Change df_to_inventory to use a local copy of NRL if needed

CHANGELOG.txt

@@ -1,3 +1,8 @@
+master
+  - obsplus.utils.stations
+    * Fixed df_to_inventory to use a local copy of the NRL for compatibility
+      with ObsPy and NRLv2 (Note that NRLv1 is no longer accessible)
+
 obsplus 0.2.5
   - obsplus
     * Modernized packaging, including src file and pyrpoject.toml (#259)

src/obsplus/constants.py

@@ -1,4 +1,5 @@
 """Constants used throughout obsplus."""
+
 from collections import OrderedDict
 from os import cpu_count
 from pathlib import Path

src/obsplus/exceptions.py

@@ -1,6 +1,5 @@
 """A collection of ObsPlus Exceptions and Warnings."""
 
-
 # --- Exceptions
 
 

src/obsplus/interfaces.py

@@ -4,6 +4,7 @@
 Note: These are used instead of the ones in obspy.clients.base so the subclass
 hooks can be used.
 """
+
 from abc import abstractmethod
 from typing_extensions import Protocol, runtime_checkable
 

src/obsplus/utils/stations.py

@@ -5,7 +5,7 @@
 import warnings
 from functools import singledispatch, lru_cache
 from pathlib import Path
-from typing import Optional
+from typing import Optional, Union
 
 import numpy as np
 import obspy
@@ -88,8 +88,9 @@ class _InventoryConstructor:
         channel=("channel", "location", "start_date", "end_date"),
     )
 
-    def __init__(self, station_client=None):
+    def __init__(self, station_client=None, nrl_path=None):
         self._client = station_client
+        self._nrl_path = nrl_path
 
     def _groupby_if_exists(self, df, level):
         """Groupby columns if they exist on dataframe, else return empty."""
@@ -136,13 +137,12 @@ def _get_kwargs(self, series, key_mapping):
 
         return out
 
-    @property
     @lru_cache()
-    def nrl_client(self):
+    def nrl_client(self, path):
         """Initiate a nominal response library object."""
         from obspy.clients.nrl import NRL
 
-        return NRL()
+        return NRL(str(path))
 
     @property
     @lru_cache()
@@ -159,8 +159,8 @@ def station_client(self):
         return client
 
     @lru_cache()
-    def get_nrl_response(self, datalogger_keys, sensor_keys):
-        nrl = self.nrl_client
+    def get_nrl_response(self, path, datalogger_keys, sensor_keys):
+        nrl = self.nrl_client(path)
         kwargs = dict(datalogger_keys=datalogger_keys, sensor_keys=sensor_keys)
         return nrl.get_response(**kwargs)
 
@@ -182,8 +182,12 @@ def _update_nrl_response(self, response, df):
         # df doesn't have needed columns, just exit
         logger_keys, sensor_keys = df["datalogger_keys"], df["sensor_keys"]
         valid = (~logger_keys.isna()) & (~sensor_keys.isna())
+        if valid.any() and self._nrl_path is None:
+            raise AttributeError(
+                "nrl_path must be specified if using NRL to get instrument responses"
+            )
         response[valid] = [
-            self.get_nrl_response(tuple(x), tuple(y))
+            self.get_nrl_response(self._nrl_path, tuple(x), tuple(y))
             for x, y in zip(logger_keys[valid], sensor_keys[valid])
         ]
 
@@ -319,7 +323,9 @@ def _make_inventory(self, df: pd.DataFrame):
 
 @compose_docstring(station_columns=station_col_str)
 def df_to_inventory(
-    df: pd.DataFrame, client: Optional[StationClient] = None
+    df: pd.DataFrame,
+    client: Optional[StationClient] = None,
+    nrl_path: Optional[Union[Path, str]] = None,
 ) -> obspy.Inventory:
     """
     Create an inventory from a dataframe.
@@ -334,6 +340,10 @@ def df_to_inventory(
     client
         Any client with a `get_stations` method. Only used if the dataframe
         contains special columns for retrieving channel responses.
+    nrl_path
+        The path to a local copy of the Nominal Response Library. Only used
+        if the dataframe contains special columns for retrieving channel
+        responses.
 
     Notes
     -----
@@ -344,13 +354,16 @@ def df_to_inventory(
     If the dataframe has columns named "sensor_keys" and "datalogger_keys"
     these will indicate the response information should be fetched using
     ObsPy's NRL client. Each of these columns should either contain lists
-    or josn-loadable strings.
+    or json-loadable strings.
     For example, to specify sensor keys:
     ["Nanometrics", "Trillium 120 Horizon"]
     or
     '["Nanometrics", "Trillium 120 Horizon"]'
     are both valid.
 
+    Note that the capability of ObsPy's NRL client to parse the online NRL has
+    been deprecated and it is now necessary to download and use a local copy.
+
     2. Using a station client:
     If the dataframe contains a column get_stations_kwargs it indicates that
     either a client was passed as the client argument or the fdsn IRIS client
@@ -375,7 +388,7 @@ def df_to_inventory(
     - If both NRL and client methods are indicated by column contents an
       AmbiguousResponseError will be raised.
     """
-    inv_constructor = _InventoryConstructor(station_client=client)
+    inv_constructor = _InventoryConstructor(station_client=client, nrl_path=nrl_path)
     return inv_constructor(df)
 
 

src/obsplus/version.py

@@ -1,4 +1,5 @@
 """Module for reporting the package version."""
+
 from contextlib import suppress
 from importlib.metadata import PackageNotFoundError, version
 

tests/conftest.py

@@ -131,6 +131,8 @@ def internet_available():
     """Test if internet resources are available."""
     import socket
 
+    # TODO: This isn't a consistent way to determine if there's internet, especially
+    #  behind a corporate firewall
     address = "8.8.8.8"
     port = 53
     try:
@@ -164,6 +166,12 @@ def load_and_update_dataset(name):
 has_internet = internet_available()
 
 
+@pytest.fixture(scope="session")
+def data_path():
+    """For scenarios when you really just need a path to test data"""
+    return TEST_DATA_PATH
+
+
 # -------------------- collection of test cases
 
 

tests/test_data/mini_nrl/datalogger/Nanometrics/Centaur.txt

@@ -0,0 +1,21 @@
+[Main]
+question = "What is the full scale voltage?"
+
+[4Vpp]
+path = "Centaur_FV4Vpp.txt"
+
+[40Vpp]
+path = "Centaur_FV40Vpp.txt"
+
+[2Vpp]
+path = "Centaur_FV2Vpp.txt"
+
+[20Vpp]
+path = "Centaur_FV20Vpp.txt"
+
+[1Vpp]
+path = "Centaur_FV1Vpp.txt"
+
+[10Vpp]
+path = "Centaur_FV10Vpp.txt"
+

tests/test_data/mini_nrl/datalogger/Nanometrics/Centaur_FV1Vpp.txt

@@ -0,0 +1,66 @@
+[Main]
+question = "What is the final sample rate?"
+
+[80 Hz]
+path = "Centaur_FV1Vpp_FR80.txt"
+
+
+[5 Hz]
+path = "Centaur_FV1Vpp_FR5.txt"
+
+
+[50 Hz]
+path = "Centaur_FV1Vpp_FR50.txt"
+
+
+[500 Hz]
+path = "Centaur_FV1Vpp_FR500.txt"
+
+
+[5000 Hz]
+path = "Centaur_FV1Vpp_FR5000.txt"
+
+
+[40 Hz]
+path = "Centaur_FV1Vpp_FR40.txt"
+
+
+[2 Hz]
+path = "Centaur_FV1Vpp_FR2.txt"
+
+
+[250 Hz]
+path = "Centaur_FV1Vpp_FR250.txt"
+
+
+[20 Hz]
+path = "Centaur_FV1Vpp_FR20.txt"
+
+
+[200 Hz]
+path = "Centaur_FV1Vpp_FR200.txt"
+
+
+[2000 Hz]
+path = "Centaur_FV1Vpp_FR2000.txt"
+
+
+[1 Hz]
+path = "Centaur_FV1Vpp_FR1.txt"
+
+
+[125 Hz]
+path = "Centaur_FV1Vpp_FR125.txt"
+
+
+[10 Hz]
+path = "Centaur_FV1Vpp_FR10.txt"
+
+
+[100 Hz]
+path = "Centaur_FV1Vpp_FR100.txt"
+
+
+[1000 Hz]
+path = "Centaur_FV1Vpp_FR1000.txt"
+

tests/test_data/mini_nrl/datalogger/Nanometrics/Centaur_FV1Vpp_FR40.txt

@@ -0,0 +1,10 @@
+[Main]
+question = "What is the DC removal/low pass filter setting?"
+
+[Off]
+path = "Centaur_FV1Vpp_FR40_DFOff.txt"
+
+
+[0.001]
+path = "Centaur_FV1Vpp_FR40_DF0.001.txt"
+

tests/test_data/mini_nrl/datalogger/Nanometrics/Centaur_FV1Vpp_FR40_DFOff.txt

@@ -0,0 +1,12 @@
+[Main]
+question = "What is the final filter phase?"
+
+[Minimum]
+description = "Nanometrics; Centaur; Full-Scale_Voltage 1Vpp; Final_Sample_Rate 40 Hz; DC_Filter Off; Final_Filter_Phase Minimum"
+xml = "Centaur_FV1Vpp_FR40_DFOff_FPMinimum.xml"
+
+
+[Linear]
+description = "Nanometrics; Centaur; Full-Scale_Voltage 1Vpp; Final_Sample_Rate 40 Hz; DC_Filter Off; Final_Filter_Phase Linear"
+xml = "Centaur_FV1Vpp_FR40_DFOff_FPLinear.xml"
+