expected_name = f"{cis_expected_name}.smoothed"
+    #     if aggregate_smoothed:
+    #         cis_expected_name = f"{cis_expected_name}.agg"
+    # # copy to the prescribed column for the final output:
+    # cvd[expected_column_name] = cvd[cis_expected_name].copy()
+
+    # # aggregate trans if requested and deide which trans-expected column to use:
+    # trans_expected_name = "balanced.avg" if clr_weight_name else "count.avg"
+    # if aggregate_trans:
+    #     trans_expected_name = f"{trans_expected_name}.agg"
+    #     additive_cols = ["n_valid","count.sum"]
+    #     if clr_weight_name:
+    #         additive_cols.append("balanced.sum")
+    #     # groupby chrom1, chrom2 and aggregate additive fields (sums and n_valid):
+    #     _cpb_agg = cpb.groupby(
+    #         [
+    #             view_label["chrom"].loc[cpb["region1"]].to_numpy(),  # chrom1
+    #             view_label["chrom"].loc[cpb["region2"]].to_numpy(),  # chrom2
+    #         ]
+    #     )[additive_cols].transform("sum")
+    #     # recalculate aggregated averages:
+    #     cpb["count.avg.agg"] = _cpb_agg["count.sum"]/_cpb_agg["n_valid"]
+    #     if clr_weight_name:
+    #         cpb["balanced.avg.agg"] = _cpb_agg["balanced.sum"]/_cpb_agg["n_valid"]
+    # # copy to the prescribed column for the final output:
+    # cpb[expected_column_name] = cpb[trans_expected_name].copy()
+
+    # # concatenate cvd and cpb (cis and trans):
+    # expected_df = pd.concat([cvd, cpb], ignore_index=True)
+
+    # # add r1 r2 labels to the final dataframe for obs/exp merging
+    # expected_df["r1"] = view_label["r"].loc[expected_df["region1"]].to_numpy()
+    # expected_df["r2"] = view_label["r"].loc[expected_df["region2"]].to_numpy()
+
+    # # and return joined cis/trans expected in the same format
+    # logging.info(f"Returning combined expected DataFrame.")
+    # # consider purging unneccessary columns here
+    # return expected_df
+
+
 def obs_over_exp_generator(
         clr,
         expected_full,
diff --git a/cooltools/sandbox/observed_over_expected_example.ipynb b/cooltools/sandbox/observed_over_expected_example.ipynb
index 535c7d49..5ba3c675 100644
--- a/cooltools/sandbox/observed_over_expected_example.ipynb
+++ b/cooltools/sandbox/observed_over_expected_example.ipynb
@@ -1,8 +1,29 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "75110361",
+   "metadata": {},
+   "source": [
+    "### beware when working with mcool files generated older version of `cooler zoomify` (circa <0.8.4) - those that had a split pixel issue https://github.com/open2c/cooler/issues/270\n",
+    "\n",
+    "whenever this is the case - one should rezoomify the coolers"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
+   "id": "bd440b57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
    "id": "classical-promise",
    "metadata": {},
    "outputs": [],
@@ -15,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "saving-waterproof",
    "metadata": {},
    "outputs": [],
@@ -26,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "fifth-geology",
    "metadata": {},
    "outputs": [],
@@ -39,18 +60,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "fitting-trial",
+   "execution_count": 5,
+   "id": "4c2e8715",
    "metadata": {},
    "outputs": [],
    "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2"
+    "from time import perf_counter"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "christian-bobby",
    "metadata": {},
    "outputs": [
@@ -72,18 +92,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 24,
    "id": "fiscal-worship",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Load a Hi-C map at a 1Mb resolution from a cooler file.\n",
-    "clr = cooler.Cooler('./test.mcool::/resolutions/1000000')"
+    "clr = cooler.Cooler('./test.mcool::/resolutions/100000')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 25,
    "id": "threatened-commissioner",
    "metadata": {},
    "outputs": [
@@ -155,7 +175,7 @@
        "3  chr17  24714921   83257441  chr17_q"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -168,12 +188,552 @@
     "hg38_arms = bioframe.make_chromarms(hg38_chromsizes,  hg38_cens)\n",
     "# select only those chromosomes available in cooler\n",
     "hg38_arms = hg38_arms[hg38_arms.chrom.isin(clr.chromnames)].reset_index(drop=True)\n",
+    "\n",
+    "# # when you've got no internet ...\n",
+    "# _chrom=[\"chr2\",\"chr2\",\"chr17\",\"chr17\"]\n",
+    "# _start=[0,93139351,0,24714921]\n",
+    "# _end=[93139351,242193529,24714921,83257441]\n",
+    "# _name=[\"chr2_p\",\"chr2_q\",\"chr17_p\",\"chr17_q\"]\n",
+    "# hg38_arms = pd.DataFrame({\"chrom\":_chrom,\"start\":_start,\"end\":_end,\"name\":_name})\n",
+    "\n",
     "hg38_arms"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 26,
+   "id": "717f686e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# start = perf_counter()\n",
+    "# uuu=obs_over_exp_cooler.sum_pairwise(\n",
+    "#     clr,\n",
+    "#     view_df=hg38_arms,\n",
+    "#     transforms={\"balanced\" : lambda pix: pix[\"count\"]*pix[\"weight1\"]*pix[\"weight2\"]},\n",
+    "#     clr_weight_name=\"weight\",\n",
+    "#     ignore_diags=2,\n",
+    "#     chunksize=10_000_000,\n",
+    "# )\n",
+    "# uuu[\"exp\"] = uuu[\"balanced.sum\"]/uuu[\"n_valid\"]\n",
+    "# # uuu = uuu.reset_index(\"dist\")\n",
+    "# print(f\"it took {perf_counter()-start} sec to complete ...\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "d23f12c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "uuu = obs_over_exp_cooler.expected_full_fast(\n",
+    "    clr,\n",
+    "    view_df=hg38_arms,\n",
+    "#     smooth_cis=False,\n",
+    "#     aggregate_smoothed=False,\n",
+    "#     smooth_sigma=0.1,\n",
+    "#     aggregate_trans=False,\n",
+    "#     expected_column_name=\"expected\",\n",
+    "    ignore_diags=2,\n",
+    "    clr_weight_name='weight',\n",
+    "    chunksize=10_000_000,\n",
+    "    nproc=4,\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "97d0cf5c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>region1</th>\n",
+       "      <th>region2</th>\n",
+       "      <th>dist</th>\n",
+       "      <th>balanced.sum</th>\n",
+       "      <th>count.sum</th>\n",
+       "      <th>n_valid</th>\n",
+       "      <th>count.avg</th>\n",
+       "      <th>balanced.avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>878.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>876.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>2</td>\n",
+       "      <td>65.287351</td>\n",
+       "      <td>2738583.0</td>\n",
+       "      <td>874.0</td>\n",
+       "      <td>3133.390160</td>\n",
+       "      <td>0.074699</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>3</td>\n",
+       "      <td>41.011675</td>\n",
+       "      <td>1739972.0</td>\n",
+       "      <td>872.0</td>\n",
+       "      <td>1995.380734</td>\n",
+       "      <td>0.047032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>4</td>\n",
+       "      <td>28.473626</td>\n",
+       "      <td>1184707.0</td>\n",
+       "      <td>870.0</td>\n",
+       "      <td>1361.732184</td>\n",
+       "      <td>0.032728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6511</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>581</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6512</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>582</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6513</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>583</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6514</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>584</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6515</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>585</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6516 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      region1  region2  dist  balanced.sum  count.sum  n_valid    count.avg  \\\n",
+       "0      chr2_p   chr2_p     0           NaN        NaN    878.0          NaN   \n",
+       "1      chr2_p   chr2_p     1           NaN        NaN    876.0          NaN   \n",
+       "2      chr2_p   chr2_p     2     65.287351  2738583.0    874.0  3133.390160   \n",
+       "3      chr2_p   chr2_p     3     41.011675  1739972.0    872.0  1995.380734   \n",
+       "4      chr2_p   chr2_p     4     28.473626  1184707.0    870.0  1361.732184   \n",
+       "...       ...      ...   ...           ...        ...      ...          ...   \n",
+       "6511  chr17_q  chr17_q   581      0.000000        0.0      0.0          NaN   \n",
+       "6512  chr17_q  chr17_q   582      0.000000        0.0      0.0          NaN   \n",
+       "6513  chr17_q  chr17_q   583      0.000000        0.0      0.0          NaN   \n",
+       "6514  chr17_q  chr17_q   584      0.000000        0.0      0.0          NaN   \n",
+       "6515  chr17_q  chr17_q   585      0.000000        0.0      0.0          NaN   \n",
+       "\n",
+       "      balanced.avg  \n",
+       "0              NaN  \n",
+       "1              NaN  \n",
+       "2         0.074699  \n",
+       "3         0.047032  \n",
+       "4         0.032728  \n",
+       "...            ...  \n",
+       "6511           NaN  \n",
+       "6512           NaN  \n",
+       "6513           NaN  \n",
+       "6514           NaN  \n",
+       "6515           NaN  \n",
+       "\n",
+       "[6516 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uuu"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "b07fba4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from cooltools.sandbox import expected_smoothing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "bf022ff0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# expected_smoothing.agg_smooth_cvd?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "c6697468",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#     result_smooth = expected_smoothing.agg_smooth_cvd(\n",
+    "#         result,\n",
+    "#         sigma_log10=smooth_sigma,\n",
+    "#     )\n",
+    "#     # add smoothed columns to the result (only balanced for now)\n",
+    "#     result = result.merge(\n",
+    "#         result_smooth[[\"balanced.avg.smoothed\", _DIST]],\n",
+    "#         on=[_REGION1, _REGION2, _DIST],\n",
+    "#         how=\"left\",\n",
+    "#     )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "40a01f3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>region1</th>\n",
+       "      <th>region2</th>\n",
+       "      <th>dist</th>\n",
+       "      <th>balanced.sum</th>\n",
+       "      <th>count.sum</th>\n",
+       "      <th>n_valid</th>\n",
+       "      <th>count.avg</th>\n",
+       "      <th>balanced.avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>878.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>876.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>2</td>\n",
+       "      <td>65.287351</td>\n",
+       "      <td>2738583.0</td>\n",
+       "      <td>874.0</td>\n",
+       "      <td>3133.390160</td>\n",
+       "      <td>0.074699</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>3</td>\n",
+       "      <td>41.011675</td>\n",
+       "      <td>1739972.0</td>\n",
+       "      <td>872.0</td>\n",
+       "      <td>1995.380734</td>\n",
+       "      <td>0.047032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>chr2_p</td>\n",
+       "      <td>4</td>\n",
+       "      <td>28.473626</td>\n",
+       "      <td>1184707.0</td>\n",
+       "      <td>870.0</td>\n",
+       "      <td>1361.732184</td>\n",
+       "      <td>0.032728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6511</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>581</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6512</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>582</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6513</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>583</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6514</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>584</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6515</th>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>chr17_q</td>\n",
+       "      <td>585</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>6516 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      region1  region2  dist  balanced.sum  count.sum  n_valid    count.avg  \\\n",
+       "0      chr2_p   chr2_p     0           NaN        NaN    878.0          NaN   \n",
+       "1      chr2_p   chr2_p     1           NaN        NaN    876.0          NaN   \n",
+       "2      chr2_p   chr2_p     2     65.287351  2738583.0    874.0  3133.390160   \n",
+       "3      chr2_p   chr2_p     3     41.011675  1739972.0    872.0  1995.380734   \n",
+       "4      chr2_p   chr2_p     4     28.473626  1184707.0    870.0  1361.732184   \n",
+       "...       ...      ...   ...           ...        ...      ...          ...   \n",
+       "6511  chr17_q  chr17_q   581      0.000000        0.0      0.0          NaN   \n",
+       "6512  chr17_q  chr17_q   582      0.000000        0.0      0.0          NaN   \n",
+       "6513  chr17_q  chr17_q   583      0.000000        0.0      0.0          NaN   \n",
+       "6514  chr17_q  chr17_q   584      0.000000        0.0      0.0          NaN   \n",
+       "6515  chr17_q  chr17_q   585      0.000000        0.0      0.0          NaN   \n",
+       "\n",
+       "      balanced.avg  \n",
+       "0              NaN  \n",
+       "1              NaN  \n",
+       "2         0.074699  \n",
+       "3         0.047032  \n",
+       "4         0.032728  \n",
+       "...            ...  \n",
+       "6511           NaN  \n",
+       "6512           NaN  \n",
+       "6513           NaN  \n",
+       "6514           NaN  \n",
+       "6515           NaN  \n",
+       "\n",
+       "[6516 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "uuu"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "4aac2007",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "f,ax = plt.subplots()\n",
+    "for g,df in uuu[uuu[\"dist\"]>0].groupby([\"region1\",\"region2\"]):\n",
+    "    df.plot(x=\"dist\",y=\"balanced.avg\", loglog=True,ax=ax, label=g)\n",
+    "# # ax.set_ylim(0.5*1e-3,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "3727e842",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# f,ax = plt.subplots()\n",
+    "# uuu.loc[(0,0),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"00\")\n",
+    "# uuu.loc[(0,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"01\")\n",
+    "# uuu.loc[(1,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"11\")\n",
+    "# uuu.loc[(2,2),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"22\")\n",
+    "# uuu.loc[(2,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"23\")\n",
+    "# uuu.loc[(3,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"33\")\n",
+    "\n",
+    "# # ax.set_ylim(0.5*1e-3,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
    "id": "spare-malaysia",
    "metadata": {},
    "outputs": [
@@ -181,8 +741,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:root:Done calculating cis expected in 0.433 sec ...\n",
-      "INFO:root:Done calculating trans expected in 0.532 sec ...\n",
+      "INFO:root:Done calculating cis expected in 50.654 sec ...\n",
+      "INFO:root:Done calculating trans expected in 26.196 sec ...\n",
       "INFO:root:Returning combined expected DataFrame.\n"
      ]
     }
@@ -201,17 +761,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "precise-twins",
+   "execution_count": 52,
+   "id": "b9c9140f",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:root:Calculating observed over expected for pixels [0:52475]\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -233,60 +786,155 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>bin1_id</th>\n",
-       "      <th>bin2_id</th>\n",
-       "      <th>oe</th>\n",
+       "      <th>dist</th>\n",
+       "      <th>count.sum</th>\n",
+       "      <th>balanced.sum</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>32061001</td>\n",
+       "      <td>22391.162801</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>29927412</td>\n",
+       "      <td>22066.898493</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>0</td>\n",
        "      <td>2</td>\n",
-       "      <td>1.836246</td>\n",
+       "      <td>8706228</td>\n",
+       "      <td>6529.232708</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>1.498967</td>\n",
+       "      <td>3804582</td>\n",
+       "      <td>2843.349631</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>0</td>\n",
        "      <td>4</td>\n",
-       "      <td>1.633761</td>\n",
+       "      <td>2136953</td>\n",
+       "      <td>1592.015747</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>295212</th>\n",
+       "      <td>242040</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.002267</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>295213</th>\n",
+       "      <td>242053</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.003446</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>295214</th>\n",
+       "      <td>242067</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.001928</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>295215</th>\n",
+       "      <td>0</td>\n",
+       "      <td>104736</td>\n",
+       "      <td>81.802771</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>295216</th>\n",
+       "      <td>0</td>\n",
+       "      <td>304859</td>\n",
+       "      <td>230.234214</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>295217 rows × 3 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "   bin1_id  bin2_id        oe\n",
-       "0        0        0       NaN\n",
-       "1        0        1       NaN\n",
-       "2        0        2  1.836246\n",
-       "3        0        3  1.498967\n",
-       "4        0        4  1.633761"
+       "          dist  count.sum  balanced.sum\n",
+       "0            0   32061001  22391.162801\n",
+       "1            1   29927412  22066.898493\n",
+       "2            2    8706228   6529.232708\n",
+       "3            3    3804582   2843.349631\n",
+       "4            4    2136953   1592.015747\n",
+       "...        ...        ...           ...\n",
+       "295212  242040          1      0.002267\n",
+       "295213  242053          1      0.003446\n",
+       "295214  242067          1      0.001928\n",
+       "295215       0     104736     81.802771\n",
+       "295216       0     304859    230.234214\n",
+       "\n",
+       "[295217 rows x 3 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 52,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
+   "source": [
+    "hui.reset_index(level=[\"r1\",\"r2\"],drop=True).reset_index(level=\"dist\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "cb483c14",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['chr2_p', 'chr2_p', 'chr2_p', ..., 'chr2_q', 'chr17_p', 'chr17_q'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hg38_arms.loc[hui.index.get_level_values(\"r2\"), \"name\"].to_numpy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63c9d58c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "zzz=expected_df.set_index([\"r1\",\"r2\"]).rename(columns={\"balanced.avg\":\"exp\"})\n",
+    "f,ax = plt.subplots()\n",
+    "zzz.loc[(0,0),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"00\")\n",
+    "zzz.loc[(0,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"01\")\n",
+    "zzz.loc[(1,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"11\")\n",
+    "zzz.loc[(2,2),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"22\")\n",
+    "zzz.loc[(2,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"23\")\n",
+    "zzz.loc[(3,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"33\")\n",
+    "ax.set_ylim(0.5*1e-3,1e-1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "precise-twins",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# collect obs/exp for chunks of pixel table (in memory for 1Mb cooler)\n",
     "results = []\n",
@@ -306,18 +954,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "complete-funeral",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "generated symmetrix obs/exp matrix of size 327 X 327\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# res_df: sparse matrix -> dense matrix for plotting\n",
     "N = len(clr.bins())\n",
@@ -332,33 +972,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "current-doctor",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7fc2194058b0>"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1008x720 with 4 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# plot observed and stitched obs/exp side by side\n",
     "istart, iend = 0, 327\n",
@@ -392,7 +1009,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "separated-publication",
    "metadata": {},
    "outputs": [],
@@ -403,7 +1020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "therapeutic-semester",
    "metadata": {},
    "outputs": [],
@@ -417,20 +1034,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "sublime-institution",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:root:Done calculating cis expected in 16.787 sec ...\n",
-      "INFO:root:Done calculating trans expected in 7.697 sec ...\n",
-      "INFO:root:Returning combined expected DataFrame.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# re-calculate full expected (cis + trans) at higher resolution\n",
     "expected_df = obs_over_exp_cooler.expected_full(\n",
@@ -445,7 +1052,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "pointed-philosophy",
    "metadata": {},
    "outputs": [],
@@ -466,32 +1073,7 @@
    "execution_count": null,
    "id": "moderate-machinery",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO:root:Calculating observed over expected for pixels [0:10000000]\n",
-      "INFO:cooler.create:Writing chunk 0: /data/old_desktop/src/cooltools/cooltools/sandbox/tmpq67gm7hp.multi.cool::0\n",
-      "INFO:cooler.create:Creating cooler at \"/data/old_desktop/src/cooltools/cooltools/sandbox/tmpq67gm7hp.multi.cool::/0\"\n",
-      "INFO:cooler.create:Writing chroms\n",
-      "INFO:cooler.create:Writing bins\n",
-      "/home/sergpolly/miniconda3/envs/devcool/lib/python3.9/site-packages/cooler/core.py:123: FutureWarning: is_categorical is deprecated and will be removed in a future version. Use is_categorical_dtype instead.\n",
-      "  elif is_categorical(data):\n",
-      "INFO:cooler.create:Writing pixels\n",
-      "INFO:cooler.create:Writing indexes\n",
-      "INFO:cooler.create:Writing info\n",
-      "INFO:root:Calculating observed over expected for pixels [10000000:20000000]\n",
-      "INFO:cooler.create:Writing chunk 1: /data/old_desktop/src/cooltools/cooltools/sandbox/tmpq67gm7hp.multi.cool::1\n",
-      "INFO:cooler.create:Creating cooler at \"/data/old_desktop/src/cooltools/cooltools/sandbox/tmpq67gm7hp.multi.cool::/1\"\n",
-      "INFO:cooler.create:Writing chroms\n",
-      "INFO:cooler.create:Writing bins\n",
-      "/home/sergpolly/miniconda3/envs/devcool/lib/python3.9/site-packages/cooler/core.py:123: FutureWarning: is_categorical is deprecated and will be removed in a future version. Use is_categorical_dtype instead.\n",
-      "  elif is_categorical(data):\n",
-      "INFO:cooler.create:Writing pixels\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# write oe_pixels_stream into cooler - with custom column \"oe\" (can do \"count\":float for higlass)\n",
     "cooler.create_cooler(\n",

From fa58ad2809d9599180b1299f32cabdbee0db60d1 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 21 Sep 2022 19:18:02 -0400
Subject: [PATCH 02/17] working expected_full_fast, updated example notebook

---
 cooltools/sandbox/obs_over_exp_cooler.py      | 259 +++--
 .../observed_over_expected_example.ipynb      | 924 +++++-------------
 2 files changed, 383 insertions(+), 800 deletions(-)

diff --git a/cooltools/sandbox/obs_over_exp_cooler.py b/cooltools/sandbox/obs_over_exp_cooler.py
index 35fc9e80..0e57f841 100644
--- a/cooltools/sandbox/obs_over_exp_cooler.py
+++ b/cooltools/sandbox/obs_over_exp_cooler.py
@@ -2,14 +2,29 @@
 This module enables construction of observed over expected pixels tables and
 storing them inside a cooler.
 
-It includes 2 functions.
+It includes 3 main functions.
 expected_full - is a convenience function that calculates cis and trans-expected
     and "stitches" them togeter. Such a stitched expected that "covers"
     entire Hi-C heatmap can be easily merged with the pixel table.
+expected_full_fast - generated the same output as `expected_full` but ~2x faster.
+    Efficiency is achieved through calculating cis and trans expected in one
+    pass of the pixel table. Post-processing is not fully implemented yet.
 obs_over_exp_generator - is a function/generator(lazy iterator) that merges
     pre-calculated full expected with the pixel table in clr and yields chunks
     of observed/expected pixel table. Such a "stream" can be used in cooler.create
     as a "pixels" argument to write obs/exp cooler-file.
+
+It also includes 3 helper functions (used in `expected_full_fast`):
+make_pairwise_expected_table - a function that creates an empty table for the
+    full expected with all the right sizes and number of valid pixels pre-filled.
+    Combines functionality of `make_diag_tables` and `make_block_tables` from the API.
+sum_pairwise - a function that calculates the full pixel summary for all pairwise
+    combinations of the regions in the view, and for each genomic separation for
+    cis-combinations of regions. In a nutshell - it calls `make_pairwise_expected_table`
+    to generate empty table for expected, and it gets filled by applying `_sum_` to the
+    pixels table.
+_sum_ - a function that does the actual summing of pixel values grouped by regions
+    and genomic separations - can work on a chunk of pixel table.
 """
 import time
 import logging
@@ -50,12 +65,15 @@
     block_expected_dtypes
 )
 
+from cooltools.sandbox import expected_smoothing
 
 # common expected_df column names, take from schemas
-_REGION1 = list(diag_expected_dtypes)[0]
-_REGION2 = list(diag_expected_dtypes)[1]
-_DIST = list(diag_expected_dtypes)[2]
-_NUM_VALID = list(diag_expected_dtypes)[3]
+_REGION1_NAME = list(diag_expected_dtypes)[0]
+_REGION2_NAME = list(diag_expected_dtypes)[1]
+_DIST_NAME = list(diag_expected_dtypes)[2]
+_NUM_VALID_NAME = list(diag_expected_dtypes)[3]
+
+TRANS_DIST_VALUE = -1  # special value for the "genomic distance" for the trans data
 
 logging.basicConfig(level=logging.INFO)
 
@@ -146,9 +164,8 @@ def expected_full(
         chunksize=chunksize,
         nproc=nproc,
     )
-    # pretend that they also have a "dist"
-    # to make them mergeable with cvd
-    cpb["dist"] = -1
+    # pretend that they also have a "dist" to make them mergeable with cvd
+    cpb["dist"] = TRANS_DIST_VALUE
     time_elapsed = time.perf_counter() - time_start
     logging.info(f"Done calculating trans expected in {time_elapsed:.3f} sec ...")
 
@@ -241,13 +258,13 @@ def make_pairwise_expected_table(clr, view_df, clr_weight_name):
                     df = dtables[(name1, name2)].reset_index()
                     df.insert(0, "r2", _r2)
                     df.insert(0, "r1", _r1)
-                    _tables.append(df.set_index(["r1", "r2", _DIST]))
+                    _tables.append(df.set_index(["r1", "r2", _DIST_NAME]))
                 if (chrom1 != chrom2):
                     df = pd.DataFrame(btables[(name1, name2)], index=[0])
-                    df.insert(0, _DIST, -1)  # special trans-value for distance
+                    df.insert(0, _DIST_NAME, TRANS_DIST_VALUE)  # special trans-value for distance
                     df.insert(0, "r2", _r2)
                     df.insert(0, "r1", _r1)
-                    _tables.append(df.set_index(["r1", "r2", _DIST]))
+                    _tables.append(df.set_index(["r1", "r2", _DIST_NAME]))
 
     # return all concatenated DataFrame for cis and trans blocks:
     return pd.concat( _tables )
@@ -291,17 +308,17 @@ def _sum_(clr, fields, transforms, clr_weight_name, regions, span):
     # create a cis-mask, trans-mask
     cis_mask = pixels["chrom1"] == pixels["chrom2"]
 
-    # initialize _DIST as 0 for all pixels
+    # initialize _DIST_NAME as 0 for all pixels
     # consider using -1 as a special value to distinguish trans data easily ...
-    pixels.loc[:, _DIST] = -1
-    # calculate actual genomic _DIST for cis-pixels:
-    pixels.loc[cis_mask, _DIST] = pixels.loc[cis_mask, "bin2_id"] - pixels.loc[cis_mask, "bin1_id"]
+    pixels.loc[:, _DIST_NAME] = TRANS_DIST_VALUE
+    # calculate actual genomic _DIST_NAME for cis-pixels:
+    pixels.loc[cis_mask, _DIST_NAME] = pixels.loc[cis_mask, "bin2_id"] - pixels.loc[cis_mask, "bin1_id"]
     # apply requested transforms, e.g. balancing:
     for field, t in transforms.items():
         pixels[field] = t(pixels)
     
-    # perform aggregation by r1, r2 and _DIST
-    _blocks = pixels.groupby(["r1", "r2", _DIST])
+    # perform aggregation by r1, r2 and _DIST_NAME
+    _blocks = pixels.groupby(["r1", "r2", _DIST_NAME])
     
     # calculate summaries and add ".sum" suffix to field column-names
     return _blocks[fields].sum().add_suffix(".sum")
@@ -386,19 +403,19 @@ def sum_pairwise(
     # accumulate every chunk of summary results to exp_table
     result_df = reduce(lambda df1,df2: df1.add(df2, fill_value=0), results, exp_table)
 
-    # following can be done easily, when _DIST has a special value for trans ...
+    # following can be done easily, when _DIST_NAME has a special value for trans ...
     if ignore_diags:
         for _d in range(ignore_diags):
             # extract fist "ignore_diags" from DataFrame and fill them with NaNs
-            _idx = result_df.xs(_d, level=_DIST, drop_level=False).index
+            _idx = result_df.xs(_d, level=_DIST_NAME, drop_level=False).index
             result_df.loc[_idx, summary_fields] = np.nan
 
     # # returning a pd.DataFrame for API consistency:
-    result_df.reset_index(level=_DIST, inplace=True)
+    result_df.reset_index(level=_DIST_NAME, inplace=True)
     # region1 for the final table
-    result_df.insert(0, _REGION1, view_df.loc[result_df.index.get_level_values("r1"), "name"].to_numpy())
+    result_df.insert(0, _REGION1_NAME, view_df.loc[result_df.index.get_level_values("r1"), "name"].to_numpy())
     # region2 for the final table
-    result_df.insert(1, _REGION2, view_df.loc[result_df.index.get_level_values("r2"), "name"].to_numpy())
+    result_df.insert(1, _REGION2_NAME, view_df.loc[result_df.index.get_level_values("r2"), "name"].to_numpy())
     # drop r1/r2 region labels
     result_df.reset_index(level=["r1", "r2"], drop=True, inplace=True)
 
@@ -409,7 +426,7 @@ def expected_full_fast(
         clr,
         view_df=None,
         smooth_cis=False,
-        aggregate_smoothed=False,
+        aggregate_cis=False,
         smooth_sigma=0.1,
         aggregate_trans=False,
         expected_column_name="expected",
@@ -482,14 +499,23 @@ def expected_full_fast(
             raise ValueError("view_df is not a valid viewframe or incompatible") from e
 
     # define transforms - balanced and raw ('count') for now
+    cols = {
+        "dist": _DIST_NAME,
+        "n_pixels": _NUM_VALID_NAME,
+        "smooth_suffix": ".smooth",
+    }
     if clr_weight_name is None:
         # no transforms
         transforms = {}
+        cols["n_contacts"] = "count.sum"
+        cols["contact_freq"] = "count.avg"
     elif is_cooler_balanced(clr, clr_weight_name):
         # define balanced data transform:
         weight1 = clr_weight_name + "1"
         weight2 = clr_weight_name + "2"
         transforms = {"balanced": lambda p: p["count"] * p[weight1] * p[weight2]}
+        cols["n_contacts"] = "balanced.sum"
+        cols["contact_freq"] = "balanced.avg"
     else:
         raise ValueError(
             "cooler is not balanced, or"
@@ -503,7 +529,8 @@ def expected_full_fast(
     else:
         map_ = map
 
-    # using try-clause to close mp.Pool properly
+    # using try-clause to close mp.Pool properly ans start the timer
+    time_start = time.perf_counter()
     try:
         result = sum_pairwise(
             clr,
@@ -518,88 +545,112 @@ def expected_full_fast(
         if nproc > 1:
             pool.close()
 
-
     # calculate actual averages by dividing sum by n_valid:
-    for key in chain(["count"], transforms):
-        result[f"{key}.avg"] = result[f"{key}.sum"] / result[_NUM_VALID]
-
-    # # additional smoothing and aggregating options would add columns only, not replace them
-    # if smooth:
-    #     result_smooth = expected_smoothing.agg_smooth_cvd(
-    #         result,
-    #         sigma_log10=smooth_sigma,
-    #     )
-    #     # add smoothed columns to the result (only balanced for now)
-    #     result = result.merge(
-    #         result_smooth[["balanced.avg.smoothed", _DIST]],
-    #         on=[_REGION1, _REGION2, _DIST],
-    #         how="left",
-    #     )
-    #     if aggregate_smoothed:
-    #         result_smooth_agg = expected_smoothing.agg_smooth_cvd(
-    #             result,
-    #             groupby=None,
-    #             sigma_log10=smooth_sigma,
-    #         ).rename(columns={"balanced.avg.smoothed": "balanced.avg.smoothed.agg"})
-    #         # add smoothed columns to the result
-    #         result = result.merge(
-    #             result_smooth_agg[["balanced.avg.smoothed.agg", _DIST]],
-    #             on=[
-    #                 _DIST,
-    #             ],
-    #             how="left",
-    #         )
+    result[cols["contact_freq"]] = result[cols["n_contacts"]].divide(
+        result[cols["n_pixels"]]
+    )
 
-    return result
+    # annotate result with the region index and chromosomes
+    view_label = view_df \
+                .reset_index() \
+                .rename(columns={"index":"r"}) \
+                .set_index("name")
 
+    # add r1 r2 labels to the final dataframe for obs/exp merging
+    result["r1"] = view_label.loc[result["region1"], "r"].to_numpy()
+    result["r2"] = view_label.loc[result["region2"], "r"].to_numpy()
+
+    # initialize empty column with the final name of expected
+    result.insert(loc=len(result.columns), column=expected_column_name, value=np.nan)
+
+    # annotate result with chromosomes in case chrom-level aggregation is requested
+    if "chrom" in [aggregate_trans, aggregate_cis]:
+        result["chrom1"] = view_label.loc[result["region1"], "chrom"].to_numpy()
+        result["chrom2"] = view_label.loc[result["region2"], "chrom"].to_numpy()
+
+    if aggregate_cis:
+        if aggregate_cis == "chrom":
+            grp_columns = ["chrom1", "chrom2"]  # chrom-level aggregation
+        elif aggregate_cis == "genome":
+            grp_columns = None  # genome-wide level aggregation
+        else:
+            raise ValueError("aggregate_cis could be only chrom, genome or False")
+    else:
+        grp_columns = [_REGION1_NAME, _REGION2_NAME]  # no aggregation, keep as in view_df
 
-    # # annotate expected_df with the region index and chromosomes
-    # view_label = view_df \
-    #             .reset_index() \
-    #             .rename(columns={"index":"r"}) \
-    #             .set_index("name")
-
-    # # which expected column to use, based on requested "modifications":
-    # cis_expected_name = "balanced.avg" if clr_weight_name else "count.avg"
-    # if smooth_cis:
-    #     cis_expected_name = f"{cis_expected_name}.smoothed"
-    #     if aggregate_smoothed:
-    #         cis_expected_name = f"{cis_expected_name}.agg"
-    # # copy to the prescribed column for the final output:
-    # cvd[expected_column_name] = cvd[cis_expected_name].copy()
-
-    # # aggregate trans if requested and deide which trans-expected column to use:
-    # trans_expected_name = "balanced.avg" if clr_weight_name else "count.avg"
-    # if aggregate_trans:
-    #     trans_expected_name = f"{trans_expected_name}.agg"
-    #     additive_cols = ["n_valid","count.sum"]
-    #     if clr_weight_name:
-    #         additive_cols.append("balanced.sum")
-    #     # groupby chrom1, chrom2 and aggregate additive fields (sums and n_valid):
-    #     _cpb_agg = cpb.groupby(
-    #         [
-    #             view_label["chrom"].loc[cpb["region1"]].to_numpy(),  # chrom1
-    #             view_label["chrom"].loc[cpb["region2"]].to_numpy(),  # chrom2
-    #         ]
-    #     )[additive_cols].transform("sum")
-    #     # recalculate aggregated averages:
-    #     cpb["count.avg.agg"] = _cpb_agg["count.sum"]/_cpb_agg["n_valid"]
-    #     if clr_weight_name:
-    #         cpb["balanced.avg.agg"] = _cpb_agg["balanced.sum"]/_cpb_agg["n_valid"]
-    # # copy to the prescribed column for the final output:
-    # cpb[expected_column_name] = cpb[trans_expected_name].copy()
-
-    # # concatenate cvd and cpb (cis and trans):
-    # expected_df = pd.concat([cvd, cpb], ignore_index=True)
-
-    # # add r1 r2 labels to the final dataframe for obs/exp merging
-    # expected_df["r1"] = view_label["r"].loc[expected_df["region1"]].to_numpy()
-    # expected_df["r2"] = view_label["r"].loc[expected_df["region2"]].to_numpy()
-
-    # # and return joined cis/trans expected in the same format
-    # logging.info(f"Returning combined expected DataFrame.")
-    # # consider purging unneccessary columns here
-    # return expected_df
+    # prepare cis/trans masks for smoothing, aggregation and/or simply copying values
+    # to the final column:
+    _cis_mask = result[_DIST_NAME] != TRANS_DIST_VALUE
+    _trans_mask = result[_DIST_NAME] == TRANS_DIST_VALUE
+
+    # additive columns for aggregation
+    additive_cols = [ cols["n_pixels"], cols["n_contacts"] ]
+
+    # additional smoothing and aggregating options would add columns only, not replace them
+    if smooth_cis:
+        # smooth and aggregate
+        _smooth_df = expected_smoothing.agg_smooth_cvd(
+            result.loc[_cis_mask],
+            groupby=grp_columns,
+            sigma_log10=smooth_sigma,
+            cols=cols,
+        )
+        _smooth_col_name = cols["contact_freq"] + cols["smooth_suffix"]
+        # add smoothed columns to the result
+        result = result.merge(
+            _smooth_df[[ _DIST_NAME, _smooth_col_name ]],
+            on=[*(grp_columns or []), _DIST_NAME],
+            how="left",
+        )
+        # add the results to the expected column
+        result.loc[_cis_mask, expected_column_name] = result.loc[_cis_mask, _smooth_col_name]
+    elif aggregate_cis:
+        # aggregate only if requested:
+        _agg_df = results.loc[_cis_mask] \
+            .groupby([*(grp_columns or []), _DIST_NAME])[additive_cols] \
+            .transform("sum") \
+            .add_suffix(".agg")
+        # calculate new average
+        _agg_df[expected_column_name] = _agg_df[f"""{cols["n_contacts"]}.agg"""].divide(
+            _agg_df[f"""{cols["n_pixels"]}.agg"""]
+        )
+        # add aggregated result to the result df
+        result.loc[_cis_mask, expected_column_name] = _agg_df[expected_column_name]
+    else:
+        # just copy unchanged result to expected_column_name
+        result.loc[_cis_mask, expected_column_name] = result.loc[_cis_mask, cols["contact_freq"]]
+
+    # aggregate trans on requested level and copy result into final expected column:
+    if aggregate_trans:
+        if aggregate_trans == "chrom":
+            # groupby chromosomes and sum up additive values:
+            _trans_agg_df = result.loc[_trans_mask] \
+                .groupby(["chrom1", "chrom2"])[additive_cols] \
+                .transform("sum") \
+                .add_suffix(".agg")
+        elif aggregate_trans == "genome":
+            # genome-wide transform :
+            _trans_df = result.loc[_trans_mask]
+            _trans_agg_df = result.loc[_trans_mask, additive_cols] \
+                .transform("sum") \
+                .add_suffix(".agg")
+        else:
+            raise ValueError("aggregate_trans could be only chrom, genome or False")
+        # complete aggregation by recalculating new average:
+        _trans_agg_df[expected_column_name] = _trans_agg_df[f"""{cols["n_contacts"]}.agg"""].divide(
+            _trans_agg_df[f"""{cols["n_pixels"]}.agg"""]
+        )
+        # and adding aggregated result to the result df:
+        result.loc[_trans_mask, expected_column_name] = _trans_agg_df[expected_column_name]
+    else:
+        # just copy unchanged result to expected_column_name
+        result.loc[_trans_mask, expected_column_name] = result.loc[_trans_mask, cols["contact_freq"]]
+
+    # time is up
+    time_elapsed = time.perf_counter() - time_start
+    logging.info(f"Done calculating full expected {time_elapsed:.3f} sec ...")
+
+    return result
 
 
 def obs_over_exp_generator(
@@ -639,7 +690,7 @@ def obs_over_exp_generator(
     ------
     pixel_df: pd.DataFrame
         chunks of pixels with observed over expected
-"""
+    """
 
     # use the same view that was used to calculate full expected
     if view_df is None:
@@ -687,7 +738,7 @@ def obs_over_exp_generator(
         pixels = pixels.astype({"r1":int, "r2":int})
 
         # trans pixels will have "feature"-dist of 0
-        pixels["dist"] = 0
+        pixels["dist"] = TRANS_DIST_VALUE
         # cis pixels will have "feature"-dist "bind2_id - bin1_id"
         cis_mask = (pixels["chrom1"] == pixels["chrom2"])
         pixels.loc[cis_mask,"dist"] = pixels.loc[cis_mask,"bin2_id"] - pixels.loc[cis_mask,"bin1_id"]
diff --git a/cooltools/sandbox/observed_over_expected_example.ipynb b/cooltools/sandbox/observed_over_expected_example.ipynb
index 5ba3c675..0b9d962c 100644
--- a/cooltools/sandbox/observed_over_expected_example.ipynb
+++ b/cooltools/sandbox/observed_over_expected_example.ipynb
@@ -1,29 +1,8 @@
 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "75110361",
-   "metadata": {},
-   "source": [
-    "### beware when working with mcool files generated older version of `cooler zoomify` (circa <0.8.4) - those that had a split pixel issue https://github.com/open2c/cooler/issues/270\n",
-    "\n",
-    "whenever this is the case - one should rezoomify the coolers"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "bd440b57",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
    "id": "classical-promise",
    "metadata": {},
    "outputs": [],
@@ -36,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "saving-waterproof",
    "metadata": {},
    "outputs": [],
@@ -47,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "fifth-geology",
    "metadata": {},
    "outputs": [],
@@ -60,17 +39,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "4c2e8715",
+   "execution_count": 4,
+   "id": "484f0e3a",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from time import perf_counter"
+    "%load_ext autoreload\n",
+    "%autoreload 2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "christian-bobby",
    "metadata": {},
    "outputs": [
@@ -83,27 +63,25 @@
     }
    ],
    "source": [
-    "# clr = cooler.Cooler(\"./ALV-repo/Hap1-WT-combined.mcool::/resolutions/500000\")\n",
-    "# download test data\n",
-    "# this file is 145 Mb, and may take a few seconds to download\n",
+    "# download test data, this file is 145 Mb, and may take a few seconds to download\n",
     "cool_file = cooltools.download_data(\"HFF_MicroC\", cache=True, data_dir='./')    \n",
     "print(cool_file)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 6,
    "id": "fiscal-worship",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Load a Hi-C map at a 1Mb resolution from a cooler file.\n",
-    "clr = cooler.Cooler('./test.mcool::/resolutions/100000')"
+    "clr = cooler.Cooler('./test.mcool::/resolutions/1000000')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 7,
    "id": "threatened-commissioner",
    "metadata": {},
    "outputs": [
@@ -175,7 +153,7 @@
        "3  chr17  24714921   83257441  chr17_q"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -188,583 +166,134 @@
     "hg38_arms = bioframe.make_chromarms(hg38_chromsizes,  hg38_cens)\n",
     "# select only those chromosomes available in cooler\n",
     "hg38_arms = hg38_arms[hg38_arms.chrom.isin(clr.chromnames)].reset_index(drop=True)\n",
-    "\n",
-    "# # when you've got no internet ...\n",
-    "# _chrom=[\"chr2\",\"chr2\",\"chr17\",\"chr17\"]\n",
-    "# _start=[0,93139351,0,24714921]\n",
-    "# _end=[93139351,242193529,24714921,83257441]\n",
-    "# _name=[\"chr2_p\",\"chr2_q\",\"chr17_p\",\"chr17_q\"]\n",
-    "# hg38_arms = pd.DataFrame({\"chrom\":_chrom,\"start\":_start,\"end\":_end,\"name\":_name})\n",
-    "\n",
     "hg38_arms"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "id": "717f686e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# start = perf_counter()\n",
-    "# uuu=obs_over_exp_cooler.sum_pairwise(\n",
-    "#     clr,\n",
-    "#     view_df=hg38_arms,\n",
-    "#     transforms={\"balanced\" : lambda pix: pix[\"count\"]*pix[\"weight1\"]*pix[\"weight2\"]},\n",
-    "#     clr_weight_name=\"weight\",\n",
-    "#     ignore_diags=2,\n",
-    "#     chunksize=10_000_000,\n",
-    "# )\n",
-    "# uuu[\"exp\"] = uuu[\"balanced.sum\"]/uuu[\"n_valid\"]\n",
-    "# # uuu = uuu.reset_index(\"dist\")\n",
-    "# print(f\"it took {perf_counter()-start} sec to complete ...\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "id": "d23f12c3",
+   "execution_count": 8,
+   "id": "spare-malaysia",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:root:Done calculating cis expected in 0.920 sec ...\n",
+      "INFO:root:Done calculating trans expected in 0.616 sec ...\n",
+      "INFO:root:Returning combined expected DataFrame.\n"
+     ]
+    }
+   ],
    "source": [
-    "uuu = obs_over_exp_cooler.expected_full_fast(\n",
+    "# calculate full expected (cis + trans)\n",
+    "# inside of this function \n",
+    "expected_df = obs_over_exp_cooler.expected_full(\n",
     "    clr,\n",
     "    view_df=hg38_arms,\n",
-    "#     smooth_cis=False,\n",
-    "#     aggregate_smoothed=False,\n",
-    "#     smooth_sigma=0.1,\n",
-    "#     aggregate_trans=False,\n",
-    "#     expected_column_name=\"expected\",\n",
-    "    ignore_diags=2,\n",
-    "    clr_weight_name='weight',\n",
-    "    chunksize=10_000_000,\n",
-    "    nproc=4,\n",
-    ")\n"
+    "    smooth_cis=False,\n",
+    "    aggregate_trans=True,\n",
+    "    expected_column_name=\"expected\",\n",
+    "    nproc=2,\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "id": "97d0cf5c",
+   "execution_count": 9,
+   "id": "1c44e996",
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>region1</th>\n",
-       "      <th>region2</th>\n",
-       "      <th>dist</th>\n",
-       "      <th>balanced.sum</th>\n",
-       "      <th>count.sum</th>\n",
-       "      <th>n_valid</th>\n",
-       "      <th>count.avg</th>\n",
-       "      <th>balanced.avg</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>878.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>1</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>876.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>2</td>\n",
-       "      <td>65.287351</td>\n",
-       "      <td>2738583.0</td>\n",
-       "      <td>874.0</td>\n",
-       "      <td>3133.390160</td>\n",
-       "      <td>0.074699</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41.011675</td>\n",
-       "      <td>1739972.0</td>\n",
-       "      <td>872.0</td>\n",
-       "      <td>1995.380734</td>\n",
-       "      <td>0.047032</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>4</td>\n",
-       "      <td>28.473626</td>\n",
-       "      <td>1184707.0</td>\n",
-       "      <td>870.0</td>\n",
-       "      <td>1361.732184</td>\n",
-       "      <td>0.032728</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6511</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>581</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6512</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>582</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6513</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>583</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6514</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>584</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6515</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>585</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>6516 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      region1  region2  dist  balanced.sum  count.sum  n_valid    count.avg  \\\n",
-       "0      chr2_p   chr2_p     0           NaN        NaN    878.0          NaN   \n",
-       "1      chr2_p   chr2_p     1           NaN        NaN    876.0          NaN   \n",
-       "2      chr2_p   chr2_p     2     65.287351  2738583.0    874.0  3133.390160   \n",
-       "3      chr2_p   chr2_p     3     41.011675  1739972.0    872.0  1995.380734   \n",
-       "4      chr2_p   chr2_p     4     28.473626  1184707.0    870.0  1361.732184   \n",
-       "...       ...      ...   ...           ...        ...      ...          ...   \n",
-       "6511  chr17_q  chr17_q   581      0.000000        0.0      0.0          NaN   \n",
-       "6512  chr17_q  chr17_q   582      0.000000        0.0      0.0          NaN   \n",
-       "6513  chr17_q  chr17_q   583      0.000000        0.0      0.0          NaN   \n",
-       "6514  chr17_q  chr17_q   584      0.000000        0.0      0.0          NaN   \n",
-       "6515  chr17_q  chr17_q   585      0.000000        0.0      0.0          NaN   \n",
-       "\n",
-       "      balanced.avg  \n",
-       "0              NaN  \n",
-       "1              NaN  \n",
-       "2         0.074699  \n",
-       "3         0.047032  \n",
-       "4         0.032728  \n",
-       "...            ...  \n",
-       "6511           NaN  \n",
-       "6512           NaN  \n",
-       "6513           NaN  \n",
-       "6514           NaN  \n",
-       "6515           NaN  \n",
-       "\n",
-       "[6516 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:root:Done calculating full expected 1.184 sec ...\n"
+     ]
     }
    ],
    "source": [
-    "uuu"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "id": "b07fba4e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from cooltools.sandbox import expected_smoothing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "bf022ff0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# expected_smoothing.agg_smooth_cvd?"
+    "# essentially same function, but faster - does only one pass over cooler file\n",
+    "# instead of 2\n",
+    "fast_expected_df = obs_over_exp_cooler.expected_full_fast(\n",
+    "    clr,\n",
+    "    view_df=hg38_arms,  # same view for cis and trans\n",
+    "    smooth_cis=False,\n",
+    "    aggregate_trans=\"chrom\",\n",
+    "    expected_column_name=\"expected\",\n",
+    "    nproc=2,\n",
+    ")\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "c6697468",
+   "cell_type": "markdown",
+   "id": "d9139846",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "#     result_smooth = expected_smoothing.agg_smooth_cvd(\n",
-    "#         result,\n",
-    "#         sigma_log10=smooth_sigma,\n",
-    "#     )\n",
-    "#     # add smoothed columns to the result (only balanced for now)\n",
-    "#     result = result.merge(\n",
-    "#         result_smooth[[\"balanced.avg.smoothed\", _DIST]],\n",
-    "#         on=[_REGION1, _REGION2, _DIST],\n",
-    "#         how=\"left\",\n",
-    "#     )\n"
+    "### typical output of `expectedf_full`\n",
+    "\n",
+    "region1 | region2 | dist | n_valid | balanced.sum | balanced.avg | balanced.avg.smooth | expected\n",
+    "-- | -- | -- | -- | -- | -- | -- | --\n",
+    "chr2_p | chr2_p | 0 | 878.0 | NaN | NaN | NaN | NaN\n",
+    "chr2_p | chr2_p | 1 | 876.0 | NaN | NaN | 0.000795 | 0.000795\n",
+    "chr2_p | chr2_p | 2 | 874.0 | 65.287351 | 0.074699 | 0.068918 | 0.068918\n",
+    "chr2_p | chr2_p | 3 | 872.0 | 41.011675 | 0.047032 | 0.045381 | 0.045381\n",
+    "... | ... | ... | ... | ... | ... | ... | ...\n",
+    "chr2_p | chr2_q | 2421 | 0.0 | 0.000000 | NaN | 0.000050 | 0.000050\n",
+    "chr2_p | chr17_p | -1 | 174722.0 | 3.940185 | 0.000023 | NaN | 0.000022\n",
+    "chr2_p | chr17_q | -1 | 477632.0 | 10.879623 | 0.000023 | NaN | 0.000022\n",
+    "chr2_q | chr17_p | -1 | 284769.0 | 5.839495 | 0.000021 | NaN | 0.000022\n",
+    "chr2_q | chr17_q | -1 | 778464.0 | 16.283992 | 0.000021 | NaN | 0.000022"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "40a01f3c",
+   "cell_type": "markdown",
+   "id": "823696da",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>region1</th>\n",
-       "      <th>region2</th>\n",
-       "      <th>dist</th>\n",
-       "      <th>balanced.sum</th>\n",
-       "      <th>count.sum</th>\n",
-       "      <th>n_valid</th>\n",
-       "      <th>count.avg</th>\n",
-       "      <th>balanced.avg</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>878.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>1</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>876.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>2</td>\n",
-       "      <td>65.287351</td>\n",
-       "      <td>2738583.0</td>\n",
-       "      <td>874.0</td>\n",
-       "      <td>3133.390160</td>\n",
-       "      <td>0.074699</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41.011675</td>\n",
-       "      <td>1739972.0</td>\n",
-       "      <td>872.0</td>\n",
-       "      <td>1995.380734</td>\n",
-       "      <td>0.047032</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>chr2_p</td>\n",
-       "      <td>4</td>\n",
-       "      <td>28.473626</td>\n",
-       "      <td>1184707.0</td>\n",
-       "      <td>870.0</td>\n",
-       "      <td>1361.732184</td>\n",
-       "      <td>0.032728</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6511</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>581</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6512</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>582</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6513</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>583</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6514</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>584</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6515</th>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>chr17_q</td>\n",
-       "      <td>585</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>6516 rows × 8 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      region1  region2  dist  balanced.sum  count.sum  n_valid    count.avg  \\\n",
-       "0      chr2_p   chr2_p     0           NaN        NaN    878.0          NaN   \n",
-       "1      chr2_p   chr2_p     1           NaN        NaN    876.0          NaN   \n",
-       "2      chr2_p   chr2_p     2     65.287351  2738583.0    874.0  3133.390160   \n",
-       "3      chr2_p   chr2_p     3     41.011675  1739972.0    872.0  1995.380734   \n",
-       "4      chr2_p   chr2_p     4     28.473626  1184707.0    870.0  1361.732184   \n",
-       "...       ...      ...   ...           ...        ...      ...          ...   \n",
-       "6511  chr17_q  chr17_q   581      0.000000        0.0      0.0          NaN   \n",
-       "6512  chr17_q  chr17_q   582      0.000000        0.0      0.0          NaN   \n",
-       "6513  chr17_q  chr17_q   583      0.000000        0.0      0.0          NaN   \n",
-       "6514  chr17_q  chr17_q   584      0.000000        0.0      0.0          NaN   \n",
-       "6515  chr17_q  chr17_q   585      0.000000        0.0      0.0          NaN   \n",
-       "\n",
-       "      balanced.avg  \n",
-       "0              NaN  \n",
-       "1              NaN  \n",
-       "2         0.074699  \n",
-       "3         0.047032  \n",
-       "4         0.032728  \n",
-       "...            ...  \n",
-       "6511           NaN  \n",
-       "6512           NaN  \n",
-       "6513           NaN  \n",
-       "6514           NaN  \n",
-       "6515           NaN  \n",
-       "\n",
-       "[6516 rows x 8 columns]"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
-    "uuu"
+    "### compare results between full expected calculated 2 different ways ..."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "id": "4aac2007",
+   "execution_count": 10,
+   "id": "5af93c8e",
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "comparison tests: True True True True True\n"
+     ]
     }
    ],
    "source": [
-    "f,ax = plt.subplots()\n",
-    "for g,df in uuu[uuu[\"dist\"]>0].groupby([\"region1\",\"region2\"]):\n",
-    "    df.plot(x=\"dist\",y=\"balanced.avg\", loglog=True,ax=ax, label=g)\n",
-    "# # ax.set_ylim(0.5*1e-3,1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "id": "3727e842",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# f,ax = plt.subplots()\n",
-    "# uuu.loc[(0,0),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"00\")\n",
-    "# uuu.loc[(0,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"01\")\n",
-    "# uuu.loc[(1,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"11\")\n",
-    "# uuu.loc[(2,2),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"22\")\n",
-    "# uuu.loc[(2,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"23\")\n",
-    "# uuu.loc[(3,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"33\")\n",
+    "_1 = expected_df.sort_values(by=[\"region1\", \"region2\", \"dist\"])\n",
+    "_2 = fast_expected_df.sort_values(by=[\"region1\", \"region2\", \"dist\"])\n",
+    "\n",
+    "balanced_sum_eq = np.allclose(_1[\"balanced.sum\"], _2[\"balanced.sum\"], equal_nan=True)\n",
+    "balanced_avg_eq = np.allclose(_1[\"balanced.avg\"], _2[\"balanced.avg\"], equal_nan=True)\n",
+    "count_sum_eq = np.allclose(_1[\"count.sum\"], _2[\"count.sum\"], equal_nan=True)\n",
+    "n_valid_eq = np.allclose(_1[\"n_valid\"], _2[\"n_valid\"], equal_nan=True)\n",
+    "expected_eq = np.allclose(_1[\"expected\"], _2[\"expected\"], equal_nan=True)\n",
     "\n",
-    "# # ax.set_ylim(0.5*1e-3,1)"
+    "print(f\"comparison tests: {balanced_avg_eq} {balanced_sum_eq} {count_sum_eq} {n_valid_eq} {expected_eq}\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "id": "spare-malaysia",
+   "execution_count": 11,
+   "id": "precise-twins",
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "INFO:root:Done calculating cis expected in 50.654 sec ...\n",
-      "INFO:root:Done calculating trans expected in 26.196 sec ...\n",
-      "INFO:root:Returning combined expected DataFrame.\n"
+      "INFO:root:Calculating observed over expected for pixels [0:52475]\n"
      ]
-    }
-   ],
-   "source": [
-    "# calculate full expected (cis + trans)\n",
-    "expected_df = obs_over_exp_cooler.expected_full(\n",
-    "    clr,\n",
-    "    view_df=hg38_arms,\n",
-    "    smooth_cis=False,\n",
-    "    aggregate_trans=True,\n",
-    "    expected_column_name=\"expected\",\n",
-    "    nproc=4,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "id": "b9c9140f",
-   "metadata": {},
-   "outputs": [
+    },
     {
      "data": {
       "text/html": [
@@ -786,155 +315,60 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>dist</th>\n",
-       "      <th>count.sum</th>\n",
-       "      <th>balanced.sum</th>\n",
+       "      <th>bin1_id</th>\n",
+       "      <th>bin2_id</th>\n",
+       "      <th>oe</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>0</td>\n",
-       "      <td>32061001</td>\n",
-       "      <td>22391.162801</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
+       "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>29927412</td>\n",
-       "      <td>22066.898493</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
+       "      <td>0</td>\n",
        "      <td>2</td>\n",
-       "      <td>8706228</td>\n",
-       "      <td>6529.232708</td>\n",
+       "      <td>1.836246</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
+       "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>3804582</td>\n",
-       "      <td>2843.349631</td>\n",
+       "      <td>1.498967</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>4</td>\n",
-       "      <td>2136953</td>\n",
-       "      <td>1592.015747</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>295212</th>\n",
-       "      <td>242040</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.002267</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>295213</th>\n",
-       "      <td>242053</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.003446</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>295214</th>\n",
-       "      <td>242067</td>\n",
-       "      <td>1</td>\n",
-       "      <td>0.001928</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>295215</th>\n",
-       "      <td>0</td>\n",
-       "      <td>104736</td>\n",
-       "      <td>81.802771</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>295216</th>\n",
        "      <td>0</td>\n",
-       "      <td>304859</td>\n",
-       "      <td>230.234214</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.633761</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>295217 rows × 3 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "          dist  count.sum  balanced.sum\n",
-       "0            0   32061001  22391.162801\n",
-       "1            1   29927412  22066.898493\n",
-       "2            2    8706228   6529.232708\n",
-       "3            3    3804582   2843.349631\n",
-       "4            4    2136953   1592.015747\n",
-       "...        ...        ...           ...\n",
-       "295212  242040          1      0.002267\n",
-       "295213  242053          1      0.003446\n",
-       "295214  242067          1      0.001928\n",
-       "295215       0     104736     81.802771\n",
-       "295216       0     304859    230.234214\n",
-       "\n",
-       "[295217 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 52,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "hui.reset_index(level=[\"r1\",\"r2\"],drop=True).reset_index(level=\"dist\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "cb483c14",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['chr2_p', 'chr2_p', 'chr2_p', ..., 'chr2_q', 'chr17_p', 'chr17_q'],\n",
-       "      dtype=object)"
+       "   bin1_id  bin2_id        oe\n",
+       "0        0        0       NaN\n",
+       "1        0        1       NaN\n",
+       "2        0        2  1.836246\n",
+       "3        0        3  1.498967\n",
+       "4        0        4  1.633761"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "hg38_arms.loc[hui.index.get_level_values(\"r2\"), \"name\"].to_numpy()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "63c9d58c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "zzz=expected_df.set_index([\"r1\",\"r2\"]).rename(columns={\"balanced.avg\":\"exp\"})\n",
-    "f,ax = plt.subplots()\n",
-    "zzz.loc[(0,0),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"00\")\n",
-    "zzz.loc[(0,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"01\")\n",
-    "zzz.loc[(1,1),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"11\")\n",
-    "zzz.loc[(2,2),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"22\")\n",
-    "zzz.loc[(2,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"23\")\n",
-    "zzz.loc[(3,3),[\"dist\",\"exp\"]].plot(x=\"dist\",y=\"exp\", loglog=True,ax=ax, label=\"33\")\n",
-    "ax.set_ylim(0.5*1e-3,1e-1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "precise-twins",
-   "metadata": {},
-   "outputs": [],
    "source": [
     "# collect obs/exp for chunks of pixel table (in memory for 1Mb cooler)\n",
     "results = []\n",
@@ -954,10 +388,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "complete-funeral",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated symmetrix obs/exp matrix of size 327 X 327\n"
+     ]
+    }
+   ],
    "source": [
     "# res_df: sparse matrix -> dense matrix for plotting\n",
     "N = len(clr.bins())\n",
@@ -972,10 +414,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "current-doctor",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar at 0x7f4070aaf640>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x720 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# plot observed and stitched obs/exp side by side\n",
     "istart, iend = 0, 327\n",
@@ -987,7 +452,7 @@
     "    obs,\n",
     "    interpolation=\"none\",\n",
     "    cmap=\"YlOrRd\",\n",
-    "    norm=colors.LogNorm(vmin=0.00005,vmax=0.01)\n",
+    "    norm=colors.LogNorm(vmin=0.00005,vmax=0.02)\n",
     ")\n",
     "plt.colorbar(img,ax=axs[0],orientation=\"horizontal\")\n",
     "img = axs[1].imshow(\n",
@@ -1009,18 +474,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "separated-publication",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# try 10kb ...\n",
-    "clr = cooler.Cooler('./test.mcool::/resolutions/10000')"
+    "# try 100kb ...\n",
+    "clr = cooler.Cooler('./test.mcool::/resolutions/100000')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "therapeutic-semester",
    "metadata": {},
    "outputs": [],
@@ -1034,17 +499,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "sublime-institution",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:root:Done calculating full expected 3.782 sec ...\n"
+     ]
+    }
+   ],
    "source": [
     "# re-calculate full expected (cis + trans) at higher resolution\n",
-    "expected_df = obs_over_exp_cooler.expected_full(\n",
+    "expected_df = obs_over_exp_cooler.expected_full_fast(\n",
     "    clr,\n",
     "    view_df=hg38_arms,\n",
     "    smooth_cis=False,\n",
-    "    aggregate_trans=True,\n",
+    "    aggregate_trans=\"chrom\",\n",
     "    expected_column_name=\"expected\",\n",
     "    nproc=4,\n",
     ")"
@@ -1052,7 +525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "pointed-philosophy",
    "metadata": {},
    "outputs": [],
@@ -1070,10 +543,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "id": "moderate-machinery",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:root:Calculating observed over expected for pixels [0:3329916]\n",
+      "INFO:cooler.create:Writing chunk 0: /data/old_desktop/src/cooltools/cooltools/sandbox/tmpsz6da3sq.multi.cool::0\n",
+      "INFO:cooler.create:Creating cooler at \"/data/old_desktop/src/cooltools/cooltools/sandbox/tmpsz6da3sq.multi.cool::/0\"\n",
+      "INFO:cooler.create:Writing chroms\n",
+      "INFO:cooler.create:Writing bins\n",
+      "/home/sergpolly/miniconda3/envs/devcool/lib/python3.9/site-packages/cooler/core.py:123: FutureWarning: is_categorical is deprecated and will be removed in a future version. Use is_categorical_dtype instead.\n",
+      "  elif is_categorical(data):\n",
+      "INFO:cooler.create:Writing pixels\n",
+      "INFO:cooler.create:Writing indexes\n",
+      "INFO:cooler.create:Writing info\n",
+      "INFO:cooler.create:Merging into fun.cool\n",
+      "INFO:cooler.create:Creating cooler at \"fun.cool::/\"\n",
+      "INFO:cooler.create:Writing chroms\n",
+      "INFO:cooler.create:Writing bins\n",
+      "/home/sergpolly/miniconda3/envs/devcool/lib/python3.9/site-packages/cooler/core.py:123: FutureWarning: is_categorical is deprecated and will be removed in a future version. Use is_categorical_dtype instead.\n",
+      "  elif is_categorical(data):\n",
+      "INFO:cooler.create:Writing pixels\n",
+      "INFO:cooler.reduce:nnzs: [3226216]\n",
+      "INFO:cooler.reduce:current: [3226216]\n",
+      "INFO:cooler.create:Writing indexes\n",
+      "INFO:cooler.create:Writing info\n"
+     ]
+    }
+   ],
    "source": [
     "# write oe_pixels_stream into cooler - with custom column \"oe\" (can do \"count\":float for higlass)\n",
     "cooler.create_cooler(\n",
@@ -1087,13 +588,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "light-sword",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_170082/2539071016.py:17: MatplotlibDeprecationWarning: You are modifying the state of a globally registered colormap. This has been deprecated since 3.3 and in 3.6, you will not be able to modify a registered colormap in-place. To remove this warning, you can make a copy of the colormap first. cmap = mpl.cm.get_cmap(\"coolwarm\").copy()\n",
+      "  cm.set_under(cm(0))\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar at 0x7f4065fa9fd0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1008x720 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# plot observed and stitched obs/exp side by side directly from the new cooler\n",
-    "istart, iend = 23_000, 25_000\n",
+    "istart, iend = 1_500, 3_100\n",
     "obs = clr.matrix()[istart:iend, istart:iend]\n",
     "obs_exp = cooler.Cooler(\"fun.cool\").matrix(field=\"oe\")[istart:iend, istart:iend]\n",
     "\n",
@@ -1102,7 +634,7 @@
     "    obs,\n",
     "    interpolation=\"none\",\n",
     "    cmap=\"YlOrRd\",\n",
-    "    norm=colors.LogNorm(vmin=0.00005,vmax=0.01)\n",
+    "    norm=colors.LogNorm(vmin=0.00001,vmax=0.002)\n",
     ")\n",
     "plt.colorbar(img,ax=axs[0],orientation=\"horizontal\")\n",
     "\n",
@@ -1114,7 +646,7 @@
     "    obs_exp+10**-8,\n",
     "    interpolation=\"none\",\n",
     "    cmap=cm,\n",
-    "    norm=colors.LogNorm(vmin=0.4,vmax=2.5)\n",
+    "    norm=colors.LogNorm(vmin=0.33,vmax=3)\n",
     "    # add color to the \"under\" - to avoid adding \"floor\" to obs_exp\n",
     "    # \n",
     ")\n",

From b058b2516465edc5a207af01d205dd62944d578d Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 21 Sep 2022 20:07:48 -0400
Subject: [PATCH 03/17] fix OE generator after bad conflict resolve

---
 cooltools/sandbox/obs_over_exp_cooler.py | 143 +++++++++++++++++------
 1 file changed, 105 insertions(+), 38 deletions(-)

diff --git a/cooltools/sandbox/obs_over_exp_cooler.py b/cooltools/sandbox/obs_over_exp_cooler.py
index c93a23cf..f773349f 100644
--- a/cooltools/sandbox/obs_over_exp_cooler.py
+++ b/cooltools/sandbox/obs_over_exp_cooler.py
@@ -9,10 +9,12 @@
 expected_full_fast - generated the same output as `expected_full` but ~2x faster.
     Efficiency is achieved through calculating cis and trans expected in one
     pass of the pixel table. Post-processing is not fully implemented yet.
-obs_over_exp_generator - is a function/generator(lazy iterator) that merges
-    pre-calculated full expected with the pixel table in clr and yields chunks
-    of observed/expected pixel table. Such a "stream" can be used in cooler.create
-    as a "pixels" argument to write obs/exp cooler-file.
+obs_over_exp - is a function that merges pre-calculated full expected with the pixel
+    table in pd.DataFrame or dask.DataFrame formats.
+obs_over_exp_generator - is a function/generator(lazy iterator) that wraps
+    `obs_over_exp` function and yields chunks of observed/expected pixel table.
+    Such a "stream" can be used in cooler.create as a "pixels" argument to write
+    obs/exp cooler-file.
 
 It also includes 3 helper functions (used in `expected_full_fast`):
 make_pairwise_expected_table - a function that creates an empty table for the
@@ -653,6 +655,96 @@ def expected_full_fast(
     return result
 
 
+def obs_over_exp(
+    pixels,
+    bins,
+    expected_full,
+    view_column_name="r",
+    expected_column_name="expected",
+    clr_weight_name='weight',
+    oe_column_name="oe",
+):
+    """
+    A function that returns pixel table with observed over expected.
+    It takes a DataFrame of pixels (complete or a chunk, in pandas or dask formats),
+    and merges it with the `expected_full` DataFrame, in order to assign appropriate
+    expected for each pixels. This assignment is done according to the pixels' location,
+    specifically - which combination of regions in the view and genomic distance for
+    cis-pixels.
+    Parameters
+    ----------
+    pixels: pd.DataFrame | dask.DataFrame
+        DataFrame of pixels
+    bins : pd.DataFrame
+        A bin table with a view column annotation.
+    expected_full : pd.DataFrame
+        DataFrame expected for all regions in the view used for annotation of bins.
+    view_column_name : str
+        Name of the column with the view annotations in `bins` and `expected_full`
+    expected_column_name : str
+        Name of the column with the expected values in `expected_full`
+    clr_weight_name : str or None
+        Name of balancing weight column from the cooler to use.
+        Use raw unbalanced data, when None.
+    oe_column_name : str
+        Name of the column to store observed over expected in.
+    Returns
+    -------
+    pixels_oe : pd.DataFrame | dask.DataFrame
+        DataFrame of pixels with observed/expected
+    """
+
+    # use balanced data, when clr_weight is provided - otherwise raw counts
+    if clr_weight_name:
+        observed_column_name = "balanced"
+        weight_col1 = f"{clr_weight_name}1"
+        weight_col2 = f"{clr_weight_name}2"
+    else:
+        observed_column_name = "count"
+
+    # names of the view
+    view_col1 = f"{view_column_name}1"
+    view_col2 = f"{view_column_name}2"
+
+    # labeling with the view-labels view_column_name1/view_column_name2:
+    pixels_oe = cooler.annotate(pixels, bins, replace=False)
+
+    # calculate balanced pixel values and drop NAs for bad bins
+    # as well as pixels_oe not covered by the view (i.e. with view_column annotation as NA)
+    if clr_weight_name:
+        pixels_oe[observed_column_name] = pixels_oe["count"] * pixels_oe[weight_col1] * pixels_oe[weight_col2]
+        pixels_oe = pixels_oe.dropna( subset=[view_col1, view_col1, weight_col1, weight_col2] )
+    else:
+        pixels_oe = pixels_oe.dropna( subset=[view_col1, view_col1] )
+
+    # cast to int, as there are no more NaNs among view_column_name1/view_column_name2
+    pixels_oe = pixels_oe.astype({view_col1 : int, view_col1 : int})
+
+    # trans pixels_oe will have "feature"-dist of 0 (or some other special value)
+    pixels_oe["dist"] = TRANS_DIST_VALUE
+
+    # cis pixels_oe will have "feature"-dist "bind2_id - bin1_id"
+    # dask-compatible notation using `where`, as assign to iloc/loc isn't supported
+    cis_mask = (pixels_oe["chrom1"] == pixels_oe["chrom2"])
+    pixels_oe["dist"] = pixels_oe["dist"].where(
+        ~cis_mask,
+        pixels_oe.loc[cis_mask, "bin2_id"] - pixels_oe.loc[cis_mask, "bin1_id"]
+    )
+
+    # merge pixels_oe with the expected_full - to assign appropriate expected to each pixel
+    # dask-compatible notation instead of pd.merge
+    pixels_oe = pixels_oe.merge(
+        expected_full[[view_col1, view_col2, "dist", expected_column_name]],
+        how="left",
+        on=[view_col1, view_col2, "dist"],
+    )
+
+    # observed over expected = observed / expected
+    pixels_oe[oe_column_name] = pixels_oe[observed_column_name] / pixels_oe[expected_column_name]
+
+    return pixels_oe
+
+
 def obs_over_exp_generator(
     clr,
     expected_full,
@@ -665,7 +757,6 @@ def obs_over_exp_generator(
     """
     Generator yielding chunks of pixels with
     pre-caluclated observed over expected.
-
     Parameters
     ----------
     clr : cooler.Cooler
@@ -683,7 +774,6 @@ def obs_over_exp_generator(
         Use raw unbalanced data, when None.
     chunksize : int, optional
         Size of pixel table chunks to process and output
-
     Yields
     ------
     pixel_df: pd.DataFrame
@@ -704,38 +794,15 @@ def obs_over_exp_generator(
     spans = partition(0, len(clr.pixels()), chunksize)
     for span in spans:
         lo, hi = span
-        pixels = clr.pixels()[lo:hi]
-        # full re-annotation may not be needed - to be optimized
-        # labeling with the regions-labels r1/r2 is happening here:
-        pixels = cooler.annotate(pixels, bins, replace=False)
-
-        logging.info(f"Calculating observed over expected for pixels [{lo}:{hi}]")
-
-        # calculate balanced pixel values
-        if clr_weight_name:
-            pixels[observed_column_name] = pixels["count"] * pixels[weight_col1] * pixels[weight_col2]
-
-        # consider dropping NAs if view_df covers only part of the genome and for "bad" bins
-        if clr_weight_name:
-            pixels = pixels.dropna( subset=["r1", "r2", weight_col1, weight_col2] )
-        else:
-            pixels = pixels.dropna( subset=["r1", "r2"] )
-
-        # cast to int, as there are no more NaNs among r1/r2
-        pixels = pixels.astype({"r1":int, "r2":int})
-
-        # trans pixels will have "feature"-dist of -1
-        pixels["dist"] = TRANS_DIST_VALUE
-        # cis pixels will have "feature"-dist "bind2_id - bin1_id"
-        cis_mask = (pixels["chrom1"] == pixels["chrom2"])
-        pixels.loc[cis_mask,"dist"] = pixels.loc[cis_mask,"bin2_id"] - pixels.loc[cis_mask,"bin1_id"]
-
-        # merge observed (i.e. all_pixels) with the expected
-        pixels = pd.merge(
-            pixels,
-            expected_full[["r1","r2","dist",expected_column_name]],
-            how="left",
-            on=["r1","r2","dist"],
+        # logging.info(f"Calculating observed over expected for pixels [{lo}:{hi}]")
+        oe_chunk = obs_over_exp(
+            clr.pixels()[lo:hi],
+            bins_view,
+            expected_full,
+            view_column_name=view_column_name,
+            expected_column_name=expected_column_name,
+            clr_weight_name=clr_weight_name,
+            oe_column_name=oe_column_name,
         )
 
         # yield pixel-table-like chunks of observed over expected

From 3dab5a5051f24ba7fcc073372319dc8f017ba58b Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 21 Sep 2022 20:12:08 -0400
Subject: [PATCH 04/17] minimize diff

---
 cooltools/sandbox/obs_over_exp_cooler.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/cooltools/sandbox/obs_over_exp_cooler.py b/cooltools/sandbox/obs_over_exp_cooler.py
index f773349f..6caefe24 100644
--- a/cooltools/sandbox/obs_over_exp_cooler.py
+++ b/cooltools/sandbox/obs_over_exp_cooler.py
@@ -52,7 +52,7 @@
 )
 from cooltools.lib.common import (
     assign_supports,
-    make_cooler_view,
+    make_cooler_view
 )
 
 from cooltools.lib import (
@@ -671,6 +671,7 @@ def obs_over_exp(
     expected for each pixels. This assignment is done according to the pixels' location,
     specifically - which combination of regions in the view and genomic distance for
     cis-pixels.
+
     Parameters
     ----------
     pixels: pd.DataFrame | dask.DataFrame
@@ -688,6 +689,7 @@ def obs_over_exp(
         Use raw unbalanced data, when None.
     oe_column_name : str
         Name of the column to store observed over expected in.
+
     Returns
     -------
     pixels_oe : pd.DataFrame | dask.DataFrame
@@ -757,6 +759,7 @@ def obs_over_exp_generator(
     """
     Generator yielding chunks of pixels with
     pre-caluclated observed over expected.
+
     Parameters
     ----------
     clr : cooler.Cooler
@@ -774,6 +777,7 @@ def obs_over_exp_generator(
         Use raw unbalanced data, when None.
     chunksize : int, optional
         Size of pixel table chunks to process and output
+
     Yields
     ------
     pixel_df: pd.DataFrame

From 8878c260ead1dedfac6e1a3bfb9fd4e53df440e9 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 21 Sep 2022 20:17:21 -0400
Subject: [PATCH 05/17] typo fix

---
 cooltools/sandbox/obs_over_exp_cooler.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cooltools/sandbox/obs_over_exp_cooler.py b/cooltools/sandbox/obs_over_exp_cooler.py
index 6caefe24..912a498e 100644
--- a/cooltools/sandbox/obs_over_exp_cooler.py
+++ b/cooltools/sandbox/obs_over_exp_cooler.py
@@ -608,7 +608,7 @@ def expected_full_fast(
         result.loc[_cis_mask, expected_column_name] = result.loc[_cis_mask, _smooth_col_name]
     elif aggregate_cis:
         # aggregate only if requested:
-        _agg_df = results.loc[_cis_mask] \
+        _agg_df = result.loc[_cis_mask] \
             .groupby([*(grp_columns or []), _DIST_NAME])[additive_cols] \
             .transform("sum") \
             .add_suffix(".agg")

From 959d5203c10a6d6026fa1951bf790ca6986d44dc Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Sun, 14 Jan 2024 23:17:07 -0500
Subject: [PATCH 06/17] refactor snipping to enable trans-pileups

---
 cooltools/api/snipping.py | 250 ++++++++++++++++----------------------
 tests/test_snipping.py    |  24 ++--
 2 files changed, 121 insertions(+), 153 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index a03a4133..49f49981 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -111,6 +111,8 @@ def expand_align_features(features_df, flank, resolution, format="bed"):
         ).astype(int)
         features_df["start2"] = features_df["lo2"] * resolution
         features_df["end2"] = features_df["hi2"] * resolution
+    else:
+        raise ValueError(f"feature_type can be 'bed' or 'bedpe', {format} is provided.")
     return features_df
 
 
@@ -185,51 +187,53 @@ def make_bin_aligned_windows(
 
 
 def _extract_stack(data_select, data_snip, arg):
+    # on-diagonal: support is a single region name or ""
     support, feature_group = arg
     # return empty snippets if region is unannotated:
     if len(support) == 0:
-        if "start" in feature_group:  # on-diagonal off-region case:
-            lo = feature_group["lo"].values
-            hi = feature_group["hi"].values
-            s = (hi - lo).astype(int)  # Shape of individual snips
-            assert s.max() == s.min(), "Pileup accepts only windows of the same size"
-            stack = np.full((len(feature_group), s[0], s[0]), np.nan)
-        else:  # off-diagonal off-region case:
-            lo1 = feature_group["lo1"].values
-            hi1 = feature_group["hi1"].values
-            lo2 = feature_group["lo2"].values
-            hi2 = feature_group["hi2"].values
-            s1 = (hi1 - lo1).astype(int)  # Shape of individual snips
-            s2 = (hi2 - lo2).astype(int)
-            assert s1.max() == s1.min(), "Pileup accepts only windows of the same size"
-            assert s2.max() == s2.min(), "Pileup accepts only windows of the same size"
-            stack = np.full((len(feature_group), s1[0], s2[0]), np.nan)
-        return stack, feature_group["_rank"].values
-
-    # check if support region is on- or off-diagonal
-    if len(support) == 2:
-        region1, region2 = support
+        lo = feature_group["lo"].to_numpy()
+        hi = feature_group["hi"].to_numpy()
+        s = (hi - lo).astype(int)  # Shape of individual snips
+        assert s.max() == s.min(), "Pileup accepts only windows of the same size"
+        stack = np.full((len(feature_group), s[0], s[0]), np.nan)
     else:
         region1 = region2 = support
-
-    # check if features are on- or off-diagonal
-    if "start" in feature_group:
-        s1 = feature_group["start"].values
-        e1 = feature_group["end"].values
+        s1 = feature_group["start"].to_numpy()
+        e1 = feature_group["end"].to_numpy()
         s2, e2 = s1, e1
-    else:
-        s1 = feature_group["start1"].values
-        e1 = feature_group["end1"].values
-        s2 = feature_group["start2"].values
-        e2 = feature_group["end2"].values
+        data = data_select(region1, region2)
+        stack = list(map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2)))
+        stack = np.stack(stack)
+    return stack, feature_group["_rank"].to_numpy()
+
 
-    data = data_select(region1, region2)
-    stack = list(map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2)))
-    stack = np.stack(stack)
-    return stack, feature_group["_rank"].values
+def _extract_stack_paired(data_select, data_snip, arg):
+    # off-diagonal case: support is (region1, region2), region1/2 could be ""
+    support, feature_group = arg
+    region1, region2 = support
+    # return empty snippets if region is unannotated:
+    if (len(region1) == 0) or (len(region2) == 0):
+        lo1 = feature_group["lo1"].to_numpy()
+        hi1 = feature_group["hi1"].to_numpy()
+        lo2 = feature_group["lo2"].to_numpy()
+        hi2 = feature_group["hi2"].to_numpy()
+        s1 = (hi1 - lo1).astype(int)  # Shape of individual snips
+        s2 = (hi2 - lo2).astype(int)
+        assert s1.max() == s1.min(), "Pileup accepts only windows of the same size"
+        assert s2.max() == s2.min(), "Pileup accepts only windows of the same size"
+        stack = np.full((len(feature_group), s1[0], s2[0]), np.nan)
+    else:
+        s1 = feature_group["start1"].to_numpy()
+        e1 = feature_group["end1"].to_numpy()
+        s2 = feature_group["start2"].to_numpy()
+        e2 = feature_group["end2"].to_numpy()
+        data = data_select(region1, region2)
+        stack = list(map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2)))
+        stack = np.stack(stack)
+    return stack, feature_group["_rank"].to_numpy()
 
 
-def _pileup(features, data_select, data_snip, map=map):
+def _pileup(features, feature_type, data_select, data_snip, map=map):
     """
     Creates a stackup of snippets (a 3D array) by selecting each region present in the
     `features` (using the `data_select` function) and then extracting all snippets from
@@ -241,11 +245,15 @@ def _pileup(features, data_select, data_snip, map=map):
     Parameters
     ----------
     features : DataFrame
-        Table of features. Requires columns ['chrom', 'start', 'end'].
-        Or ['chrom1', 'start1', 'end1', 'chrom1', 'start2', 'end2'].
+        Table of features. Requires columns ['chrom', 'start', 'end'] for
+        features of type 'bed'. For features of type 'bedpe' - columns
+        ['chrom1', 'start1', 'end1', 'chrom1', 'start2', 'end2'].
         start, end are bp coordinates.
         lo, hi are bin coordinates.
 
+    feature_type: str
+        type of the provided features. Can be 'bed' or 'bedpe'.
+
     data_select : callable
         Callable that takes a region as argument and returns
         the data, mask and bin offset of a support region
@@ -258,26 +266,28 @@ def _pileup(features, data_select, data_snip, map=map):
         Callable that works like builtin `map`.
 
     """
-    if features["region"].isnull().any():
-        warnings.warn(
-            "Some features do not have view regions assigned! Some snips will be empty."
-        )
 
     features = features.copy()
-    features["region"] = features["region"].fillna(
-        ""
-    )  # fill in unanotated view regions with empty string
     features["_rank"] = range(len(features))
+    # based on feature_type define how we will extract stacks for each region-group:
+    # define _extract_group_data function and _feature_groups iterable (region, group_df)
+    # Note that unannotated regions will form a separate group
+    if feature_type == "bed":
+        # fill in unanotated view regions with empty string
+        features["region"] = features["region"].fillna("")
+        _extract_group_data = partial(_extract_stack, data_select, data_snip)
+        _feature_groups = features.groupby("region", sort=False)
+    elif feature_type == "bedpe":
+        # fill in unanotated view regions with empty string
+        features["region1"] = features["region1"].fillna("")
+        features["region2"] = features["region2"].fillna("")
+        _extract_group_data = partial(_extract_stack_paired, data_select, data_snip)
+        _feature_groups = features.groupby(["region1", "region2"], sort=False)
+    else:
+        raise ValueError(f"feature_type can be only bed or bedpe, {feature_type} is provided.")
 
-    # cumul_stack = []
-    # orig_rank = []
-    cumul_stack, orig_rank = zip(
-        *map(
-            partial(_extract_stack, data_select, data_snip),
-            # Note that unannotated regions will form a separate group
-            features.groupby("region", sort=False),
-        )
-    )
+    # perform stack extraction on a per-region basis using _extract_group_data and _feature_groups
+    cumul_stack, orig_rank = zip( *map( _extract_group_data, _feature_groups ) )
     # Restore the original rank of the input features
     cumul_stack = np.concatenate(cumul_stack, axis=0)
     orig_rank = np.concatenate(orig_rank)
@@ -288,42 +298,26 @@ def _pileup(features, data_select, data_snip, map=map):
 
 
 class CoolerSnipper:
-    def __init__(self, clr, cooler_opts=None, view_df=None, min_diag=2):
+    def __init__(self, clr, view_df, cooler_opts=None, min_diag=2):
         """Class for generating snips with "observed" data from a cooler
 
         Parameters
         ----------
         clr : cooler.Cooler
             Cooler object with data to use
+        view_df : pd.DataFrame
+            Genomic view to constrain the analysis
+            E.g. use make_cooler_view(clr) to generate view with
+            all chromosomes present in the cooler
         cooler_opts : dict, optional
             Options to pass to the clr.matrix() method, by default None
             Can be used to choose the cooler weight name, e.g.
             cooler_opts={balance='non-standard-weight'}, or use unbalanced data with
             cooler_opts={balance=False}
-        view_df : pd.DataFrame, optional
-            Genomic view to constrain the analysis, by default None and uses all
-            chromosomes present in the cooler
         min_diag : int, optional
             This number of short-distance diagonals is ignored, by default 2
         """
 
-        # get chromosomes from cooler, if view_df not specified:
-        if view_df is None:
-            view_df = make_cooler_view(clr)
-        else:
-            # Make sure view_df is a proper viewframe
-            try:
-                _ = is_compatible_viewframe(
-                    view_df,
-                    clr,
-                    check_sorting=True,
-                    raise_errors=True,
-                )
-            except Exception as e:
-                raise ValueError(
-                    "view_df is not a valid viewframe or incompatible"
-                ) from e
-
         self.view_df = view_df.set_index("name")
         self.clr = clr
         self.binsize = self.clr.binsize
@@ -468,8 +462,8 @@ def __init__(
         self,
         clr,
         expected,
+        view_df,
         cooler_opts=None,
-        view_df=None,
         min_diag=2,
         expected_value_col="balanced.avg",
     ):
@@ -481,6 +475,10 @@ def __init__(
             Cooler object with data to use
         expected : pd.DataFrame
             Dataframe containing expected interactions in the cooler
+        view_df : pd.DataFrame
+            Genomic view to constrain the analysis
+            E.g. use make_cooler_view(clr) to generate view with
+            all chromosomes present in the cooler
         cooler_opts : dict, optional
             Options to pass to the clr.matrix() method, by default None
             Can be used to choose the cooler weight name, e.g.
@@ -498,37 +496,6 @@ def __init__(
         self.clr = clr
         self.expected = expected
         self.expected_value_col = expected_value_col
-        # get chromosomes from cooler, if view_df not specified:
-        if view_df is None:
-            view_df = make_cooler_view(clr)
-        else:
-            # Make sure view_df is a proper viewframe
-            try:
-                _ = is_compatible_viewframe(
-                    view_df,
-                    clr,
-                    check_sorting=True,
-                    raise_errors=True,
-                )
-            except Exception as e:
-                raise ValueError(
-                    "view_df is not a valid viewframe or incompatible"
-                ) from e
-        # make sure expected is compatible
-        try:
-            _ = is_valid_expected(
-                expected,
-                "cis",
-                view_df,
-                verify_cooler=clr,
-                expected_value_cols=[
-                    self.expected_value_col,
-                ],
-                raise_errors=True,
-            )
-        except Exception as e:
-            raise ValueError("provided expected is not valid") from e
-
         self.view_df = view_df.set_index("name")
         self.binsize = self.clr.binsize
         self.offsets = {}
@@ -699,37 +666,6 @@ def __init__(
         self.clr = clr
         self.expected = expected
         self.expected_value_col = expected_value_col
-        # get chromosomes from cooler, if view_df not specified:
-        if view_df is None:
-            view_df = make_cooler_view(clr)
-        else:
-            # Make sure view_df is a proper viewframe
-            try:
-                _ = is_compatible_viewframe(
-                    view_df,
-                    clr,
-                    check_sorting=True,
-                    raise_errors=True,
-                )
-            except Exception as e:
-                raise ValueError(
-                    "view_df is not a valid viewframe or incompatible"
-                ) from e
-        # make sure expected is compatible
-        try:
-            _ = is_valid_expected(
-                expected,
-                "cis",
-                view_df,
-                verify_cooler=clr,
-                expected_value_cols=[
-                    self.expected_value_col,
-                ],
-                raise_errors=True,
-            )
-        except Exception as e:
-            raise ValueError("provided expected is not valid") from e
-
         self.view_df = view_df.set_index("name")
         self.binsize = self.clr.binsize
         self.offsets = {}
@@ -869,6 +805,7 @@ def pileup(
 
     """
 
+    # deduce feature_type -> bed or bedpe
     if {"chrom", "start", "end"}.issubset(features_df.columns):
         feature_type = "bed"
     elif {"chrom1", "start1", "end1", "chrom2", "start2", "end1"}.issubset(
@@ -878,6 +815,7 @@ def pileup(
     else:
         raise ValueError("Unknown feature_df format")
 
+    # check view_df or generate full chromosome view
     if view_df is None:
         view_df = make_cooler_view(clr)
     else:
@@ -891,7 +829,23 @@ def pileup(
         except Exception as e:
             raise ValueError("view_df is not a valid viewframe or incompatible") from e
 
-    features_df = assign_view_auto(features_df, view_df)
+    # check expected compatibility when provided
+    if expected_df is not None:
+        try:
+            _ = is_valid_expected(
+                expected_df,
+                "cis",
+                view_df,
+                verify_cooler=clr,
+                expected_value_cols=[
+                    expected_value_col,
+                ],
+                raise_errors=True,
+            )
+        except Exception as e:
+            raise ValueError("provided expected is not valid") from e
+
+    features_df = assign_view_auto(features_df, view_df, combined_assignments_column=False)
     # TODO: switch to bioframe.assign_view upon update
 
     if flank is not None:
@@ -930,9 +884,13 @@ def pileup(
     region_offsets = view_df[["chrom", "start", "end"]].apply(clr.offset, axis=1)
     region_offsets_dict = dict(zip(view_df["name"].values, region_offsets))
 
-    features_df["region_offset"] = features_df["region"].replace(region_offsets_dict)
 
     if feature_type == "bed":
+        if features_df["region"].isnull().any():
+            warnings.warn(
+                "Some features do not have view regions assigned! Some snips will be empty."
+            )
+        features_df["region_offset"] = features_df["region"].replace(region_offsets_dict)
         features_df[["lo", "hi"]] = (
             features_df[["lo", "hi"]]
             .subtract(
@@ -942,18 +900,24 @@ def pileup(
             .astype(int)
         )
     else:
+        if features_df["region1"].isnull().any() or features_df["region2"].isnull().any():
+            warnings.warn(
+                "Some features do not have view regions assigned! Some snips will be empty."
+            )
+        features_df["region1_offset"] = features_df["region1"].replace(region_offsets_dict)
         features_df[["lo1", "hi1"]] = (
             features_df[["lo1", "hi1"]]
             .subtract(
-                features_df["region_offset"].fillna(0),
+                features_df["region1_offset"].fillna(0),
                 axis=0,
             )
             .astype(int)
         )
+        features_df["region2_offset"] = features_df["region2"].replace(region_offsets_dict)
         features_df[["lo2", "hi2"]] = (
             features_df[["lo2", "hi2"]]
             .subtract(
-                features_df["region_offset"].fillna(0),
+                features_df["region2_offset"].fillna(0),
                 axis=0,
             )
             .astype(int)
@@ -983,7 +947,7 @@ def pileup(
         mymap = pool.map
     else:
         mymap = map
-    stack = _pileup(features_df, snipper.select, snipper.snip, map=mymap)
+    stack = _pileup(features_df, feature_type, snipper.select, snipper.snip, map=mymap)
     if feature_type == "bed":
         stack = np.fmax(stack, np.transpose(stack, axes=(0, 2, 1)))
 
diff --git a/tests/test_snipping.py b/tests/test_snipping.py
index 4406d8ff..8a551a2e 100644
--- a/tests/test_snipping.py
+++ b/tests/test_snipping.py
@@ -206,6 +206,7 @@ def test_ondiag__pileup_with_expected(request):
     view_df = bioframe.read_table(
         op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
     )
+    feature_type = "bed"
     for snipper_class in (
         cooltools.api.snipping.ObsExpSnipper,
         cooltools.api.snipping.ExpectedSnipper,
@@ -221,7 +222,7 @@ def test_ondiag__pileup_with_expected(request):
             drop=True
         )
         stack = cooltools.api.snipping._pileup(
-            windows, snipper.select, snipper.snip, map=map
+            windows, feature_type, snipper.select, snipper.snip, map=map
         )
 
         # Check that the size of snips is OK and there are two of them:
@@ -237,7 +238,7 @@ def test_ondiag__pileup_with_expected(request):
         )
 
         stack = cooltools.api.snipping._pileup(
-            windows, snipper.select, snipper.snip, map=map
+            windows, feature_type, snipper.select, snipper.snip, map=map
         )
 
         assert stack.shape == (2, 5, 5)
@@ -253,6 +254,7 @@ def test_ondiag__pileup_without_expected(request):
     view_df = bioframe.read_table(
         op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
     )
+    feature_type = "bed"
 
     # I.
     # Example region with windows, two regions from annotated genomic regions:
@@ -265,7 +267,7 @@ def test_ondiag__pileup_without_expected(request):
     )
     snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=None)
     stack = cooltools.api.snipping._pileup(
-        windows, snipper.select, snipper.snip, map=map
+        windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     # Check that the size of snips is OK and there are two of them:
@@ -281,7 +283,7 @@ def test_ondiag__pileup_without_expected(request):
     )
 
     stack = cooltools.api.snipping._pileup(
-        windows, snipper.select, snipper.snip, map=map
+        windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     assert stack.shape == (2, 5, 5)
@@ -299,6 +301,7 @@ def test_offdiag__pileup_with_expected(request):
     view_df = bioframe.read_table(
         op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
     )
+    feature_type = "bedpe"
     for snipper_class in (
         cooltools.api.snipping.ObsExpSnipper,
         cooltools.api.snipping.ExpectedSnipper,
@@ -321,7 +324,7 @@ def test_offdiag__pileup_with_expected(request):
         )
 
         stack = cooltools.api.snipping._pileup(
-            windows, snipper.select, snipper.snip, map=map
+            windows, feature_type, snipper.select, snipper.snip, map=map
         )
 
         # Check that the size of snips is OK and there are two of them:
@@ -343,7 +346,7 @@ def test_offdiag__pileup_with_expected(request):
         )
 
         stack = cooltools.api.snipping._pileup(
-            windows, snipper.select, snipper.snip, map=map
+            windows, feature_type, snipper.select, snipper.snip, map=map
         )
 
         assert stack.shape == (2, 5, 5)
@@ -366,7 +369,7 @@ def test_offdiag__pileup_with_expected(request):
         )
 
         stack = cooltools.api.snipping._pileup(
-            windows, snipper.select, snipper.snip, map=map
+            windows, feature_type, snipper.select, snipper.snip, map=map
         )
 
         assert stack.shape == (2, 5, 5)
@@ -384,6 +387,7 @@ def test_offdiag__pileup_without_expected(request):
     view_df = bioframe.read_table(
         op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
     )
+    feature_type = "bedpe"
 
     # I.
     # Example region with windows, two regions from annotated genomic regions:
@@ -402,7 +406,7 @@ def test_offdiag__pileup_without_expected(request):
 
     snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=None)
     stack = cooltools.api.snipping._pileup(
-        windows, snipper.select, snipper.snip, map=map
+        windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     # Check that the size of snips is OK and there are two of them:
@@ -424,7 +428,7 @@ def test_offdiag__pileup_without_expected(request):
     )
 
     stack = cooltools.api.snipping._pileup(
-        windows, snipper.select, snipper.snip, map=map
+        windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     assert stack.shape == (2, 5, 5)
@@ -449,7 +453,7 @@ def test_offdiag__pileup_without_expected(request):
     )
 
     stack = cooltools.api.snipping._pileup(
-        windows, snipper.select, snipper.snip, map=map
+        windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     assert stack.shape == (2, 5, 5)

From 86c2b0a1f207c43ce68665f319f9d54ccd933ee8 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Mon, 15 Jan 2024 14:24:08 -0500
Subject: [PATCH 07/17] update snipping tests, test values with allclose

---
 cooltools/api/snipping.py |  10 ++-
 requirements-dev.txt      |   1 +
 tests/test_snipping.py    | 127 +++++++++++++++++++++++++++++++++++++-
 3 files changed, 133 insertions(+), 5 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 49f49981..991f93d5 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -294,6 +294,13 @@ def _pileup(features, feature_type, data_select, data_snip, map=map):
 
     idx = np.argsort(orig_rank)
     cumul_stack = cumul_stack[idx, :, :]
+    # snippers return only upper part of the on-diagonal matrix
+    # this is intended behavior for off-diagonal pileups - it masks
+    # lower-symmetrical values for near-diagonal snips - but for
+    # on-diagonal pileups it has to be mitigated to restore symmetry:
+    if feature_type == "bed":
+        cumul_stack = np.fmax(cumul_stack, np.transpose(cumul_stack, axes=(0, 2, 1)))
+
     return cumul_stack
 
 
@@ -947,9 +954,8 @@ def pileup(
         mymap = pool.map
     else:
         mymap = map
+
     stack = _pileup(features_df, feature_type, snipper.select, snipper.snip, map=mymap)
-    if feature_type == "bed":
-        stack = np.fmax(stack, np.transpose(stack, axes=(0, 2, 1)))
 
     if nproc > 1:
         pool.close()
diff --git a/requirements-dev.txt b/requirements-dev.txt
index cd1855a3..06baddb5 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -2,3 +2,4 @@
 pytest
 pytest-flake8
 pytest-cov
+pytest-allclose
diff --git a/tests/test_snipping.py b/tests/test_snipping.py
index 8a551a2e..cedbc0d8 100644
--- a/tests/test_snipping.py
+++ b/tests/test_snipping.py
@@ -8,6 +8,7 @@
 import pytest
 
 from click.testing import CliRunner
+from cooltools.lib import numutils
 from cooltools.cli import cli
 
 
@@ -99,7 +100,7 @@ def test_pileup(request):
     windows = pd.DataFrame(
         {
             "chrom": ["chr1", "chr1"],
-            "start": [83000000, 108_000_000],
+            "start": [83_000_000, 108_000_000],
             "end": [88_000_000, 113_000_000],
         }
     )
@@ -259,9 +260,8 @@ def test_ondiag__pileup_without_expected(request):
     # I.
     # Example region with windows, two regions from annotated genomic regions:
     windows = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [120_000_000, 160_000_000], flank_bp=2_000_000
+        1_000_000, ["chr1", "chr1"], [120_000_000, 140_000_000], flank_bp=2_000_000
     )
-
     windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
         drop=True
     )
@@ -291,6 +291,46 @@ def test_ondiag__pileup_without_expected(request):
     assert np.all(np.isnan(stack[1]))
 
 
+def test_ondiag__pileup_without_expected_with_result_validation(request, allclose):
+    """
+    Test the snipping on matrix:
+    """
+    # Read cool file and create view_df out of it:
+    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
+    view_df = bioframe.read_table(
+        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
+    )
+    feature_type = "bed"
+    min_diag = 1
+
+    # Example region with windows, two regions from annotated genomic regions:
+    windows = cooltools.api.snipping.make_bin_aligned_windows(
+        1_000_000, ["chr1", "chr1"], [110_000_000, 140_000_000], flank_bp=2_000_000
+    )
+    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        drop=True
+    )
+
+    # generate reference stack using naive cooler.matrix.fetch extraction:
+    ref_stack = []
+    for _win in windows[["chrom","start","end"]].itertuples(index=False):
+        _mat = clr.matrix().fetch(_win)
+        # fill min_diag diagonals with NaNs
+        for d in range(-min_diag + 1, min_diag):
+            _mat = numutils.set_diag(_mat, np.nan, d)
+        ref_stack.append(_mat)
+    ref_stack = np.asarray(ref_stack)
+
+    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    stack = cooltools.api.snipping._pileup(
+        windows, feature_type, snipper.select, snipper.snip, map=map
+    )
+
+    # Check that the size of snips is OK and there are two of them:
+    assert stack.shape == (len(windows), 5, 5)
+    assert allclose(stack, ref_stack, equal_nan=True)
+
+
 def test_offdiag__pileup_with_expected(request):
     """
     Test the snipping on matrix:
@@ -377,6 +417,87 @@ def test_offdiag__pileup_with_expected(request):
             [np.all(np.isnan(snip[np.tril_indices_from(snip, 1)])) for snip in stack]
         )
 
+def test_offdiag__pileup_without_expected_with_result_validation(request, allclose):
+    """
+    Test the snipping on matrix:
+    """
+    # Read cool file and create view_df out of it:
+    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
+    view_df = bioframe.read_table(
+        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
+    )
+    feature_type = "bedpe"
+    min_diag = 2
+
+    # I.
+    # Example region with windows, two regions from annotated genomic regions:
+    windows1 = cooltools.api.snipping.make_bin_aligned_windows(
+        1_000_000, ["chr1", "chr1"], [102_000_000, 115_000_000], flank_bp=2_000_000
+    )
+    windows2 = cooltools.api.snipping.make_bin_aligned_windows(
+        1_000_000, ["chr1", "chr1"], [115_000_000, 140_000_000], flank_bp=2_000_000
+    )
+    windows = pd.merge(
+        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
+    )
+    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        drop=True
+    )
+
+    # generate reference stack using naive cooler.matrix.fetch extraction:
+    ref_stack = []
+    for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
+        _reg1 = _win[:3]
+        _reg2 = _win[3:]
+        _mat = clr.matrix().fetch(_reg1, _reg2)
+        # assuming regions are away from the diagonal - no set_diag needed
+        ref_stack.append(_mat)
+    ref_stack = np.asarray(ref_stack)
+
+    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    stack = cooltools.api.snipping._pileup(
+        windows, feature_type, snipper.select, snipper.snip, map=map
+    )
+
+    # Check that the size of snips is OK, there are two of them and their value are OK:
+    assert stack.shape == (len(windows), 5, 5)
+    assert allclose(stack, ref_stack, equal_nan = True)
+
+    # II.
+    # Example trans features
+    min_diag = None
+    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    windows1 = cooltools.api.snipping.make_bin_aligned_windows(
+        1_000_000, ["chr1", "chr1"], [102_000_000, 120_000_000], flank_bp=2_000_000
+    )
+    windows2 = cooltools.api.snipping.make_bin_aligned_windows(
+        1_000_000, ["chr2", "chr2"], [102_000_000, 130_000_000], flank_bp=2_000_000
+    )
+    windows = pd.merge(
+        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
+    )
+    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        drop=True
+    )
+
+    # generate reference stack using naive cooler.matrix.fetch extraction:
+    ref_stack = []
+    for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
+        _reg1 = _win[:3]
+        _reg2 = _win[3:]
+        _mat = clr.matrix().fetch(_reg1, _reg2)
+        ref_stack.append(_mat)
+    ref_stack = np.asarray(ref_stack)
+
+    stack = cooltools.api.snipping._pileup(
+        windows, feature_type, snipper.select, snipper.snip, map=map
+    )
+
+    # check shape and values
+    assert stack.shape == (len(windows), 5, 5)
+    assert allclose(stack, ref_stack, equal_nan = True)
+
+
 
 def test_offdiag__pileup_without_expected(request):
     """

From ee7937c41c8f311353d297141159762cc7065c6e Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Mon, 15 Jan 2024 15:33:21 -0500
Subject: [PATCH 08/17] add resuable fixture to snip-test, typo fix

---
 cooltools/api/snipping.py |  13 ++--
 tests/test_snipping.py    | 140 +++++++++++++++-----------------------
 2 files changed, 60 insertions(+), 93 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 991f93d5..3518aad0 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -486,14 +486,12 @@ def __init__(
             Genomic view to constrain the analysis
             E.g. use make_cooler_view(clr) to generate view with
             all chromosomes present in the cooler
+            all chromosomes present in the cooler
         cooler_opts : dict, optional
             Options to pass to the clr.matrix() method, by default None
             Can be used to choose the cooler weight name, e.g.
             cooler_opts={balance='non-standard-weight'}, or use unbalanced data with
             cooler_opts={balance=False}
-        view_df : pd.DataFrame, optional
-            Genomic view to constrain the analysis, by default None and uses all
-            chromosomes present in the cooler
         min_diag : int, optional
             This number of short-distance diagonals is ignored, by default 2
         expected_value_col : str, optional
@@ -651,7 +649,7 @@ def snip(self, matrix, region1, region2, tup):
 
 class ExpectedSnipper:
     def __init__(
-        self, clr, expected, view_df=None, min_diag=2, expected_value_col="balanced.avg"
+        self, clr, expected, view_df, min_diag=2, expected_value_col="balanced.avg"
     ):
         """Class for generating expected snips
 
@@ -661,9 +659,10 @@ def __init__(
             Cooler object to which the data corresponds
         expected : pd.DataFrame
             Dataframe containing expected interactions in the cooler
-        view_df : pd.DataFrame, optional
-            Genomic view to constrain the analysis, by default None and uses all
-            chromosomes present in the cooler
+        view_df : pd.DataFrame
+            Genomic view to constrain the analysis
+            E.g. use make_cooler_view(clr) to generate view with
+            all chromosomes present in the cooler
         min_diag : int, optional
             This number of short-distance diagonals is ignored, by default 2
         expected_value_col : str, optional
diff --git a/tests/test_snipping.py b/tests/test_snipping.py
index cedbc0d8..e33bce65 100644
--- a/tests/test_snipping.py
+++ b/tests/test_snipping.py
@@ -86,14 +86,23 @@ def test_pileup_cli_hdf5(request, tmpdir):
     )
     assert result.exit_code == 0
 
-
-def test_pileup(request):
-    # Read cool file and create view_df out of it:
+# define fixture with clr, exp and view_df to be reused across many tests
+# fixture return a dict and values can be accessed e.g. as data["clr"]
+@pytest.fixture
+def data(request):
     clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
     exp = pd.read_table(op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"))
     view_df = bioframe.read_table(
         op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
     )
+    return {
+        "clr": clr,
+        "exp": exp,
+        "view": view_df,
+    }
+
+
+def test_pileup(request, data):
 
     # I.
     # Example on-diagonal features, two regions from annotated genomic regions:
@@ -105,7 +114,7 @@ def test_pileup(request):
         }
     )
 
-    stack = cooltools.api.snipping.pileup(clr, windows, view_df=None, flank=None)
+    stack = cooltools.api.snipping.pileup(data["clr"], windows, view_df=None, flank=None)
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
     # Check that NaNs were propagated
@@ -113,7 +122,7 @@ def test_pileup(request):
     assert not np.all(np.isnan(stack))
 
     stack = cooltools.api.snipping.pileup(
-        clr, windows, view_df=view_df, expected_df=exp, flank=None
+        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
     )
     # Check that the size of snips is OK and there are two of them.
     # Now with view and expected:
@@ -132,7 +141,7 @@ def test_pileup(request):
         }
     )
     stack = cooltools.api.snipping.pileup(
-        clr, windows, view_df=view_df, expected_df=exp, flank=None
+        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
     )
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
@@ -150,7 +159,7 @@ def test_pileup(request):
         }
     )
     stack = cooltools.api.snipping.pileup(
-        clr, windows, view_df=view_df, expected_df=exp, flank=None
+        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
     )
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
@@ -167,10 +176,10 @@ def test_pileup(request):
         }
     )
     with pytest.raises(ValueError):
-        stack = cooltools.api.snipping.pileup(clr, windows, view_df, exp, flank=None)
+        stack = cooltools.api.snipping.pileup(data["clr"], windows, data["view"], data["exp"], flank=None)
 
     # DRAFT # Should work with force=True:
-    # stack = cooltools.api.snipping.pileup(clr, windows, view_df, exp, flank=None, force=True)
+    # stack = cooltools.api.snipping.pileup(data["clr"], windows, view_df, data["exp"], flank=None, force=True)
     # # Check that the size of snips is OK and there are two of them:
     # assert stack.shape == (2, 5, 5,)
 
@@ -188,38 +197,32 @@ def test_pileup(request):
     )
     with pytest.raises(ValueError):
         stack = cooltools.api.snipping.pileup(
-            clr, windows, view_df=view_df, expected_df=exp, flank=None
+            data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
         )
 
     # DRAFT # Should work with force=True:
-    # stack = cooltools.api.snipping.pileup(clr, windows, view_df, exp, flank=0, force=True)
+    # stack = cooltools.api.snipping.pileup(data["clr"], windows, data["view"], data["exp"], flank=0, force=True)
     # # Check that the size of snips is OK and there are two of them:
     # assert stack.shape == (2, 5, 5,)
 
 
-def test_ondiag__pileup_with_expected(request):
+def test_ondiag__pileup_with_expected(request, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    exp = pd.read_table(op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bed"
     for snipper_class in (
         cooltools.api.snipping.ObsExpSnipper,
         cooltools.api.snipping.ExpectedSnipper,
     ):
-        snipper = snipper_class(clr, exp, view_df=view_df)
+        snipper = snipper_class(data["clr"], data["exp"], data["view"])
 
         # I.
         # Example region with windows, two regions from annotated genomic regions:
         windows = cooltools.api.snipping.make_bin_aligned_windows(
             1_000_000, ["chr1", "chr1"], [102_000_000, 105_000_000], flank_bp=2_000_000
         )
-        windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
             drop=True
         )
         stack = cooltools.api.snipping._pileup(
@@ -234,7 +237,7 @@ def test_ondiag__pileup_with_expected(request):
         windows = cooltools.api.snipping.make_bin_aligned_windows(
             1_000_000, ["chr1", "chr1"], [120_000_000, 160_000_000], flank_bp=2_000_000
         )
-        windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
             drop=True
         )
 
@@ -246,15 +249,10 @@ def test_ondiag__pileup_with_expected(request):
         assert np.all(np.isnan(stack[1]))
 
 
-def test_ondiag__pileup_without_expected(request):
+def test_ondiag__pileup_without_expected(request, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bed"
 
     # I.
@@ -262,10 +260,10 @@ def test_ondiag__pileup_without_expected(request):
     windows = cooltools.api.snipping.make_bin_aligned_windows(
         1_000_000, ["chr1", "chr1"], [120_000_000, 140_000_000], flank_bp=2_000_000
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=None)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=None)
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -278,7 +276,7 @@ def test_ondiag__pileup_without_expected(request):
     windows = cooltools.api.snipping.make_bin_aligned_windows(
         1_000_000, ["chr1", "chr1"], [120_000_000, 160_000_000], flank_bp=2_000_000
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
@@ -291,15 +289,10 @@ def test_ondiag__pileup_without_expected(request):
     assert np.all(np.isnan(stack[1]))
 
 
-def test_ondiag__pileup_without_expected_with_result_validation(request, allclose):
+def test_ondiag__pileup_without_expected_with_result_validation(request, allclose, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bed"
     min_diag = 1
 
@@ -307,21 +300,21 @@ def test_ondiag__pileup_without_expected_with_result_validation(request, allclos
     windows = cooltools.api.snipping.make_bin_aligned_windows(
         1_000_000, ["chr1", "chr1"], [110_000_000, 140_000_000], flank_bp=2_000_000
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
     # generate reference stack using naive cooler.matrix.fetch extraction:
     ref_stack = []
     for _win in windows[["chrom","start","end"]].itertuples(index=False):
-        _mat = clr.matrix().fetch(_win)
+        _mat = data["clr"].matrix().fetch(_win)
         # fill min_diag diagonals with NaNs
         for d in range(-min_diag + 1, min_diag):
             _mat = numutils.set_diag(_mat, np.nan, d)
         ref_stack.append(_mat)
     ref_stack = np.asarray(ref_stack)
 
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -331,22 +324,16 @@ def test_ondiag__pileup_without_expected_with_result_validation(request, allclos
     assert allclose(stack, ref_stack, equal_nan=True)
 
 
-def test_offdiag__pileup_with_expected(request):
+def test_offdiag__pileup_with_expected(request, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    exp = pd.read_table(op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bedpe"
     for snipper_class in (
         cooltools.api.snipping.ObsExpSnipper,
         cooltools.api.snipping.ExpectedSnipper,
     ):
-        snipper = snipper_class(clr, exp, view_df=view_df)
+        snipper = snipper_class(data["clr"], data["exp"], data["view"])
 
         # I.
         # Example region with windows, two off-diagonal features from annotated genomic regions:
@@ -359,7 +346,7 @@ def test_offdiag__pileup_with_expected(request):
         windows = pd.merge(
             windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
         )
-        windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
             drop=True
         )
 
@@ -381,7 +368,7 @@ def test_offdiag__pileup_with_expected(request):
         windows = pd.merge(
             windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
         )
-        windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
             drop=True
         )
 
@@ -404,7 +391,7 @@ def test_offdiag__pileup_with_expected(request):
         windows = pd.merge(
             windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
         )
-        windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
             drop=True
         )
 
@@ -417,15 +404,10 @@ def test_offdiag__pileup_with_expected(request):
             [np.all(np.isnan(snip[np.tril_indices_from(snip, 1)])) for snip in stack]
         )
 
-def test_offdiag__pileup_without_expected_with_result_validation(request, allclose):
+def test_offdiag__pileup_without_expected_with_result_validation(request, allclose, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bedpe"
     min_diag = 2
 
@@ -440,7 +422,7 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     windows = pd.merge(
         windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
@@ -449,12 +431,12 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
         _reg1 = _win[:3]
         _reg2 = _win[3:]
-        _mat = clr.matrix().fetch(_reg1, _reg2)
+        _mat = data["clr"].matrix().fetch(_reg1, _reg2)
         # assuming regions are away from the diagonal - no set_diag needed
         ref_stack.append(_mat)
     ref_stack = np.asarray(ref_stack)
 
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -466,7 +448,7 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     # II.
     # Example trans features
     min_diag = None
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
         1_000_000, ["chr1", "chr1"], [102_000_000, 120_000_000], flank_bp=2_000_000
     )
@@ -476,7 +458,7 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     windows = pd.merge(
         windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
@@ -485,7 +467,7 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
         _reg1 = _win[:3]
         _reg2 = _win[3:]
-        _mat = clr.matrix().fetch(_reg1, _reg2)
+        _mat = data["clr"].matrix().fetch(_reg1, _reg2)
         ref_stack.append(_mat)
     ref_stack = np.asarray(ref_stack)
 
@@ -499,15 +481,10 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
 
 
 
-def test_offdiag__pileup_without_expected(request):
+def test_offdiag__pileup_without_expected(request, data):
     """
     Test the snipping on matrix:
     """
-    # Read cool file and create view_df out of it:
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
     feature_type = "bedpe"
 
     # I.
@@ -521,11 +498,11 @@ def test_offdiag__pileup_without_expected(request):
     windows = pd.merge(
         windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=None)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=None)
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -544,7 +521,7 @@ def test_offdiag__pileup_without_expected(request):
     windows = pd.merge(
         windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
@@ -559,7 +536,7 @@ def test_offdiag__pileup_without_expected(request):
     # III.
     # Example region with windows on diagonal, treated as off-diagonal. Check bottom
     # triangle is all NaN
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df, min_diag=2)
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=2)
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
         1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
     )
@@ -569,7 +546,7 @@ def test_offdiag__pileup_without_expected(request):
     windows = pd.merge(
         windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, view_df).reset_index(
+    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
         drop=True
     )
 
@@ -583,17 +560,12 @@ def test_offdiag__pileup_without_expected(request):
     )
 
 
-def test_snipper_with_view_and_expected(request):
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    exp = pd.read_table(op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
+def test_snipper_with_view_and_expected(request, data):
     for snipper_class in (
         cooltools.api.snipping.ObsExpSnipper,
         cooltools.api.snipping.ExpectedSnipper,
     ):
-        snipper = snipper_class(clr, exp, view_df=view_df)
+        snipper = snipper_class(data["clr"], data["exp"], data["view"])
         matrix = snipper.select("foo", "foo")
         snippet = snipper.snip(
             matrix, "foo", "foo", (110_000_000, 120_000_000, 110_000_000, 120_000_000)
@@ -601,12 +573,8 @@ def test_snipper_with_view_and_expected(request):
         assert snippet.shape is not None
 
 
-def test_cooler_snipper_with_view(request):
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
-    )
-    snipper = cooltools.api.snipping.CoolerSnipper(clr, view_df=view_df)
+def test_cooler_snipper_with_view(request, data):
+    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"])
     matrix = snipper.select("foo", "foo")
     snippet = snipper.snip(
         matrix, "foo", "foo", (110_000_000, 120_000_000, 110_000_000, 120_000_000)

From 9dd14df66d36829376b8724c11e3d1cf7224610d Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Tue, 16 Jan 2024 12:15:49 -0500
Subject: [PATCH 09/17] let go of pandas<2 requirement

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index be1624b0..5891c6c2 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,7 +7,7 @@ matplotlib
 multiprocess
 numba
 numpy
-pandas>=1.5.1,<2
+pandas>=1.5.1
 scikit-learn>=1.1.2
 scipy
 scikit-image

From 1c1d9174ccb846330462def38cffae53cb791d21 Mon Sep 17 00:00:00 2001
From: Sergey Venev <sergpolly@gmail.com>
Date: Tue, 16 Jan 2024 15:07:12 -0500
Subject: [PATCH 10/17] enforce multiprocess-dill (#478)

---
 cooltools/api/snipping.py | 4 ++--
 cooltools/cli/coverage.py | 2 +-
 cooltools/lib/common.py   | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 3518aad0..46796fac 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -48,7 +48,7 @@
 from ..lib.numutils import LazyToeplitz
 import warnings
 
-import multiprocessing
+from multiprocess import Pool
 
 
 def expand_align_features(features_df, flank, resolution, format="bed"):
@@ -949,7 +949,7 @@ def pileup(
         )
 
     if nproc > 1:
-        pool = multiprocessing.Pool(nproc)
+        pool = Pool(nproc)
         mymap = pool.map
     else:
         mymap = map
diff --git a/cooltools/cli/coverage.py b/cooltools/cli/coverage.py
index 98d82fdb..839d7865 100644
--- a/cooltools/cli/coverage.py
+++ b/cooltools/cli/coverage.py
@@ -6,7 +6,7 @@
 from . import cli
 from .. import api
 import bioframe
-import multiprocessing as mp
+import multiprocess as mp
 
 
 @cli.command()
diff --git a/cooltools/lib/common.py b/cooltools/lib/common.py
index 7946ef4f..7916a746 100644
--- a/cooltools/lib/common.py
+++ b/cooltools/lib/common.py
@@ -8,7 +8,7 @@
 
 import bioframe
 
-from multiprocessing import Pool
+from multiprocess import Pool
 
 
 def assign_view_paired(

From ba58e96c3717512af2570259a7c1f3a8f9e99e65 Mon Sep 17 00:00:00 2001
From: Sergey Venev <sergpolly@gmail.com>
Date: Wed, 17 Jan 2024 10:27:41 -0500
Subject: [PATCH 11/17] pandas>2 groupby observed behavior in expected (#480)

---
 cooltools/api/expected.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cooltools/api/expected.py b/cooltools/api/expected.py
index 40273f22..b9ae9985 100644
--- a/cooltools/api/expected.py
+++ b/cooltools/api/expected.py
@@ -319,12 +319,12 @@ def make_diag_tables(clr, regions, regions2=None, clr_weight_name="weight"):
     bins = clr.bins()[:]
     if clr_weight_name is None:
         # ignore bad bins
-        sizes = dict(bins.groupby("chrom").size())
+        sizes = dict(bins.groupby("chrom", observed=True).size())
         bad_bin_dict = {
             chrom: np.zeros(sizes[chrom], dtype=bool) for chrom in sizes.keys()
         }
     elif is_cooler_balanced(clr, clr_weight_name):
-        groups = dict(iter(bins.groupby("chrom")[clr_weight_name]))
+        groups = dict(iter(bins.groupby("chrom", observed=True)[clr_weight_name]))
         bad_bin_dict = {
             chrom: np.array(groups[chrom].isnull()) for chrom in groups.keys()
         }

From 598e126c66f21e6ca082522e85069b6f7563b2ca Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Wed, 17 Jan 2024 11:49:49 -0500
Subject: [PATCH 12/17] obey new pandas indexing reqs - switch to python-tuples

---
 cooltools/api/snipping.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 3518aad0..38c67f77 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -366,8 +366,8 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )
@@ -540,10 +540,10 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        if not region1 == region2:
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
+        if region1_coords[0] != region2_coords[0]:
             raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )
@@ -697,10 +697,10 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        if not region1 == region2:
-            raise ValueError("ExpectedSnipper is implemented for cis contacts only.")
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
+        if region1_coords[0] != region2_coords[0]:
+            raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )

From 0c797569c09d77694fd3b9208810d241c9bd1c97 Mon Sep 17 00:00:00 2001
From: Sergey Venev <sergpolly@gmail.com>
Date: Wed, 17 Jan 2024 11:51:14 -0500
Subject: [PATCH 13/17] obey new pandas indexing reqs - switch to python-tuples
 (#481)

---
 cooltools/api/snipping.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 46796fac..9cc005d2 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -366,8 +366,8 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )
@@ -540,10 +540,10 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        if not region1 == region2:
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
+        if region1_coords[0] != region2_coords[0]:
             raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )
@@ -697,10 +697,10 @@ def select(self, region1, region2):
         CSR matrix
             Sparse matrix of the selected portion of the data from the cooler
         """
-        if not region1 == region2:
-            raise ValueError("ExpectedSnipper is implemented for cis contacts only.")
-        region1_coords = self.view_df.loc[region1]
-        region2_coords = self.view_df.loc[region2]
+        region1_coords = tuple(self.view_df.loc[region1])
+        region2_coords = tuple(self.view_df.loc[region2])
+        if region1_coords[0] != region2_coords[0]:
+            raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
         self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
             region1_coords[0]
         )

From d4d10e33bf7014ad749a9fe013a3d1d55e3f2c2f Mon Sep 17 00:00:00 2001
From: Sergey Venev <sergpolly@gmail.com>
Date: Fri, 19 Jan 2024 17:16:08 -0500
Subject: [PATCH 14/17] add saddle_stack by dist, deprecate plotting (#483)

---
 cooltools/api/saddle.py           | 546 +++++++++++++++++-------------
 cooltools/cli/saddle.py           |  85 -----
 tests/test_compartments_saddle.py |   8 -
 3 files changed, 312 insertions(+), 327 deletions(-)

diff --git a/cooltools/api/saddle.py b/cooltools/api/saddle.py
index 1c9499e1..9c42fac7 100644
--- a/cooltools/api/saddle.py
+++ b/cooltools/api/saddle.py
@@ -182,40 +182,65 @@ def _fetch_trans_oe(reg1, reg2):
         raise ValueError("Unknown type of expected")
 
 
-def _accumulate(
-    S, C, getmatrix, digitized, reg1, reg2, min_diag=3, max_diag=-1, verbose=False
+def _accumulate_trans(
+    S, C, getmatrix, digitized, reg1, reg2, max_dist=1, verbose=False
 ):
     """
-    Helper function to aggregate across region pairs.
-    If regions are identical, also masks returned matrices below min_diag and above max_diag.
-
-    Used in `get_saddle()`.
+    Helper function to aggregate across region pairs for trans-data
+    S and C - are 3D
     """
 
-    n_bins = S.shape[0]
+    n_bins = S.shape[-1]
     matrix = getmatrix(reg1, reg2)
 
-    if reg1 == reg2:
-        for d in np.arange(-min_diag + 1, min_diag):
-            numutils.set_diag(matrix, np.nan, d)
-        if max_diag >= 0:
-            for d in np.append(
-                np.arange(-matrix.shape[0], -max_diag),
-                np.arange(max_diag + 1, matrix.shape[0]),
-            ):
-                numutils.set_diag(matrix, np.nan, d)
+    if verbose:
+        print("regions {} vs {}".format(reg1, reg2))
+
+    for i in range(n_bins):
+        row_mask = digitized[reg1] == i
+        for j in range(n_bins):
+            col_mask = digitized[reg2] == j
+            data = matrix[row_mask, :][:, col_mask]
+            is_finite_mask = np.isfinite(data)
+            data = data[is_finite_mask]
+            S[max_dist-1, i, j] += np.sum(data)
+            C[max_dist-1, i, j] += float(len(data))
+
+
+def _accumulate_cis(
+    S, C, getmatrix, digitized, reg1, reg2, max_dist, verbose=False
+):
+    """
+    Helper function to aggregate across region pairs for cis-data.
+    Do it separately for every diagonal.
+    """
+
+    if reg1 != reg2:
+        raise ValueError("this is special version of accumulate for cis data only ...")
+
+    n_bins = S.shape[-1]
+    matrix = getmatrix(reg1, reg2)
 
     if verbose:
         print("regions {} vs {}".format(reg1, reg2))
 
+    # Toeplitz matrix with distance for every pixel ...
+    _dist_vec = np.arange(matrix.shape[0])
+    dist_mat = np.abs(_dist_vec[None,:] - _dist_vec[:,None])
+
     for i in range(n_bins):
         row_mask = digitized[reg1] == i
         for j in range(n_bins):
             col_mask = digitized[reg2] == j
             data = matrix[row_mask, :][:, col_mask]
-            data = data[np.isfinite(data)]
-            S[i, j] += np.sum(data)
-            C[i, j] += float(len(data))
+            dist = dist_mat[row_mask, :][:, col_mask]
+            is_finite_mask = np.isfinite(data)
+            data = data[is_finite_mask]
+            dist = dist[is_finite_mask]
+            # S unrolled by distances - inefficient memory access - isn't it ?
+            S[:, i, j] += np.bincount(dist, weights=data, minlength=max_dist)
+            # C unrolled by distances
+            C[:, i, j] += np.bincount(dist, minlength=max_dist).astype(float)
 
 
 def _make_binedges(track_values, n_bins, vrange=None, qrange=None):
@@ -503,9 +528,12 @@ def saddle(
 
     # set "cis" or "trans" for supports (regions to iterate over) and matrix fetcher
     if contact_type == "cis":
+        # precalculate max_dist using provided expected:
+        max_dist = expected["dist"].max() + 1
+        # redefine max_diag if it is -1:
+        max_diag = None if max_diag < 0 else max_diag
         # only symmetric intra-chromosomal regions :
         supports = list(zip(view_df[view_name_col], view_df[view_name_col]))
-
         getmatrix = _make_cis_obsexp_fetcher(
             clr,
             expected,
@@ -514,18 +542,41 @@ def saddle(
             expected_value_col=expected_value_col,
             clr_weight_name=clr_weight_name,
         )
+        # n_bins here includes 2 open bins for values <lo and >hi.
+        interaction_sum = np.zeros((max_dist, n_bins + 2, n_bins + 2))
+        interaction_count = np.zeros((max_dist, n_bins + 2, n_bins + 2))
+        for reg1, reg2 in supports:
+            _accumulate_cis(
+                interaction_sum,
+                interaction_count,
+                getmatrix,
+                digitized_tracks,
+                reg1,
+                reg2,
+                max_dist,
+                verbose=verbose
+            )
+        # symmetrise by adding transpose "saddle"
+        # transpose 2nd and 3rd coords by leaving the 1st alone
+        interaction_sum += interaction_sum.transpose(0,2,1)
+        interaction_count += interaction_count.transpose(0,2,1)
+        if trim_outliers:
+            interaction_sum = interaction_sum[:, 1:-1, 1:-1]
+            interaction_count = interaction_count[:, 1:-1, 1:-1]
+        # in order to stay compatible - return aggregated sums and counts for now:
+        return (
+            np.nansum(interaction_sum[min_diag:max_diag], axis=0),
+            np.nansum(interaction_count[min_diag:max_diag], axis=0)
+        )
     elif contact_type == "trans":
+        # precalculate max_dist using provided expected:
+        max_dist = 1
         # asymmetric inter-chromosomal regions :
-        supports = list(combinations(view_df[view_name_col], 2))
-        supports = [
-            i
-            for i in supports
-            if (
-                view_df["chrom"].loc[view_df[view_name_col] == i[0]].values
-                != view_df["chrom"].loc[view_df[view_name_col] == i[1]].values
-            )
-        ]
-
+        view_df_index = view_df.set_index(view_name_col)
+        supports = []
+        for i1, i2 in combinations(view_df[view_name_col], 2):
+            if view_df_index.at[i1, "chrom"] != view_df_index.at[i2, "chrom"]:
+                supports.append((i1, i2))
         getmatrix = _make_trans_obsexp_fetcher(
             clr,
             expected,
@@ -534,235 +585,262 @@ def saddle(
             expected_value_col=expected_value_col,
             clr_weight_name=clr_weight_name,
         )
+        # n_bins here includes 2 open bins for values <lo and >hi.
+        interaction_sum = np.zeros((max_dist, n_bins + 2, n_bins + 2))
+        interaction_count = np.zeros((max_dist, n_bins + 2, n_bins + 2))
+        for reg1, reg2 in supports:
+            _accumulate_trans(
+                interaction_sum,
+                interaction_count,
+                getmatrix,
+                digitized_tracks,
+                reg1,
+                reg2,
+                max_dist,
+                verbose=verbose,
+            )
+        # symmetrise by adding transpose "saddle"
+        # transpose 2nd and 3rd coords by leaving the 1st alone
+        interaction_sum += interaction_sum.transpose(0,2,1)
+        interaction_count += interaction_count.transpose(0,2,1)
+        if trim_outliers:
+            interaction_sum = interaction_sum[:, 1:-1, 1:-1]
+            interaction_count = interaction_count[:, 1:-1, 1:-1]
+        # in order to stay compatible - return aggregated sums and counts for now:
+        return (
+            np.nansum(interaction_sum, axis=0),
+            np.nansum(interaction_count, axis=0)
+        )
     else:
         raise ValueError("Allowed values for contact_type are 'cis' or 'trans'.")
 
-    # n_bins here includes 2 open bins for values <lo and >hi.
-    interaction_sum = np.zeros((n_bins + 2, n_bins + 2))
-    interaction_count = np.zeros((n_bins + 2, n_bins + 2))
-
-    for reg1, reg2 in supports:
-        _accumulate(
-            interaction_sum,
-            interaction_count,
-            getmatrix,
-            digitized_tracks,
-            reg1,
-            reg2,
-            min_diag=min_diag,
-            max_diag=max_diag,
-            verbose=verbose,
-        )
-
-    interaction_sum += interaction_sum.T
-    interaction_count += interaction_count.T
-
-    if trim_outliers:
-        interaction_sum = interaction_sum[1:-1, 1:-1]
-        interaction_count = interaction_count[1:-1, 1:-1]
-
-    return interaction_sum, interaction_count
-
 
-def saddleplot(
+def saddle_stack(
+    clr,
+    expected,
     track,
-    saddledata,
+    contact_type,
     n_bins,
     vrange=None,
-    qrange=(0.0, 1.0),
-    cmap="coolwarm",
-    scale="log",
-    vmin=0.5,
-    vmax=2,
-    color=None,
-    title=None,
-    xlabel=None,
-    ylabel=None,
-    clabel=None,
-    fig=None,
-    fig_kws=None,
-    heatmap_kws=None,
-    margin_kws=None,
-    cbar_kws=None,
-    subplot_spec=None,
+    qrange=None,
+    view_df=None,
+    clr_weight_name="weight",
+    expected_value_col="balanced.avg",
+    view_name_col="name",
+    trim_outliers=False,
+    verbose=False,
+    drop_track_na=False,
 ):
     """
-    Generate a saddle plot.
+    Get a matrix of average interactions between genomic bin
+    pairs as a function of a specified genomic track.
+
+    The provided genomic track is either:
+    (a) digitized inside this function by passing 'n_bins', and one of 'v_range' or 'q_range'
+    (b) passed as a pre-digitized track with a categorical value column as generated by `get_digitized()`.
 
     Parameters
     ----------
-    track : pd.DataFrame
-        See get_digitized() for details.
-    saddledata : 2D array-like
-        Saddle matrix produced by `make_saddle`. It will include 2 flanking
-        rows/columns for outlier signal values, thus the shape should be
-        `(n+2, n+2)`.
-    cmap : str or matplotlib colormap
-        Colormap to use for plotting the saddle heatmap
-    scale : str
-        Color scaling to use for plotting the saddle heatmap: log or linear
-    vmin, vmax : float
-        Value limits for coloring the saddle heatmap
-    color : matplotlib color value
-        Face color for margin bar plots
-    fig : matplotlib Figure, optional
-        Specified figure to plot on. A new figure is created if none is
-        provided.
-    fig_kws : dict, optional
-        Passed on to `plt.Figure()`
-    heatmap_kws : dict, optional
-        Passed on to `ax.imshow()`
-    margin_kws : dict, optional
-        Passed on to `ax.bar()` and `ax.barh()`
-    cbar_kws : dict, optional
-        Passed on to `plt.colorbar()`
-    subplot_spec : GridSpec object
-        Specify a subregion of a figure to using a GridSpec.
-
+    clr : cooler.Cooler
+        Observed matrix.
+    expected : DataFrame in expected format
+        Diagonal summary statistics for each chromosome, and name of the column
+        with the values of expected to use.
+    contact_type : str
+        If 'cis' then only cis interactions are used to build the matrix.
+        If 'trans', only trans interactions are used.
+    track : DataFrame
+        A track, i.e. BedGraph-like dataframe, which is digitized with
+        the options n_bins, vrange and qrange. Can optionally be passed
+        as a pre-digitized dataFrame with a categorical value column,
+        as generated by get_digitzied(), also passing n_bins as None.
+    n_bins : int or None
+        number of bins for signal quantization. If None, then track must
+        be passed as a pre-digitized track.
+    vrange : tuple
+        Low and high values used for binning track values.
+        See get_digitized().
+    qrange : tuple
+        Low and high values for quantile binning track values.
+        Low must be 0.0 or more, high must be 1.0 or less.
+        Only one of vrange or qrange can be passed. See get_digitzed().
+    view_df: viewframe
+        Viewframe with genomic regions. If none, generate from track chromosomes.
+    clr_weight_name : str
+        Name of the column in the clr.bins to use as balancing weights.
+        Using raw unbalanced data is not supported for saddles.
+    expected_value_col : str
+        Name of the column in expected used for normalizing.
+    view_name_col : str
+        Name of column in view_df with region names.
+    trim_outliers : bool, optional
+        Remove first and last row and column from the output matrix.
+    verbose : bool, optional
+        If True then reports progress.
+    drop_track_na : bool, optional
+        If True then drops NaNs in input track (as if they were missing),
+        If False then counts NaNs as present in dataframe.
+        In general, this only adds check form chromosomes that have all missing values, but does not affect the results.
     Returns
     -------
-    Dictionary of axes objects.
-
+    interaction_sum : 3D array
+        The matrix of summed interaction probability between two genomic bins
+        given their values of the provided genomic track. The first dimension
+        corresponds to the index of the diagonal where the data was collected from.
+    interaction_count : 3D array
+        The matrix of the number of genomic bin pairs that contributed to the
+        corresponding pixel of ``interaction_sum``. The first dimension
+        corresponds to the index of the diagonal where the data was collected from.
     """
 
-    warnings.warn(
-        "Generating a saddleplot will be deprecated in future versions, "
-        + "please see https://github.com/open2c_examples for examples on how to plot saddles.",
-        DeprecationWarning,
-    )
-
-    from matplotlib.gridspec import GridSpec, GridSpecFromSubplotSpec
-    from matplotlib.colors import Normalize, LogNorm
-    from matplotlib import ticker
-    import matplotlib.pyplot as plt
-
-    class MinOneMaxFormatter(ticker.LogFormatter):
-        def set_locs(self, locs=None):
-            self._sublabels = set([vmin % 10 * 10, vmax % 10, 1])
+    if type(n_bins) is int:
+        # perform digitization
+        track = align_track_with_cooler(
+            track,
+            clr,
+            view_df=view_df,
+            clr_weight_name=clr_weight_name,
+            mask_clr_bad_bins=True,
+            drop_track_na=drop_track_na,  # this adds check for chromosomes that have all missing values
+        )
+        digitized_track, binedges = digitize(
+            track.iloc[:, :4],
+            n_bins,
+            vrange=vrange,
+            qrange=qrange,
+            digitized_suffix=".d",
+        )
+        digitized_col = digitized_track.columns[3]
 
-        def __call__(self, x, pos=None):
-            if x not in [vmin, 1, vmax]:
-                return ""
-            else:
-                return "{x:g}".format(x=x)
+    elif n_bins is None:
+        # assume and test if track is pre-digitized
+        digitized_track = track
+        digitized_col = digitized_track.columns[3]
+        is_track(track.astype({digitized_col: "float"}), raise_errors=True)
+        if (
+            type(digitized_track.dtypes[3])
+            is not pd.core.dtypes.dtypes.CategoricalDtype
+        ):
+            raise ValueError(
+                """when n_bins=None, saddle assumes the track has been
+                pre-digitized and the value column is a
+                pandas categorical. See get_digitized()."""
+            )
+        cats = digitized_track[digitized_col].dtype.categories.values
+        # cats has two additional categories, 0 and n_bins+1, for values
+        # falling outside range, as well as -1 for NAs.
+        n_bins = len(cats[cats > -1]) - 2
+    else:
+        raise ValueError("n_bins must be provided as int or None")
 
-    track_value_col = track.columns[3]
-    track_values = track[track_value_col].values
+    if view_df is None:
+        view_df = view_from_track(digitized_track)
+    else:
+        # Make sure view_df is a proper viewframe
+        try:
+            _ = is_compatible_viewframe(
+                view_df,
+                clr,
+                check_sorting=True,  # just in case
+                raise_errors=True,
+            )
+        except Exception as e:
+            raise ValueError("view_df is not a valid viewframe or incompatible") from e
 
-    # Digitize the track and calculate histogram
-    digitized_track, binedges = digitize(track, n_bins, vrange=vrange, qrange=qrange)
-    x = digitized_track[digitized_track.columns[3]].values.astype(int).copy()
-    x = x[(x > -1) & (x < len(binedges) + 1)]
-    hist = np.bincount(x, minlength=len(binedges) + 1)
+    # make sure provided expected is compatible
+    try:
+        _ = is_valid_expected(
+            expected,
+            contact_type,
+            view_df,
+            verify_cooler=clr,
+            expected_value_cols=[
+                expected_value_col,
+            ],
+            raise_errors=True,
+        )
+    except Exception as e:
+        raise ValueError("provided expected is not compatible") from e
 
-    if vrange is not None:
-        lo, hi = vrange
-    if qrange is not None:
-        lo, hi = qrange
-        # Reset the binedges for plotting
-        binedges = np.linspace(lo, hi, n_bins + 1)
+    # check if cooler is balanced
+    if clr_weight_name:
+        try:
+            _ = is_cooler_balanced(clr, clr_weight_name, raise_errors=True)
+        except Exception as e:
+            raise ValueError(
+                f"provided cooler is not balanced or {clr_weight_name} is missing"
+            ) from e
 
-    # Histogram and saddledata are flanked by outlier bins
-    n = saddledata.shape[0]
-    X, Y = np.meshgrid(binedges, binedges)
-    C = saddledata
-    if (n - n_bins) == 2:
-        C = C[1:-1, 1:-1]
-        hist = hist[1:-1]
-
-    # Layout
-    if subplot_spec is not None:
-        GridSpec = partial(GridSpecFromSubplotSpec, subplot_spec=subplot_spec)
-    grid = {}
-    gs = GridSpec(
-        nrows=3,
-        ncols=3,
-        width_ratios=[0.2, 1, 0.1],
-        height_ratios=[0.2, 1, 0.1],
-        wspace=0.05,
-        hspace=0.05,
-    )
+    digitized_tracks = {}
+    for num, reg in view_df.iterrows():
+        digitized_reg = bioframe.select(digitized_track, reg)
+        digitized_tracks[reg[view_name_col]] = digitized_reg[digitized_col]
 
-    # Figure
-    if fig is None:
-        fig_kws_default = dict(figsize=(5, 5))
-        fig_kws = _merge_dict(fig_kws_default, fig_kws if fig_kws is not None else {})
-        fig = plt.figure(**fig_kws)
-
-    # Heatmap
-    if scale == "log":
-        norm = LogNorm(vmin=vmin, vmax=vmax)
-    elif scale == "linear":
-        norm = Normalize(vmin=vmin, vmax=vmax)
+    # set "cis" or "trans" for supports (regions to iterate over) and matrix fetcher
+    if contact_type == "cis":
+        # precalculate max_dist using provided expected:
+        max_dist = expected["dist"].max() + 1
+        # only symmetric intra-chromosomal regions :
+        supports = list(zip(view_df[view_name_col], view_df[view_name_col]))
+        getmatrix = _make_cis_obsexp_fetcher(
+            clr,
+            expected,
+            view_df,
+            view_name_col=view_name_col,
+            expected_value_col=expected_value_col,
+            clr_weight_name=clr_weight_name,
+        )
+        _acc = partial(_accumulate_cis,
+            getmatrix=getmatrix,
+            digitized=digitized_tracks,
+            max_dist=max_dist,
+            verbose=verbose,
+        )
+    elif contact_type == "trans":
+        # fake max_dist for trans - 1:
+        max_dist = 1
+        # asymmetric inter-chromosomal regions :
+        supports = list(combinations(view_df[view_name_col], 2))
+        supports = [
+            i
+            for i in supports
+            if (
+                view_df["chrom"].loc[view_df[view_name_col] == i[0]].values
+                != view_df["chrom"].loc[view_df[view_name_col] == i[1]].values
+            )
+        ]
+        getmatrix = _make_trans_obsexp_fetcher(
+            clr,
+            expected,
+            view_df,
+            view_name_col=view_name_col,
+            expected_value_col=expected_value_col,
+            clr_weight_name=clr_weight_name,
+        )
+        _acc = partial(_accumulate_trans,
+            getmatrix=getmatrix,
+            digitized=digitized_tracks,
+            max_dist=max_dist,
+            verbose=verbose,
+        )
     else:
-        raise ValueError("Only linear and log color scaling is supported")
+        raise ValueError("Allowed values for contact_type are 'cis' or 'trans'.")
 
-    grid["ax_heatmap"] = ax = plt.subplot(gs[4])
-    heatmap_kws_default = dict(cmap=cmap, rasterized=True)
-    heatmap_kws = _merge_dict(
-        heatmap_kws_default, heatmap_kws if heatmap_kws is not None else {}
-    )
-    img = ax.pcolormesh(X, Y, C, norm=norm, **heatmap_kws)
-    plt.gca().yaxis.set_visible(False)
+    # n_bins here includes 2 open bins for values <lo and >hi.
+    _sum = np.zeros((max_dist, n_bins + 2, n_bins + 2))
+    _count = np.zeros((max_dist, n_bins + 2, n_bins + 2))
 
-    # Margins
-    margin_kws_default = dict(edgecolor="k", facecolor=color, linewidth=1)
-    margin_kws = _merge_dict(
-        margin_kws_default, margin_kws if margin_kws is not None else {}
-    )
-    # left margin hist
-    grid["ax_margin_y"] = plt.subplot(gs[3], sharey=grid["ax_heatmap"])
-    plt.barh(
-        binedges[:-1], height=np.diff(binedges), width=hist, align="edge", **margin_kws
-    )
-    plt.xlim(plt.xlim()[1], plt.xlim()[0])  # fliplr
-    plt.ylim(hi, lo)
-    plt.gca().spines["top"].set_visible(False)
-    plt.gca().spines["bottom"].set_visible(False)
-    plt.gca().spines["left"].set_visible(False)
-    plt.gca().xaxis.set_visible(False)
-    # top margin hist
-    grid["ax_margin_x"] = plt.subplot(gs[1], sharex=grid["ax_heatmap"])
-    plt.bar(
-        binedges[:-1], width=np.diff(binedges), height=hist, align="edge", **margin_kws
-    )
-    plt.xlim(lo, hi)
-    # plt.ylim(plt.ylim())  # correct
-    plt.gca().spines["top"].set_visible(False)
-    plt.gca().spines["right"].set_visible(False)
-    plt.gca().spines["left"].set_visible(False)
-    plt.gca().xaxis.set_visible(False)
-    plt.gca().yaxis.set_visible(False)
-
-    # Colorbar
-    grid["ax_cbar"] = plt.subplot(gs[5])
-    cbar_kws_default = dict(fraction=0.8, label=clabel or "")
-    cbar_kws = _merge_dict(cbar_kws_default, cbar_kws if cbar_kws is not None else {})
-    if scale == "linear" and vmin is not None and vmax is not None:
-        grid["cbar"] = cb = plt.colorbar(img, **cbar_kws)
-        # cb.set_ticks(np.arange(vmin, vmax + 0.001, 0.5))
-        # # do linspace between vmin and vmax of 5 segments and trunc to 1 decimal:
-        decimal = 10
-        nsegments = 5
-        cd_ticks = np.trunc(np.linspace(vmin, vmax, nsegments) * decimal) / decimal
-        cb.set_ticks(cd_ticks)
-    else:
-        grid["cbar"] = cb = plt.colorbar(img, format=MinOneMaxFormatter(), **cbar_kws)
-        cb.ax.yaxis.set_minor_formatter(MinOneMaxFormatter())
-
-    # extra settings
-    grid["ax_heatmap"].set_xlim(lo, hi)
-    grid["ax_heatmap"].set_ylim(hi, lo)
-    plt.grid(False)
-    plt.axis("off")
-    if title is not None:
-        grid["ax_margin_x"].set_title(title)
-    if xlabel is not None:
-        grid["ax_heatmap"].set_xlabel(xlabel)
-    if ylabel is not None:
-        grid["ax_margin_y"].set_ylabel(ylabel)
-
-    return grid
+    for reg1, reg2 in supports:
+        _acc( _sum, _count, reg1=reg1, reg2=reg2 )
+
+    # symmetrise by adding transpose "saddle"
+    # transpose 2nd and 3rd coords by leaving the 1st alone
+    _sum += _sum.transpose(0,2,1)
+    _count += _count.transpose(0,2,1)
+    if trim_outliers:
+        _sum = _sum[:, 1:-1, 1:-1]
+        _count = _count[:, 1:-1, 1:-1]
+    return _sum, _count
 
 
 def saddle_strength(S, C):
diff --git a/cooltools/cli/saddle.py b/cooltools/cli/saddle.py
index 64eca7f9..0fd520c2 100644
--- a/cooltools/cli/saddle.py
+++ b/cooltools/cli/saddle.py
@@ -1,6 +1,5 @@
 # inspired by:
 # saddles.py by @nvictus
-# https://github.com/nandankita/labUtilityTools
 from functools import partial
 import os.path as op
 import sys
@@ -125,36 +124,6 @@
     "bedGraph-style TSV.",
     required=True,
 )
-@click.option(
-    "--fig",
-    type=click.Choice(["png", "jpg", "svg", "pdf", "ps", "eps"]),
-    multiple=True,
-    help="Generate a figure and save to a file of the specified format. "
-    "If not specified - no image is generated. Repeat for multiple "
-    "output formats.",
-)
-@click.option(
-    "--scale",
-    help="Value scale for the heatmap",
-    type=click.Choice(["linear", "log"]),
-    default="log",
-    show_default=True,
-)
-@click.option(
-    "--cmap", help="Name of matplotlib colormap", default="coolwarm", show_default=True
-)
-@click.option(
-    "--vmin",
-    help="Low value of the saddleplot colorbar. "
-    "Note: value in original units irrespective of used scale, "
-    "and therefore should be positive for both vmin and vmax.",
-    type=float,
-    default=0.5,
-)
-@click.option(
-    "--vmax", help="High value of the saddleplot colorbar", type=float, default=2
-)
-@click.option("--hist-color", help="Face color of histogram bar chart")
 @click.option(
     "-v", "--verbose", help="Enable verbose output", is_flag=True, default=False
 )
@@ -172,12 +141,6 @@ def saddle(
     strength,
     view,
     out_prefix,
-    fig,
-    scale,
-    cmap,
-    vmin,
-    vmax,
-    hist_color,
     verbose,
 ):
     """
@@ -336,51 +299,3 @@ def saddle(
     # Save data
     np.savez(out_prefix + ".saddledump", **to_save)  # .npz auto-added
     digitized_track.to_csv(out_prefix + ".digitized.tsv", sep="\t", index=False)
-
-    # Generate figure
-    if len(fig):
-        try:
-            import matplotlib as mpl
-
-            mpl.use("Agg")  # savefig only for now:
-            import matplotlib.pyplot as plt
-        except ImportError:
-            print("Install matplotlib to use ", file=sys.stderr)
-            sys.exit(1)
-
-        if hist_color is None:
-            color = (
-                0.41568627450980394,
-                0.8,
-                0.39215686274509803,
-            )  # sns.color_palette('muted')[2]
-        else:
-            color = mpl.colors.colorConverter.to_rgb(hist_color)
-        title = op.basename(cool_path) + " ({})".format(contact_type)
-
-        if qrange is not None:
-            track_label = track_name + " quantiles"
-        else:
-            track_label = track_name
-
-        clabel = "(contact frequency / expected)"
-
-        api.saddle.saddleplot(
-            track,
-            saddledata,
-            n_bins,
-            vrange=vrange,
-            qrange=qrange,
-            scale=scale,
-            vmin=vmin,
-            vmax=vmax,
-            color=color,
-            title=title,
-            xlabel=track_label,
-            ylabel=track_label,
-            clabel=clabel,
-            cmap=cmap,
-        )
-
-        for ext in fig:
-            plt.savefig(out_prefix + "." + ext, bbox_inches="tight")
diff --git a/tests/test_compartments_saddle.py b/tests/test_compartments_saddle.py
index d125aa62..ce7abe7e 100644
--- a/tests/test_compartments_saddle.py
+++ b/tests/test_compartments_saddle.py
@@ -156,10 +156,6 @@ def test_saddle_cli(request, tmpdir):
             "0.5",
             "--n-bins",
             "30",
-            "--scale",
-            "log",
-            "--fig",
-            "png",
             in_cool,
             f"{out_eig_prefix}.cis.vecs.tsv",
             out_expected,
@@ -215,8 +211,6 @@ def test_trans_saddle_cli(request, tmpdir):
             "0.5",
             "--n-bins",
             "30",
-            "--scale",
-            "log",
             in_cool,
             f"{out_eig_prefix}.trans.vecs.tsv",
             out_expected,
@@ -275,8 +269,6 @@ def test_trans_saddle_cli_viewframe(request, tmpdir):
             "0.5",
             "--n-bins",
             "30",
-            "--scale",
-            "log",
             "--view",
             in_regions,
             in_cool,

From c3b3878ddacf81d04f8e4e9e686d786ddf2bab87 Mon Sep 17 00:00:00 2001
From: Sergey Venev <sergpolly@gmail.com>
Date: Fri, 19 Jan 2024 20:24:02 -0500
Subject: [PATCH 15/17] Enable futures (#485)

* pandas>2 groupby observed behavior in expected

* another groupby fix in is_track
---
 cooltools/lib/checks.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cooltools/lib/checks.py b/cooltools/lib/checks.py
index f33c6541..808d880c 100644
--- a/cooltools/lib/checks.py
+++ b/cooltools/lib/checks.py
@@ -547,7 +547,7 @@ def is_track(track, raise_errors=False):
         else:
             return False
 
-    for name, group in track.groupby(track.columns[0]):
+    for name, group in track.groupby(track.columns[0], observed=True):
         if not _is_sorted_ascending(group[track.columns[1]].values):
             if raise_errors:
                 raise ValueError(

From 39d4dfd0a9423ac32c010790fea9f48d2a8e3e67 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Tue, 23 Jan 2024 22:36:03 -0500
Subject: [PATCH 16/17] flake8 to pyproject-ruff, ran ruff format

---
 cooltools/api/snipping.py | 179 +++++++++++++------
 pyproject.toml            |  15 ++
 tests/test_snipping.py    | 358 +++++++++++++++++++++++++++-----------
 3 files changed, 399 insertions(+), 153 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index 38c67f77..cdcaaf73 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -83,7 +83,9 @@ def expand_align_features(features_df, flank, resolution, format="bed"):
             np.floor(features_df["center"] / resolution) - flank // resolution
         ).astype(int)
         features_df["hi"] = (
-            np.floor(features_df["center"] / resolution) + flank // resolution + 1
+            np.floor(features_df["center"] / resolution)
+            + flank // resolution
+            + 1
         ).astype(int)
         features_df["start"] = features_df["lo"] * resolution
         features_df["end"] = features_df["hi"] * resolution
@@ -91,14 +93,20 @@ def expand_align_features(features_df, flank, resolution, format="bed"):
         features_df[
             ["orig_start1", "orig_end1", "orig_start2", "orig_end2"]
         ] = features_df[["start1", "end1", "start2", "end2"]]
-        features_df["center1"] = (features_df["start1"] + features_df["end1"]) / 2
-        features_df["center2"] = (features_df["start2"] + features_df["end2"]) / 2
+        features_df["center1"] = (
+            features_df["start1"] + features_df["end1"]
+        ) / 2
+        features_df["center2"] = (
+            features_df["start2"] + features_df["end2"]
+        ) / 2
 
         features_df["lo1"] = (
             np.floor(features_df["center1"] / resolution) - flank // resolution
         ).astype(int)
         features_df["hi1"] = (
-            np.floor(features_df["center1"] / resolution) + flank // resolution + 1
+            np.floor(features_df["center1"] / resolution)
+            + flank // resolution
+            + 1
         ).astype(int)
         features_df["start1"] = features_df["lo1"] * resolution
         features_df["end1"] = features_df["hi1"] * resolution
@@ -107,12 +115,16 @@ def expand_align_features(features_df, flank, resolution, format="bed"):
             np.floor(features_df["center2"] / resolution) - flank // resolution
         ).astype(int)
         features_df["hi2"] = (
-            np.floor(features_df["center2"] / resolution) + flank // resolution + 1
+            np.floor(features_df["center2"] / resolution)
+            + flank // resolution
+            + 1
         ).astype(int)
         features_df["start2"] = features_df["lo2"] * resolution
         features_df["end2"] = features_df["hi2"] * resolution
     else:
-        raise ValueError(f"feature_type can be 'bed' or 'bedpe', {format} is provided.")
+        raise ValueError(
+            f"feature_type can be 'bed' or 'bedpe', {format} is provided."
+        )
     return features_df
 
 
@@ -194,7 +206,9 @@ def _extract_stack(data_select, data_snip, arg):
         lo = feature_group["lo"].to_numpy()
         hi = feature_group["hi"].to_numpy()
         s = (hi - lo).astype(int)  # Shape of individual snips
-        assert s.max() == s.min(), "Pileup accepts only windows of the same size"
+        assert (
+            s.max() == s.min()
+        ), "Pileup accepts only windows of the same size"
         stack = np.full((len(feature_group), s[0], s[0]), np.nan)
     else:
         region1 = region2 = support
@@ -202,7 +216,9 @@ def _extract_stack(data_select, data_snip, arg):
         e1 = feature_group["end"].to_numpy()
         s2, e2 = s1, e1
         data = data_select(region1, region2)
-        stack = list(map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2)))
+        stack = list(
+            map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2))
+        )
         stack = np.stack(stack)
     return stack, feature_group["_rank"].to_numpy()
 
@@ -219,8 +235,12 @@ def _extract_stack_paired(data_select, data_snip, arg):
         hi2 = feature_group["hi2"].to_numpy()
         s1 = (hi1 - lo1).astype(int)  # Shape of individual snips
         s2 = (hi2 - lo2).astype(int)
-        assert s1.max() == s1.min(), "Pileup accepts only windows of the same size"
-        assert s2.max() == s2.min(), "Pileup accepts only windows of the same size"
+        assert (
+            s1.max() == s1.min()
+        ), "Pileup accepts only windows of the same size"
+        assert (
+            s2.max() == s2.min()
+        ), "Pileup accepts only windows of the same size"
         stack = np.full((len(feature_group), s1[0], s2[0]), np.nan)
     else:
         s1 = feature_group["start1"].to_numpy()
@@ -228,7 +248,9 @@ def _extract_stack_paired(data_select, data_snip, arg):
         s2 = feature_group["start2"].to_numpy()
         e2 = feature_group["end2"].to_numpy()
         data = data_select(region1, region2)
-        stack = list(map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2)))
+        stack = list(
+            map(partial(data_snip, data, region1, region2), zip(s1, e1, s2, e2))
+        )
         stack = np.stack(stack)
     return stack, feature_group["_rank"].to_numpy()
 
@@ -281,13 +303,17 @@ def _pileup(features, feature_type, data_select, data_snip, map=map):
         # fill in unanotated view regions with empty string
         features["region1"] = features["region1"].fillna("")
         features["region2"] = features["region2"].fillna("")
-        _extract_group_data = partial(_extract_stack_paired, data_select, data_snip)
+        _extract_group_data = partial(
+            _extract_stack_paired, data_select, data_snip
+        )
         _feature_groups = features.groupby(["region1", "region2"], sort=False)
     else:
-        raise ValueError(f"feature_type can be only bed or bedpe, {feature_type} is provided.")
+        raise ValueError(
+            f"feature_type can be only bed or bedpe, {feature_type} is provided."
+        )
 
     # perform stack extraction on a per-region basis using _extract_group_data and _feature_groups
-    cumul_stack, orig_rank = zip( *map( _extract_group_data, _feature_groups ) )
+    cumul_stack, orig_rank = zip(*map(_extract_group_data, _feature_groups))
     # Restore the original rank of the input features
     cumul_stack = np.concatenate(cumul_stack, axis=0)
     orig_rank = np.concatenate(orig_rank)
@@ -299,7 +325,9 @@ def _pileup(features, feature_type, data_select, data_snip, map=map):
     # lower-symmetrical values for near-diagonal snips - but for
     # on-diagonal pileups it has to be mitigated to restore symmetry:
     if feature_type == "bed":
-        cumul_stack = np.fmax(cumul_stack, np.transpose(cumul_stack, axes=(0, 2, 1)))
+        cumul_stack = np.fmax(
+            cumul_stack, np.transpose(cumul_stack, axes=(0, 2, 1))
+        )
 
     return cumul_stack
 
@@ -368,21 +396,25 @@ def select(self, region1, region2):
         """
         region1_coords = tuple(self.view_df.loc[region1])
         region2_coords = tuple(self.view_df.loc[region2])
-        self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
-            region1_coords[0]
-        )
-        self.offsets[region2] = self.clr.offset(region2_coords) - self.clr.offset(
-            region2_coords[0]
-        )
+        self.offsets[region1] = self.clr.offset(
+            region1_coords
+        ) - self.clr.offset(region1_coords[0])
+        self.offsets[region2] = self.clr.offset(
+            region2_coords
+        ) - self.clr.offset(region2_coords[0])
         matrix = self.clr.matrix(**self.cooler_opts).fetch(
             region1_coords, region2_coords
         )
         if self.clr_weight_name:
             self._isnan1 = np.isnan(
-                self.clr.bins()[self.clr_weight_name].fetch(region1_coords).values
+                self.clr.bins()[self.clr_weight_name]
+                .fetch(region1_coords)
+                .values
             )
             self._isnan2 = np.isnan(
-                self.clr.bins()[self.clr_weight_name].fetch(region2_coords).values
+                self.clr.bins()[self.clr_weight_name]
+                .fetch(region2_coords)
+                .values
             )
         else:
             self._isnan1 = np.zeros_like(
@@ -394,7 +426,9 @@ def select(self, region1, region2):
         if self.cooler_opts["sparse"]:
             matrix = matrix.tocsr()
         if self.min_diag is not None:
-            diags = np.arange(np.diff(self.clr.extent(region1_coords)), dtype=np.int32)
+            diags = np.arange(
+                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
+            )
             self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
         return matrix
 
@@ -543,13 +577,15 @@ def select(self, region1, region2):
         region1_coords = tuple(self.view_df.loc[region1])
         region2_coords = tuple(self.view_df.loc[region2])
         if region1_coords[0] != region2_coords[0]:
-            raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
-        self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
-            region1_coords[0]
-        )
-        self.offsets[region2] = self.clr.offset(region2_coords) - self.clr.offset(
-            region2_coords[0]
-        )
+            raise ValueError(
+                "ObsExpSnipper is implemented for cis contacts only."
+            )
+        self.offsets[region1] = self.clr.offset(
+            region1_coords
+        ) - self.clr.offset(region1_coords[0])
+        self.offsets[region2] = self.clr.offset(
+            region2_coords
+        ) - self.clr.offset(region2_coords[0])
         matrix = self.clr.matrix(**self.cooler_opts).fetch(
             region1_coords, region2_coords
         )
@@ -557,10 +593,14 @@ def select(self, region1, region2):
             matrix = matrix.tocsr()
         if self.clr_weight_name:
             self._isnan1 = np.isnan(
-                self.clr.bins()[self.clr_weight_name].fetch(region1_coords).values
+                self.clr.bins()[self.clr_weight_name]
+                .fetch(region1_coords)
+                .values
             )
             self._isnan2 = np.isnan(
-                self.clr.bins()[self.clr_weight_name].fetch(region2_coords).values
+                self.clr.bins()[self.clr_weight_name]
+                .fetch(region2_coords)
+                .values
             )
         else:
             self._isnan1 = np.zeros_like(
@@ -575,7 +615,9 @@ def select(self, region1, region2):
             .values
         )
         if self.min_diag is not None:
-            diags = np.arange(np.diff(self.clr.extent(region1_coords)), dtype=np.int32)
+            diags = np.arange(
+                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
+            )
             self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
         return matrix
 
@@ -649,7 +691,12 @@ def snip(self, matrix, region1, region2, tup):
 
 class ExpectedSnipper:
     def __init__(
-        self, clr, expected, view_df, min_diag=2, expected_value_col="balanced.avg"
+        self,
+        clr,
+        expected,
+        view_df,
+        min_diag=2,
+        expected_value_col="balanced.avg",
     ):
         """Class for generating expected snips
 
@@ -700,13 +747,15 @@ def select(self, region1, region2):
         region1_coords = tuple(self.view_df.loc[region1])
         region2_coords = tuple(self.view_df.loc[region2])
         if region1_coords[0] != region2_coords[0]:
-            raise ValueError("ObsExpSnipper is implemented for cis contacts only.")
-        self.offsets[region1] = self.clr.offset(region1_coords) - self.clr.offset(
-            region1_coords[0]
-        )
-        self.offsets[region2] = self.clr.offset(region2_coords) - self.clr.offset(
-            region2_coords[0]
-        )
+            raise ValueError(
+                "ObsExpSnipper is implemented for cis contacts only."
+            )
+        self.offsets[region1] = self.clr.offset(
+            region1_coords
+        ) - self.clr.offset(region1_coords[0])
+        self.offsets[region2] = self.clr.offset(
+            region2_coords
+        ) - self.clr.offset(region2_coords[0])
         self.m = np.diff(self.clr.extent(region1_coords))
         self.n = np.diff(self.clr.extent(region2_coords))
         self._expected = LazyToeplitz(
@@ -715,7 +764,9 @@ def select(self, region1, region2):
             .values
         )
         if self.min_diag is not None:
-            diags = np.arange(np.diff(self.clr.extent(region1_coords)), dtype=np.int32)
+            diags = np.arange(
+                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
+            )
             self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
         return self._expected
 
@@ -833,7 +884,9 @@ def pileup(
                 raise_errors=True,
             )
         except Exception as e:
-            raise ValueError("view_df is not a valid viewframe or incompatible") from e
+            raise ValueError(
+                "view_df is not a valid viewframe or incompatible"
+            ) from e
 
     # check expected compatibility when provided
     if expected_df is not None:
@@ -851,7 +904,9 @@ def pileup(
         except Exception as e:
             raise ValueError("provided expected is not valid") from e
 
-    features_df = assign_view_auto(features_df, view_df, combined_assignments_column=False)
+    features_df = assign_view_auto(
+        features_df, view_df, combined_assignments_column=False
+    )
     # TODO: switch to bioframe.assign_view upon update
 
     if flank is not None:
@@ -864,9 +919,13 @@ def pileup(
             features_df["lo"] = (features_df["start"] / clr.binsize).astype(int)
             features_df["hi"] = (features_df["end"] / clr.binsize).astype(int)
         else:
-            features_df["lo1"] = (features_df["start1"] / clr.binsize).astype(int)
+            features_df["lo1"] = (features_df["start1"] / clr.binsize).astype(
+                int
+            )
             features_df["hi1"] = (features_df["end1"] / clr.binsize).astype(int)
-            features_df["lo2"] = (features_df["start2"] / clr.binsize).astype(int)
+            features_df["lo2"] = (features_df["start2"] / clr.binsize).astype(
+                int
+            )
             features_df["hi2"] = (features_df["end2"] / clr.binsize).astype(int)
 
     if clr_weight_name not in [None, False]:
@@ -887,16 +946,19 @@ def pileup(
 
     # Find region offsets and then subtract them from the feature extents
 
-    region_offsets = view_df[["chrom", "start", "end"]].apply(clr.offset, axis=1)
+    region_offsets = view_df[["chrom", "start", "end"]].apply(
+        clr.offset, axis=1
+    )
     region_offsets_dict = dict(zip(view_df["name"].values, region_offsets))
 
-
     if feature_type == "bed":
         if features_df["region"].isnull().any():
             warnings.warn(
                 "Some features do not have view regions assigned! Some snips will be empty."
             )
-        features_df["region_offset"] = features_df["region"].replace(region_offsets_dict)
+        features_df["region_offset"] = features_df["region"].replace(
+            region_offsets_dict
+        )
         features_df[["lo", "hi"]] = (
             features_df[["lo", "hi"]]
             .subtract(
@@ -906,11 +968,16 @@ def pileup(
             .astype(int)
         )
     else:
-        if features_df["region1"].isnull().any() or features_df["region2"].isnull().any():
+        if (
+            features_df["region1"].isnull().any()
+            or features_df["region2"].isnull().any()
+        ):
             warnings.warn(
                 "Some features do not have view regions assigned! Some snips will be empty."
             )
-        features_df["region1_offset"] = features_df["region1"].replace(region_offsets_dict)
+        features_df["region1_offset"] = features_df["region1"].replace(
+            region_offsets_dict
+        )
         features_df[["lo1", "hi1"]] = (
             features_df[["lo1", "hi1"]]
             .subtract(
@@ -919,7 +986,9 @@ def pileup(
             )
             .astype(int)
         )
-        features_df["region2_offset"] = features_df["region2"].replace(region_offsets_dict)
+        features_df["region2_offset"] = features_df["region2"].replace(
+            region_offsets_dict
+        )
         features_df[["lo2", "hi2"]] = (
             features_df[["lo2", "hi2"]]
             .subtract(
@@ -954,7 +1023,9 @@ def pileup(
     else:
         mymap = map
 
-    stack = _pileup(features_df, feature_type, snipper.select, snipper.snip, map=mymap)
+    stack = _pileup(
+        features_df, feature_type, snipper.select, snipper.snip, map=mymap
+    )
 
     if nproc > 1:
         pool.close()
diff --git a/pyproject.toml b/pyproject.toml
index effcaf0e..35ba4c94 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,18 @@
 [build-system]
 requires = ["setuptools", "cython", "numpy"]
 build-backend = "setuptools.build_meta"
+[tool.ruff]
+exclude = [
+    "__init__.py",
+    "__main__.py",
+]
+ignore = ["E501"]
+line-length = 80
+select = [
+    "B",
+    "C",
+    "E",
+    "F",
+    "W",
+]
+
diff --git a/tests/test_snipping.py b/tests/test_snipping.py
index e33bce65..524ab917 100644
--- a/tests/test_snipping.py
+++ b/tests/test_snipping.py
@@ -14,9 +14,13 @@
 
 def test_pileup_cli_npz(request, tmpdir):
     in_cool = op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool")
-    in_features = op.join(request.fspath.dirname, "data/CN.mm9.toy_features.bed")
+    in_features = op.join(
+        request.fspath.dirname, "data/CN.mm9.toy_features.bed"
+    )
     in_regions = op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed")
-    in_expected = op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv")
+    in_expected = op.join(
+        request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"
+    )
     out_file = op.join(tmpdir, "tmp.npz")
     runner = CliRunner()
     # Output npz file:
@@ -50,9 +54,13 @@ def test_pileup_cli_npz(request, tmpdir):
 
 def test_pileup_cli_hdf5(request, tmpdir):
     in_cool = op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool")
-    in_features = op.join(request.fspath.dirname, "data/CN.mm9.toy_features.bed")
+    in_features = op.join(
+        request.fspath.dirname, "data/CN.mm9.toy_features.bed"
+    )
     in_regions = op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed")
-    in_expected = op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv")
+    in_expected = op.join(
+        request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"
+    )
     out_file = op.join(tmpdir, "tmp.hdf5")
     runner = CliRunner()
 
@@ -86,14 +94,20 @@ def test_pileup_cli_hdf5(request, tmpdir):
     )
     assert result.exit_code == 0
 
+
 # define fixture with clr, exp and view_df to be reused across many tests
 # fixture return a dict and values can be accessed e.g. as data["clr"]
 @pytest.fixture
 def data(request):
-    clr = cooler.Cooler(op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool"))
-    exp = pd.read_table(op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv"))
+    clr = cooler.Cooler(
+        op.join(request.fspath.dirname, "data/CN.mm9.1000kb.cool")
+    )
+    exp = pd.read_table(
+        op.join(request.fspath.dirname, "data/CN.mm9.toy_expected.tsv")
+    )
     view_df = bioframe.read_table(
-        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"), schema="bed4"
+        op.join(request.fspath.dirname, "data/CN.mm9.toy_regions.bed"),
+        schema="bed4",
     )
     return {
         "clr": clr,
@@ -103,7 +117,6 @@ def data(request):
 
 
 def test_pileup(request, data):
-
     # I.
     # Example on-diagonal features, two regions from annotated genomic regions:
     windows = pd.DataFrame(
@@ -114,7 +127,9 @@ def test_pileup(request, data):
         }
     )
 
-    stack = cooltools.api.snipping.pileup(data["clr"], windows, view_df=None, flank=None)
+    stack = cooltools.api.snipping.pileup(
+        data["clr"], windows, view_df=None, flank=None
+    )
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
     # Check that NaNs were propagated
@@ -122,7 +137,11 @@ def test_pileup(request, data):
     assert not np.all(np.isnan(stack))
 
     stack = cooltools.api.snipping.pileup(
-        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
+        data["clr"],
+        windows,
+        view_df=data["view"],
+        expected_df=data["exp"],
+        flank=None,
     )
     # Check that the size of snips is OK and there are two of them.
     # Now with view and expected:
@@ -141,7 +160,11 @@ def test_pileup(request, data):
         }
     )
     stack = cooltools.api.snipping.pileup(
-        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
+        data["clr"],
+        windows,
+        view_df=data["view"],
+        expected_df=data["exp"],
+        flank=None,
     )
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
@@ -159,7 +182,11 @@ def test_pileup(request, data):
         }
     )
     stack = cooltools.api.snipping.pileup(
-        data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
+        data["clr"],
+        windows,
+        view_df=data["view"],
+        expected_df=data["exp"],
+        flank=None,
     )
     # Check that the size of snips is OK and there are two of them:
     assert stack.shape == (2, 5, 5)
@@ -176,7 +203,9 @@ def test_pileup(request, data):
         }
     )
     with pytest.raises(ValueError):
-        stack = cooltools.api.snipping.pileup(data["clr"], windows, data["view"], data["exp"], flank=None)
+        stack = cooltools.api.snipping.pileup(
+            data["clr"], windows, data["view"], data["exp"], flank=None
+        )
 
     # DRAFT # Should work with force=True:
     # stack = cooltools.api.snipping.pileup(data["clr"], windows, view_df, data["exp"], flank=None, force=True)
@@ -197,7 +226,11 @@ def test_pileup(request, data):
     )
     with pytest.raises(ValueError):
         stack = cooltools.api.snipping.pileup(
-            data["clr"], windows, view_df=data["view"], expected_df=data["exp"], flank=None
+            data["clr"],
+            windows,
+            view_df=data["view"],
+            expected_df=data["exp"],
+            flank=None,
         )
 
     # DRAFT # Should work with force=True:
@@ -220,11 +253,14 @@ def test_ondiag__pileup_with_expected(request, data):
         # I.
         # Example region with windows, two regions from annotated genomic regions:
         windows = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [102_000_000, 105_000_000], flank_bp=2_000_000
-        )
-        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-            drop=True
+            1_000_000,
+            ["chr1", "chr1"],
+            [102_000_000, 105_000_000],
+            flank_bp=2_000_000,
         )
+        windows = cooltools.lib.common.assign_view_auto(
+            windows, data["view"]
+        ).reset_index(drop=True)
         stack = cooltools.api.snipping._pileup(
             windows, feature_type, snipper.select, snipper.snip, map=map
         )
@@ -235,11 +271,14 @@ def test_ondiag__pileup_with_expected(request, data):
         # II.
         # Example region with windows, second window comes from unannotated genomic region:
         windows = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [120_000_000, 160_000_000], flank_bp=2_000_000
-        )
-        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-            drop=True
+            1_000_000,
+            ["chr1", "chr1"],
+            [120_000_000, 160_000_000],
+            flank_bp=2_000_000,
         )
+        windows = cooltools.lib.common.assign_view_auto(
+            windows, data["view"]
+        ).reset_index(drop=True)
 
         stack = cooltools.api.snipping._pileup(
             windows, feature_type, snipper.select, snipper.snip, map=map
@@ -258,12 +297,17 @@ def test_ondiag__pileup_without_expected(request, data):
     # I.
     # Example region with windows, two regions from annotated genomic regions:
     windows = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [120_000_000, 140_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [120_000_000, 140_000_000],
+        flank_bp=2_000_000,
     )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=None
     )
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=None)
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -274,11 +318,14 @@ def test_ondiag__pileup_without_expected(request, data):
     # II.
     # Example region with windows, second window comes from unannotated genomic region:
     windows = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [120_000_000, 160_000_000], flank_bp=2_000_000
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        1_000_000,
+        ["chr1", "chr1"],
+        [120_000_000, 160_000_000],
+        flank_bp=2_000_000,
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
@@ -289,7 +336,9 @@ def test_ondiag__pileup_without_expected(request, data):
     assert np.all(np.isnan(stack[1]))
 
 
-def test_ondiag__pileup_without_expected_with_result_validation(request, allclose, data):
+def test_ondiag__pileup_without_expected_with_result_validation(
+    request, allclose, data
+):
     """
     Test the snipping on matrix:
     """
@@ -298,15 +347,18 @@ def test_ondiag__pileup_without_expected_with_result_validation(request, allclos
 
     # Example region with windows, two regions from annotated genomic regions:
     windows = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [110_000_000, 140_000_000], flank_bp=2_000_000
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        1_000_000,
+        ["chr1", "chr1"],
+        [110_000_000, 140_000_000],
+        flank_bp=2_000_000,
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     # generate reference stack using naive cooler.matrix.fetch extraction:
     ref_stack = []
-    for _win in windows[["chrom","start","end"]].itertuples(index=False):
+    for _win in windows[["chrom", "start", "end"]].itertuples(index=False):
         _mat = data["clr"].matrix().fetch(_win)
         # fill min_diag diagonals with NaNs
         for d in range(-min_diag + 1, min_diag):
@@ -314,7 +366,9 @@ def test_ondiag__pileup_without_expected_with_result_validation(request, allclos
         ref_stack.append(_mat)
     ref_stack = np.asarray(ref_stack)
 
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=min_diag
+    )
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -338,17 +392,27 @@ def test_offdiag__pileup_with_expected(request, data):
         # I.
         # Example region with windows, two off-diagonal features from annotated genomic regions:
         windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [102_000_000, 105_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [102_000_000, 105_000_000],
+            flank_bp=2_000_000,
         )
         windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [105_000_000, 109_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [105_000_000, 109_000_000],
+            flank_bp=2_000_000,
         )
         windows = pd.merge(
-            windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-        )
-        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-            drop=True
+            windows1,
+            windows2,
+            left_index=True,
+            right_index=True,
+            suffixes=("1", "2"),
         )
+        windows = cooltools.lib.common.assign_view_auto(
+            windows, data["view"]
+        ).reset_index(drop=True)
 
         stack = cooltools.api.snipping._pileup(
             windows, feature_type, snipper.select, snipper.snip, map=map
@@ -360,17 +424,27 @@ def test_offdiag__pileup_with_expected(request, data):
         # II.
         # Example region with windows, second window is between two different regions:
         windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [102_000_000, 10_000_000],
+            flank_bp=2_000_000,
         )
         windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [105_000_000, 109_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [105_000_000, 109_000_000],
+            flank_bp=2_000_000,
         )
         windows = pd.merge(
-            windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-        )
-        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-            drop=True
+            windows1,
+            windows2,
+            left_index=True,
+            right_index=True,
+            suffixes=("1", "2"),
         )
+        windows = cooltools.lib.common.assign_view_auto(
+            windows, data["view"]
+        ).reset_index(drop=True)
 
         stack = cooltools.api.snipping._pileup(
             windows, feature_type, snipper.select, snipper.snip, map=map
@@ -383,17 +457,27 @@ def test_offdiag__pileup_with_expected(request, data):
         # Example region with windows on diagonal, treated as off-diagonal. Check bottom
         # triangle is all NaN
         windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [102_000_000, 10_000_000],
+            flank_bp=2_000_000,
         )
         windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-            1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+            1_000_000,
+            ["chr1", "chr1"],
+            [102_000_000, 10_000_000],
+            flank_bp=2_000_000,
         )
         windows = pd.merge(
-            windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-        )
-        windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-            drop=True
+            windows1,
+            windows2,
+            left_index=True,
+            right_index=True,
+            suffixes=("1", "2"),
         )
+        windows = cooltools.lib.common.assign_view_auto(
+            windows, data["view"]
+        ).reset_index(drop=True)
 
         stack = cooltools.api.snipping._pileup(
             windows, feature_type, snipper.select, snipper.snip, map=map
@@ -401,10 +485,16 @@ def test_offdiag__pileup_with_expected(request, data):
 
         assert stack.shape == (2, 5, 5)
         assert np.all(
-            [np.all(np.isnan(snip[np.tril_indices_from(snip, 1)])) for snip in stack]
+            [
+                np.all(np.isnan(snip[np.tril_indices_from(snip, 1)]))
+                for snip in stack
+            ]
         )
 
-def test_offdiag__pileup_without_expected_with_result_validation(request, allclose, data):
+
+def test_offdiag__pileup_without_expected_with_result_validation(
+    request, allclose, data
+):
     """
     Test the snipping on matrix:
     """
@@ -414,21 +504,33 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
     # I.
     # Example region with windows, two regions from annotated genomic regions:
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 115_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 115_000_000],
+        flank_bp=2_000_000,
     )
     windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [115_000_000, 140_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [115_000_000, 140_000_000],
+        flank_bp=2_000_000,
     )
     windows = pd.merge(
-        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        windows1,
+        windows2,
+        left_index=True,
+        right_index=True,
+        suffixes=("1", "2"),
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     # generate reference stack using naive cooler.matrix.fetch extraction:
     ref_stack = []
-    for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
+    for _win in windows[
+        ["chrom1", "start1", "end1", "chrom2", "start2", "end2"]
+    ].itertuples(index=False):
         _reg1 = _win[:3]
         _reg2 = _win[3:]
         _mat = data["clr"].matrix().fetch(_reg1, _reg2)
@@ -436,35 +538,51 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
         ref_stack.append(_mat)
     ref_stack = np.asarray(ref_stack)
 
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=min_diag
+    )
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
 
     # Check that the size of snips is OK, there are two of them and their value are OK:
     assert stack.shape == (len(windows), 5, 5)
-    assert allclose(stack, ref_stack, equal_nan = True)
+    assert allclose(stack, ref_stack, equal_nan=True)
 
     # II.
     # Example trans features
     min_diag = None
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=min_diag)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=min_diag
+    )
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 120_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 120_000_000],
+        flank_bp=2_000_000,
     )
     windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr2", "chr2"], [102_000_000, 130_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr2", "chr2"],
+        [102_000_000, 130_000_000],
+        flank_bp=2_000_000,
     )
     windows = pd.merge(
-        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        windows1,
+        windows2,
+        left_index=True,
+        right_index=True,
+        suffixes=("1", "2"),
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     # generate reference stack using naive cooler.matrix.fetch extraction:
     ref_stack = []
-    for _win in windows[["chrom1", "start1", "end1", "chrom2", "start2", "end2"]].itertuples(index=False):
+    for _win in windows[
+        ["chrom1", "start1", "end1", "chrom2", "start2", "end2"]
+    ].itertuples(index=False):
         _reg1 = _win[:3]
         _reg2 = _win[3:]
         _mat = data["clr"].matrix().fetch(_reg1, _reg2)
@@ -477,8 +595,7 @@ def test_offdiag__pileup_without_expected_with_result_validation(request, allclo
 
     # check shape and values
     assert stack.shape == (len(windows), 5, 5)
-    assert allclose(stack, ref_stack, equal_nan = True)
-
+    assert allclose(stack, ref_stack, equal_nan=True)
 
 
 def test_offdiag__pileup_without_expected(request, data):
@@ -490,19 +607,31 @@ def test_offdiag__pileup_without_expected(request, data):
     # I.
     # Example region with windows, two regions from annotated genomic regions:
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 105_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 105_000_000],
+        flank_bp=2_000_000,
     )
     windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [105_000_000, 109_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [105_000_000, 109_000_000],
+        flank_bp=2_000_000,
     )
     windows = pd.merge(
-        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        windows1,
+        windows2,
+        left_index=True,
+        right_index=True,
+        suffixes=("1", "2"),
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=None)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=None
+    )
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
     )
@@ -513,17 +642,27 @@ def test_offdiag__pileup_without_expected(request, data):
     # II.
     # Example region with windows, second window comes from unannotated genomic region:
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 10_000_000],
+        flank_bp=2_000_000,
     )
     windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [105_000_000, 109_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [105_000_000, 109_000_000],
+        flank_bp=2_000_000,
     )
     windows = pd.merge(
-        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        windows1,
+        windows2,
+        left_index=True,
+        right_index=True,
+        suffixes=("1", "2"),
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
@@ -536,19 +675,31 @@ def test_offdiag__pileup_without_expected(request, data):
     # III.
     # Example region with windows on diagonal, treated as off-diagonal. Check bottom
     # triangle is all NaN
-    snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"], min_diag=2)
+    snipper = cooltools.api.snipping.CoolerSnipper(
+        data["clr"], data["view"], min_diag=2
+    )
     windows1 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 10_000_000],
+        flank_bp=2_000_000,
     )
     windows2 = cooltools.api.snipping.make_bin_aligned_windows(
-        1_000_000, ["chr1", "chr1"], [102_000_000, 10_000_000], flank_bp=2_000_000
+        1_000_000,
+        ["chr1", "chr1"],
+        [102_000_000, 10_000_000],
+        flank_bp=2_000_000,
     )
     windows = pd.merge(
-        windows1, windows2, left_index=True, right_index=True, suffixes=("1", "2")
-    )
-    windows = cooltools.lib.common.assign_view_auto(windows, data["view"]).reset_index(
-        drop=True
+        windows1,
+        windows2,
+        left_index=True,
+        right_index=True,
+        suffixes=("1", "2"),
     )
+    windows = cooltools.lib.common.assign_view_auto(
+        windows, data["view"]
+    ).reset_index(drop=True)
 
     stack = cooltools.api.snipping._pileup(
         windows, feature_type, snipper.select, snipper.snip, map=map
@@ -556,7 +707,10 @@ def test_offdiag__pileup_without_expected(request, data):
 
     assert stack.shape == (2, 5, 5)
     assert np.all(
-        [np.all(np.isnan(snip[np.tril_indices_from(snip, 1)])) for snip in stack]
+        [
+            np.all(np.isnan(snip[np.tril_indices_from(snip, 1)]))
+            for snip in stack
+        ]
     )
 
 
@@ -568,7 +722,10 @@ def test_snipper_with_view_and_expected(request, data):
         snipper = snipper_class(data["clr"], data["exp"], data["view"])
         matrix = snipper.select("foo", "foo")
         snippet = snipper.snip(
-            matrix, "foo", "foo", (110_000_000, 120_000_000, 110_000_000, 120_000_000)
+            matrix,
+            "foo",
+            "foo",
+            (110_000_000, 120_000_000, 110_000_000, 120_000_000),
         )
         assert snippet.shape is not None
 
@@ -577,6 +734,9 @@ def test_cooler_snipper_with_view(request, data):
     snipper = cooltools.api.snipping.CoolerSnipper(data["clr"], data["view"])
     matrix = snipper.select("foo", "foo")
     snippet = snipper.snip(
-        matrix, "foo", "foo", (110_000_000, 120_000_000, 110_000_000, 120_000_000)
+        matrix,
+        "foo",
+        "foo",
+        (110_000_000, 120_000_000, 110_000_000, 120_000_000),
     )
     assert snippet.shape is not None

From c8a6f0a9761a319cb91b3dc2b6ee7a5704a4d0e5 Mon Sep 17 00:00:00 2001
From: sergpolly <sergpolly@gmail.com>
Date: Thu, 25 Jan 2024 23:49:45 -0500
Subject: [PATCH 17/17] enable arbitrary cis region, remove padding code

---
 cooltools/api/snipping.py | 276 ++++++++++++++++++--------------------
 1 file changed, 131 insertions(+), 145 deletions(-)

diff --git a/cooltools/api/snipping.py b/cooltools/api/snipping.py
index cdcaaf73..dbcc27a8 100644
--- a/cooltools/api/snipping.py
+++ b/cooltools/api/snipping.py
@@ -4,24 +4,24 @@
 The main user-facing function of this module is `pileup`, it performs pileups using
 snippers and other functions defined in the module.  The concept is the following:
 
-- First, the provided features are annotated with the regions from a view (or simply  
+- First, the provided features are annotated with the regions from a view (or simply
   whole chromosomes, if no view is provided). They are assigned to the region that
   contains it, or the one with the largest overlap.
-- Then the features are expanded using the `flank` argument, and aligned to the bins  
+- Then the features are expanded using the `flank` argument, and aligned to the bins
   of the cooler
-- Depending on the requested operation (whether the normalization to expected is  
+- Depending on the requested operation (whether the normalization to expected is
   required), the appropriate snipper object is created
-- A snipper can `select` a particular region of a genome-wide matrix, meaning it  
+- A snipper can `select` a particular region of a genome-wide matrix, meaning it
   stores its sparse representation in memory. This could be whole chromosomes or
   chromosome arms, for example
-- A snipper can `snip` a small area of a selected region, meaning it will extract  
+- A snipper can `snip` a small area of a selected region, meaning it will extract
   and return a dense representation of this area
-- For each region present, it is first `select`ed, and then all features within it are  
+- For each region present, it is first `select`ed, and then all features within it are
   `snip`ped, creating a stack: a 3D array containing all snippets for this region
-- For features that are not assigned to any region, an empty snippet is returned  
-- All per-region stacks are then combined into one, which then can be averaged to create  
+- For features that are not assigned to any region, an empty snippet is returned
+- All per-region stacks are then combined into one, which then can be averaged to create
   a single pileup
-- The order of snippets in the stack matches the order of features, this way the stack  
+- The order of snippets in the stack matches the order of features, this way the stack
   can also be used for analysis of any subsets of original features
 
 This procedure achieves a good tradeoff between speed and RAM. Extracting each
@@ -45,7 +45,7 @@
 )
 from ..lib.common import assign_view_auto, make_cooler_view
 
-from ..lib.numutils import LazyToeplitz
+from ..lib.numutils import LazyToeplitz, set_diag
 import warnings
 
 import multiprocessing
@@ -356,9 +356,8 @@ def __init__(self, clr, view_df, cooler_opts=None, min_diag=2):
         self.view_df = view_df.set_index("name")
         self.clr = clr
         self.binsize = self.clr.binsize
+        self.min_diag = min_diag
         self.offsets = {}
-        self.diag_indicators = {}
-        self.pad = True
         self.cooler_opts = {} if cooler_opts is None else cooler_opts
         self.cooler_opts.setdefault("sparse", True)
 
@@ -374,7 +373,6 @@ def __init__(self, clr, view_df, cooler_opts=None, min_diag=2):
                 self.clr_weight_name = self.cooler_opts["balance"]
         else:
             self.clr_weight_name = "weight"
-        self.min_diag = min_diag
 
     def select(self, region1, region2):
         """Select a portion of the cooler for snipping based on two regions in the view
@@ -396,40 +394,33 @@ def select(self, region1, region2):
         """
         region1_coords = tuple(self.view_df.loc[region1])
         region2_coords = tuple(self.view_df.loc[region2])
-        self.offsets[region1] = self.clr.offset(
-            region1_coords
-        ) - self.clr.offset(region1_coords[0])
-        self.offsets[region2] = self.clr.offset(
-            region2_coords
-        ) - self.clr.offset(region2_coords[0])
+        chrom1_offset = self.clr.offset(region1_coords[0])
+        chrom2_offset = self.clr.offset(region2_coords[0])
+        self.offsets[region1] = self.clr.offset(region1_coords) - chrom1_offset
+        self.offsets[region2] = self.clr.offset(region2_coords) - chrom2_offset
         matrix = self.clr.matrix(**self.cooler_opts).fetch(
             region1_coords, region2_coords
         )
+        if self.cooler_opts["sparse"]:
+            matrix = matrix.tocsr()
         if self.clr_weight_name:
             self._isnan1 = np.isnan(
                 self.clr.bins()[self.clr_weight_name]
                 .fetch(region1_coords)
-                .values
+                .to_numpy()
             )
             self._isnan2 = np.isnan(
                 self.clr.bins()[self.clr_weight_name]
                 .fetch(region2_coords)
-                .values
+                .to_numpy()
             )
         else:
             self._isnan1 = np.zeros_like(
-                self.clr.bins()["start"].fetch(region1_coords).values
+                self.clr.bins()["start"].fetch(region1_coords).to_numpy()
             ).astype(bool)
             self._isnan2 = np.zeros_like(
-                self.clr.bins()["start"].fetch(region2_coords).values
+                self.clr.bins()["start"].fetch(region2_coords).to_numpy()
             ).astype(bool)
-        if self.cooler_opts["sparse"]:
-            matrix = matrix.tocsr()
-        if self.min_diag is not None:
-            diags = np.arange(
-                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
-            )
-            self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
         return matrix
 
     def snip(self, matrix, region1, region2, tup):
@@ -458,43 +449,34 @@ def snip(self, matrix, region1, region2, tup):
         offset1 = self.offsets[region1]
         offset2 = self.offsets[region2]
         binsize = self.binsize
-        lo1, hi1 = (s1 // binsize) - offset1, (e1 // binsize) - offset1
-        lo2, hi2 = (s2 // binsize) - offset2, (e2 // binsize) - offset2
-        assert hi1 >= 0
-        assert hi2 >= 0
+        # bins relative to start of respective chromosomes
+        lo1, hi1 = s1 // binsize, e1 // binsize
+        lo2, hi2 = s2 // binsize, e2 // binsize
+        # calculate min diagonal of the snippet
+        min_diag_snip = lo2 - hi1 + 1
+        # bins relative to respective regions, i.e. matrix
+        lo1 -= offset1
+        hi1 -= offset1
+        lo2 -= offset2
+        hi2 -= offset2
 
         m, n = matrix.shape
         dm, dn = hi1 - lo1, hi2 - lo2
-        out_of_bounds = False
-        pad_left = pad_right = pad_bottom = pad_top = None
-        if lo1 < 0:
-            pad_bottom = -lo1
-            out_of_bounds = True
-        if lo2 < 0:
-            pad_left = -lo2
-            out_of_bounds = True
-        if hi1 > m:
-            pad_top = dm - (hi1 - m)
-            out_of_bounds = True
-        if hi2 > n:
-            pad_right = dn - (hi2 - n)
-            out_of_bounds = True
-
-        if out_of_bounds:
-            i0 = max(lo1, 0)
-            i1 = min(hi1, m)
-            j0 = max(lo2, 0)
-            j1 = min(hi2, n)
-            snippet = np.full((dm, dn), np.nan)
-        #             snippet[pad_bottom:pad_top,
-        #                     pad_left:pad_right] = matrix[i0:i1, j0:j1].toarray()
-        else:
-            snippet = matrix[lo1:hi1, lo2:hi2].toarray().astype("float")
-            snippet[self._isnan1[lo1:hi1], :] = np.nan
-            snippet[:, self._isnan2[lo2:hi2]] = np.nan
+        # if snippet is out of bounds, return "empty" snippet
+        if lo1 < 0 or lo2 < 0 or hi1 > m or hi2 > n:
+            return np.full((dm, dn), np.nan)
+
+        snippet = matrix[lo1:hi1, lo2:hi2].toarray().astype("float")
+        snippet[self._isnan1[lo1:hi1], :] = np.nan
+        snippet[:, self._isnan2[lo2:hi2]] = np.nan
+
         if self.min_diag is not None:
-            D = self.diag_indicators[region1][lo1:hi1, lo2:hi2] < self.min_diag
-            snippet[D] = np.nan
+            # fill in NaNs in diagonals below self.min_diag
+            for _diag, _diag_relative in zip(
+                range(min_diag_snip, self.min_diag),
+                range(-dm+1, dn),
+            ):
+                set_diag(snippet, np.nan, i=_diag_relative)
         return snippet
 
 
@@ -533,13 +515,12 @@ def __init__(
             interaction values, by default "balanced.avg"
         """
         self.clr = clr
-        self.expected = expected
+        self.expected_grp = expected.set_index("dist").groupby(["region1", "region2"])
         self.expected_value_col = expected_value_col
         self.view_df = view_df.set_index("name")
         self.binsize = self.clr.binsize
+        self.min_diag = min_diag
         self.offsets = {}
-        self.diag_indicators = {}
-        self.pad = True
         self.cooler_opts = {} if cooler_opts is None else cooler_opts
         self.cooler_opts.setdefault("sparse", True)
         if "balance" in self.cooler_opts:
@@ -554,7 +535,6 @@ def __init__(
                 self.clr_weight_name = self.cooler_opts["balance"]
         else:
             self.clr_weight_name = "weight"
-        self.min_diag = min_diag
 
     def select(self, region1, region2):
         """Select a portion of the cooler for snipping based on two regions in the view
@@ -580,12 +560,9 @@ def select(self, region1, region2):
             raise ValueError(
                 "ObsExpSnipper is implemented for cis contacts only."
             )
-        self.offsets[region1] = self.clr.offset(
-            region1_coords
-        ) - self.clr.offset(region1_coords[0])
-        self.offsets[region2] = self.clr.offset(
-            region2_coords
-        ) - self.clr.offset(region2_coords[0])
+        chrom_offset = self.clr.offset(region1_coords[0])
+        self.offsets[region1] = self.clr.offset(region1_coords) - chrom_offset
+        self.offsets[region2] = self.clr.offset(region2_coords) - chrom_offset
         matrix = self.clr.matrix(**self.cooler_opts).fetch(
             region1_coords, region2_coords
         )
@@ -595,30 +572,37 @@ def select(self, region1, region2):
             self._isnan1 = np.isnan(
                 self.clr.bins()[self.clr_weight_name]
                 .fetch(region1_coords)
-                .values
+                .to_numpy()
             )
             self._isnan2 = np.isnan(
                 self.clr.bins()[self.clr_weight_name]
                 .fetch(region2_coords)
-                .values
+                .to_numpy()
             )
         else:
             self._isnan1 = np.zeros_like(
-                self.clr.bins()["start"].fetch(region1_coords).values
+                self.clr.bins()["start"].fetch(region1_coords).to_numpy()
             ).astype(bool)
             self._isnan2 = np.zeros_like(
-                self.clr.bins()["start"].fetch(region2_coords).values
+                self.clr.bins()["start"].fetch(region2_coords).to_numpy()
             ).astype(bool)
-        self._expected = LazyToeplitz(
-            self.expected.groupby(["region1", "region2"])
-            .get_group((region1, region2))[self.expected_value_col]
-            .values
-        )
-        if self.min_diag is not None:
-            diags = np.arange(
-                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
+        # extract expected for the region from the expected_groupby, indexed by distance
+        _exp_diags = self.expected_grp.get_group((region1, region2))[self.expected_value_col]
+        if region1_coords == region2_coords:
+            # on-diagonal case
+            self._expected = LazyToeplitz(_exp_diags.to_numpy())
+        else:
+            # extract region extents for off-diagonal expected
+            lo1, hi1 = self.clr.extent(region1_coords)
+            lo2, hi2 = self.clr.extent(region2_coords)
+            # diagonal coordinates of the matrix relative to chrom
+            min_dist = lo2 - hi1
+            mid_dist = lo2 - lo1
+            max_dist = hi2 - lo1
+            self._expected = LazyToeplitz(
+                _exp_diags.loc[mid_dist:min_dist:-1].to_numpy(),
+                _exp_diags.loc[mid_dist:max_dist].to_numpy(),
             )
-            self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
         return matrix
 
     def snip(self, matrix, region1, region2, tup):
@@ -647,45 +631,35 @@ def snip(self, matrix, region1, region2, tup):
         offset1 = self.offsets[region1]
         offset2 = self.offsets[region2]
         binsize = self.binsize
-        lo1, hi1 = (s1 // binsize) - offset1, (e1 // binsize) - offset1
-        lo2, hi2 = (s2 // binsize) - offset2, (e2 // binsize) - offset2
-        assert hi1 >= 0
-        assert hi2 >= 0
+        # bins relative to start of respective chromosomes
+        lo1, hi1 = s1 // binsize, e1 // binsize
+        lo2, hi2 = s2 // binsize, e2 // binsize
+        # calculate min diagonal of the snippet
+        min_diag_snip = lo2 - hi1 + 1
+        # bins relative to respective regions (matrix)
+        lo1 -= offset1
+        hi1 -= offset1
+        lo2 -= offset2
+        hi2 -= offset2
 
         m, n = matrix.shape
         dm, dn = hi1 - lo1, hi2 - lo2
-        out_of_bounds = False
-        pad_left = pad_right = pad_bottom = pad_top = None
-        if lo1 < 0:
-            pad_bottom = -lo1
-            out_of_bounds = True
-        if lo2 < 0:
-            pad_left = -lo2
-            out_of_bounds = True
-        if hi1 > m:
-            pad_top = dm - (hi1 - m)
-            out_of_bounds = True
-        if hi2 > n:
-            pad_right = dn - (hi2 - n)
-            out_of_bounds = True
-
-        if out_of_bounds:
-            i0 = max(lo1, 0)
-            i1 = min(hi1, m)
-            j0 = max(lo2, 0)
-            j1 = min(hi2, n)
+        # if snippet is out of bounds, return "empty" snippet
+        if lo1 < 0 or lo2 < 0 or hi1 > m or hi2 > n:
             return np.full((dm, dn), np.nan)
-        #             snippet[pad_bottom:pad_top,
-        #                     pad_left:pad_right] = matrix[i0:i1, j0:j1].toarray()
-        else:
-            snippet = matrix[lo1:hi1, lo2:hi2].toarray().astype("float")
-            snippet[self._isnan1[lo1:hi1], :] = np.nan
-            snippet[:, self._isnan2[lo2:hi2]] = np.nan
+
+        snippet = matrix[lo1:hi1, lo2:hi2].toarray().astype("float")
+        snippet[self._isnan1[lo1:hi1], :] = np.nan
+        snippet[:, self._isnan2[lo2:hi2]] = np.nan
 
         e = self._expected[lo1:hi1, lo2:hi2]
         if self.min_diag is not None:
-            D = self.diag_indicators[region1][lo1:hi1, lo2:hi2] < self.min_diag
-            snippet[D] = np.nan
+            # fill in NaNs in diagonals below self.min_diag
+            for _diag, _diag_relative in zip(
+                range(min_diag_snip, self.min_diag),
+                range(-dm+1, dn)
+            ):
+                set_diag(snippet, np.nan, i=_diag_relative)
         return snippet / e
 
 
@@ -717,12 +691,11 @@ def __init__(
             interaction values, by default "balanced.avg"
         """
         self.clr = clr
-        self.expected = expected
+        self.expected_grp = expected.set_index("dist").groupby(["region1", "region2"])
         self.expected_value_col = expected_value_col
         self.view_df = view_df.set_index("name")
         self.binsize = self.clr.binsize
         self.offsets = {}
-        self.diag_indicators = {}
         self.min_diag = min_diag
 
     def select(self, region1, region2):
@@ -750,25 +723,26 @@ def select(self, region1, region2):
             raise ValueError(
                 "ObsExpSnipper is implemented for cis contacts only."
             )
-        self.offsets[region1] = self.clr.offset(
-            region1_coords
-        ) - self.clr.offset(region1_coords[0])
-        self.offsets[region2] = self.clr.offset(
-            region2_coords
-        ) - self.clr.offset(region2_coords[0])
-        self.m = np.diff(self.clr.extent(region1_coords))
-        self.n = np.diff(self.clr.extent(region2_coords))
-        self._expected = LazyToeplitz(
-            self.expected.groupby(["region1", "region2"])
-            .get_group((region1, region2))[self.expected_value_col]
-            .values
-        )
-        if self.min_diag is not None:
-            diags = np.arange(
-                np.diff(self.clr.extent(region1_coords)), dtype=np.int32
+        chrom_offset = self.clr.offset(region1_coords[0])
+        self.offsets[region1] = self.clr.offset(region1_coords) - chrom_offset
+        self.offsets[region2] = self.clr.offset(region2_coords) - chrom_offset
+        # extract expected for the region from the expected_groupby, indexed by distance
+        _exp_diags = self.expected_grp.get_group((region1, region2))[self.expected_value_col]
+        if region1_coords == region2_coords:
+            # on-diagonal case
+            return LazyToeplitz(_exp_diags.to_numpy())
+        else:
+            # extract region extents for off-diagonal expected
+            lo1, hi1 = self.clr.extent(region1_coords)
+            lo2, hi2 = self.clr.extent(region2_coords)
+            # diagonal coordinates of the matrix relative to chrom
+            min_dist = lo2 - hi1
+            mid_dist = lo2 - lo1
+            max_dist = hi2 - lo1
+            return LazyToeplitz(
+                _exp_diags.loc[mid_dist:min_dist:-1].to_numpy(),
+                _exp_diags.loc[mid_dist:max_dist].to_numpy(),
             )
-            self.diag_indicators[region1] = LazyToeplitz(-diags, diags)
-        return self._expected
 
     def snip(self, exp, region1, region2, tup):
         """Extract an expected snippet
@@ -796,19 +770,31 @@ def snip(self, exp, region1, region2, tup):
         offset1 = self.offsets[region1]
         offset2 = self.offsets[region2]
         binsize = self.binsize
-        lo1, hi1 = (s1 // binsize) - offset1, (e1 // binsize) - offset1
-        lo2, hi2 = (s2 // binsize) - offset2, (e2 // binsize) - offset2
-        assert hi1 >= 0
-        assert hi2 >= 0
+        # bins relative to start of respective chromosomes
+        lo1, hi1 = s1 // binsize, e1 // binsize
+        lo2, hi2 = s2 // binsize, e2 // binsize
+        # calculate min diagonal of the snippet
+        min_diag_snip = lo2 - hi1 + 1
+        # bins relative to respective regions, i.e. matrix
+        lo1 -= offset1
+        hi1 -= offset1
+        lo2 -= offset2
+        hi2 -= offset2
+
+        m, n = exp.shape
         dm, dn = hi1 - lo1, hi2 - lo2
 
-        if lo1 < 0 or lo2 < 0 or hi1 > self.m or hi2 > self.n:
+        if lo1 < 0 or lo2 < 0 or hi1 > m or hi2 > n:
             return np.full((dm, dn), np.nan)
 
         snippet = exp[lo1:hi1, lo2:hi2]
         if self.min_diag is not None:
-            D = self.diag_indicators[region1][lo1:hi1, lo2:hi2] < self.min_diag
-            snippet[D] = np.nan
+            # fill in NaNs in diagonals below self.min_diag
+            for _diag, _diag_relative in zip(
+                range(min_diag_snip, self.min_diag),
+                range(-dm+1, dn)
+            ):
+                set_diag(snippet, np.nan, i=_diag_relative)
         return snippet