Merge branch 'fix_spi_attrs' of https://github.com/Ouranosinc/xclim i…

…nto fix_spi_attrs

.readthedocs.yml

@@ -27,3 +27,11 @@ python:
       path: .
       extra_requirements:
         - dev
+
+search:
+  ranking:
+
+    notebooks/*: 2
+    api_indicators.html: 1
+    indices.html: -1
+    _modules/*: -3

CHANGES.rst

@@ -4,21 +4,32 @@ Changelog
 
 v0.47.0 (unreleased)
 --------------------
-Contributors to this version: Juliette Lavoie (:user:`juliettelavoie`), Pascal Bourgault (:user:`aulemahal`), Trevor James Smith (:user:`Zeitsperre`), Éric Dupuis (:user:`coxipi`)
+Contributors to this version: Juliette Lavoie (:user:`juliettelavoie`), Pascal Bourgault (:user:`aulemahal`), Trevor James Smith (:user:`Zeitsperre`), David Huard (:user:`huard`), Éric Dupuis (:user:`coxipi`).
+
+Announcements
+^^^^^^^^^^^^^
+* To circumvent issues stemming from changes to the frequency code convention in `pandas` v2.2, we have pinned `xarray` (< 2023.11.0) and `pandas` (< 2.2) for this release. This change will be reverted in `xclim` v0.48.0 to support the newer versions (`xarray>= 2023.11.0` and `pandas>= 2.2`).
+* `xclim` v0.47.0 will be the last release supporting Python3.8.
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-* New functions ``xclim.ensembles.robustness_fractions`` and ``xclim.ensembles.robustness_categories``. The former will replace ``xclim.ensembles.change_significance`` which is now deprecated and will be removed in xclim 0.49 (:pull:`1514`).
+* New functions ``xclim.ensembles.robustness_fractions`` and ``xclim.ensembles.robustness_categories``. The former will replace ``xclim.ensembles.change_significance`` which is now deprecated and will be removed in xclim 0.49. (:pull:`1514`).
+* Add indicator ID to searched terms in the indicator search documentation page. (:issue:`1525`, :pull:`1528`).
 
 Bug fixes
 ^^^^^^^^^
-* Fixed a bug with ``n_escore=-1`` in ``xclim.sdba.adjustment.NpdfTransform`` (:issue:`1515`, :pull:`1516`).
-* Fix wrong attributes in `xclim.indices.standardized_precipitation_index``, `xclim.indices.standardized_precipitation_evapotranspiration_index`` (:issue:`1537`, :pull:`1538`).
+* Fixed a bug with ``n_escore=-1`` in ``xclim.sdba.adjustment.NpdfTransform``. (:issue:`1515`, :pull:`1516`).
+* In the documentation, fixed the tooltips in the indicator search results. (:issue:`1524`, :pull:`1527`).
+* If chunked inputs are passed to indicators ``mean_radiant_temperature`` and ``potential_evapotranspiration``, sub-calculations of the solar angle will also use the same chunks, instead of a single one of the same size as the data. (:issue:`1536`, :pull:`1542`).
+* Fix wrong attributes in ``xclim.indices.standardized_precipitation_index``, ``xclim.indices.standardized_precipitation_evapotranspiration_index``. (:issue:`1537`, :pull:`1538`).
 
 Internal changes
 ^^^^^^^^^^^^^^^^
 * Pinned `cf-xarray` below v0.8.5 in Python3.8 installation to further extend legacy support. (:pull:`1519`).
 * `pip check` in conda builds in GitHub workflows have been temporarily set to always pass. (:pull:`1531`).
+* Configure RtD search rankings to emphasize notebooks and indicators over indices and raw source code. (:pull:`1526`).
+* Addressed around 100 very basic `mypy` typing errors and call signature errors. (:pull:`1532`).
+* Use the intermediate step ``_cumsum_reset_on_zero`` instead of ``rle`` which is sufficient in ``_boundary_run``. (:issue:`1405`, :pull:`1530`).
 
 v0.46.0 (2023-10-24)
 --------------------

docs/_static/indsearch.js

@@ -3,7 +3,7 @@ let indicators = [];
 
 /* MiniSearch object defining search mechanism */
 let miniSearch = new MiniSearch({
-  fields: ['title', 'abstract', 'variables', 'keywords'], // fields to index for full-text search
+  fields: ['title', 'abstract', 'variables', 'keywords', 'id'], // fields to index for full-text search
   storeFields: ['title', 'abstract', 'vars', 'realm', 'module', 'name', 'keywords'], // fields to return with search results
   searchOptions: {
     boost: {'title': 3, 'variables': 2},
@@ -30,15 +30,18 @@ fetch('indicators.json')
   });
 
 
-// Populate list of variables
-//function getVariables() {
-//    fetch('variables.json')
-//        .then((res) => {
-//            return res.json();
-//        })
-//}
-//const variables = getVariables();
-
+function escapeHTML(str){
+    /* Escape HTML characters in a string. */
+    var map =
+    {
+        '&': '&',
+        '<': '&lt;',
+        '>': '&gt;',
+        '"': '&quot;',
+        "'": '&#039;'
+    };
+    return str.replace(/[&<>"']/g, function(m) {return map[m];});
+}
 
 function makeKeywordLabel(ind) {
     /* Print list of keywords only if there is at least one. */
@@ -55,7 +58,10 @@ function makeKeywordLabel(ind) {
 function makeVariableList(ind) {
     /* Print list of variables and include mouse-hover tooltip with variable description. */
     return Object.entries(ind.vars).map((kv) => {
-        const tooltip = `<button class="indVarname" title="${kv[1]}" alt="${kv[1]}">${kv[0]}</button>`;
+        /* kv[0] is the variable name, kv[1] is the variable description. */
+        /* Convert kv[1] to a string literal */
+        const text = escapeHTML(kv[1]);
+        const tooltip = `<button class="indVarname" title="${text}" alt="${text}">${kv[0]}</button>`;
         return tooltip
     }).join('');
 }
@@ -66,13 +72,13 @@ function indTemplate(ind) {
   return `
     <div class="indElem" id="${ind.id}">
       <div class="indHeader">
-        <b class="indTitle">${ind.title}</b>
+        <b class="indTitle">${escapeHTML(ind.title)}</b>
         <a class="reference_internal indName" href="api_indicators.html#xclim.indicators.${ind.module}.${ind.name}" title="${ind.name}">
           <code>${ind.module}.${ind.name}</code>
         </a>
       </div>
       <div class="indVars">Uses: ${varlist}</div>
-      <div class="indDesc"><p>${ind.abstract}</p></div>
+      <div class="indDesc"><p>${escapeHTML(ind.abstract)}</p></div>
       ${makeKeywordLabel(ind)}
       <div class="indID">Yaml ID: <code>${ind.id}</code></div>
     </div>

environment.yml

@@ -16,14 +16,14 @@ dependencies:
     - lmoments3
     - numba
     - numpy >=1.16
-    - pandas >=0.23
+    - pandas >=0.23,<2.2
     - pint >=0.9
     - poppler >=0.67
     - pyyaml
     - scikit-learn >=0.21.3
     - scipy >=1.2
     - statsmodels
-    - xarray >=2022.06.0
+    - xarray >=2022.06.0,<2023.11.0
     # Extras
     - eofs
     - flox

pyproject.toml

@@ -45,13 +45,13 @@ dependencies = [
   "numba",
   "numpy>=1.16",
   "pandas>=0.23,<2.0; python_version == '3.8'",
-  "pandas>=0.23; python_version >= '3.9'",
+  "pandas>=0.23,<2.2; python_version >= '3.9'",
   "pint>=0.10",
   "pyyaml",
   "scikit-learn>=0.21.3",
   "scipy>=1.2",
   "statsmodels",
-  "xarray>=2022.06.0"
+  "xarray>=2022.06.0,<2023.11.0"
 ]
 
 [project.optional-dependencies]
@@ -183,13 +183,16 @@ module = [
   "clisops.core.subset.*",
   "dask.*",
   "lmoments3.*",
+  "matplotlib.*",
   "numba.*",
   "numpy.*",
   "pandas.*",
   "pint.*",
+  "SBCK.*",
   "scipy.*",
   "sklearn.cluster.*",
-  "xarray.*"
+  "xarray.*",
+  "yaml.*"
 ]
 ignore_missing_imports = true
 

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.46.4-beta
+current_version = 0.46.10-beta
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+).(?P<patch>\d+)(\-(?P<release>[a-z]+))?

tests/test_ensembles.py

@@ -743,8 +743,9 @@ def test_robustness_fractions_empty():
 
 
 def test_robustness_categories():
-    changed = xr.DataArray([0.5, 0.8, 1, 1])
-    agree = xr.DataArray([1, 0.5, 0.5, 1])
+    lat = xr.DataArray([1, 2, 3, 4], dims=("lat",), attrs={"axis": "Y"}, name="lat")
+    changed = xr.DataArray([0.5, 0.8, 1, 1], dims=("lat",), coords={"lat": lat})
+    agree = xr.DataArray([1, 0.5, 0.5, 1], dims=("lat",), coords={"lat": lat})
 
     categories = ensembles.robustness_categories(changed, agree)
     np.testing.assert_array_equal(categories, [2, 3, 3, 1])
@@ -753,6 +754,7 @@ def test_robustness_categories():
         categories.flag_meanings
         == "robust_signal no_change_or_no_signal conflicting_signal"
     )
+    assert categories.lat.attrs["axis"] == "Y"
 
 
 def test_robustness_coefficient():

tests/test_utils.py

@@ -8,11 +8,13 @@
 import xarray as xr
 
 from xclim.core.utils import (
+    _chunk_like,
     ensure_chunk_size,
     nan_calc_percentiles,
     walk_map,
     wrapped_partial,
 )
+from xclim.testing.helpers import test_timeseries as _test_timeseries
 
 
 def test_walk_map():
@@ -110,3 +112,18 @@ def test_calc_perc_partial_nan(self):
         # The expected is from R `quantile(arr, 0.5, type=8, na.rm = TRUE)`
         # Note that scipy mquantiles would give a different result here
         assert res[()] == 42.0
+
+
+def test_chunk_like():
+    da = _test_timeseries(
+        np.zeros(
+            100,
+        ),
+        "tas",
+    )
+    da = xr.concat([da] * 10, xr.DataArray(np.arange(10), dims=("lat",), name="lat"))
+
+    assert isinstance(da.lat.variable, xr.core.variable.IndexVariable)
+    t, la = _chunk_like(da.time, da.lat, chunks={"time": 10, "lat": 1})
+    assert t.chunks[0] == tuple([10] * 10)
+    assert la.chunks[0] == tuple([1] * 10)

xclim/__init__.py

@@ -15,7 +15,7 @@
 
 __author__ = """Travis Logan"""
 __email__ = "[email protected]"
-__version__ = "0.46.4-beta"
+__version__ = "0.46.10-beta"
 
 
 _module_data = _files("xclim.data")

xclim/analog.py

@@ -5,7 +5,7 @@
 # Code adapted from flyingpigeon.dissimilarity, Nov 2020.
 from __future__ import annotations
 
-from typing import Sequence
+from typing import Any, Sequence
 
 import numpy as np
 import pandas as pd
@@ -16,7 +16,7 @@
 from scipy import spatial
 from scipy.spatial import cKDTree as KDTree
 
-metrics = {}
+metrics: dict[str, Any] = {}
 
 
 def spatial_analogs(
@@ -61,7 +61,7 @@ def spatial_analogs(
         raise RuntimeError(f"Spatial analogue method ({method}) requires scipy>=1.6.0.")
 
     # Create the target DataArray:
-    target = target.to_array("_indices", "target")
+    target_array = target.to_array("_indices", "target")
 
     # Create the target DataArray
     # drop any (sub-)index along "dist_dim" that could conflict with target, and rename it.
@@ -86,13 +86,13 @@ def spatial_analogs(
 
     if candidates.chunks is not None:
         candidates = candidates.chunk({"_indices": -1})
-    if target.chunks is not None:
-        target = target.chunk({"_indices": -1})
+    if target_array.chunks is not None:
+        target_array = target_array.chunk({"_indices": -1})
 
     # Compute dissimilarity
     diss = xr.apply_ufunc(
         metric_func,
-        target,
+        target_array,
         candidates,
         input_core_dims=[(dist_dim, "_indices"), ("_dist_dim", "_indices")],
         output_core_dims=[()],
@@ -104,7 +104,7 @@ def spatial_analogs(
     diss.name = "dissimilarity"
     diss.attrs.update(
         long_name=f"Dissimilarity between target and candidates, using metric {method}.",
-        indices=",".join(target._indices.values),  # noqa
+        indices=",".join(target_array._indices.values),  # noqa
         metric=method,
     )