Merge pull request #169 from OMS-NetZero/purge_logger

remove logger warnings and debugs

CHANGELOG.rst

@@ -1,6 +1,11 @@
 Changelog
 ---------
 
+v2.2.2
+------
+
+(`#169 <https://github.com/OMS-NetZero/FAIR/pull/169>`_) Removed logging messages which were too annoying and slowed down overrides in all but default cases (`#162 <https://github.com/OMS-NetZero/FAIR/issues/162>`_)
+
 v2.2.1
 ------
 

src/fair/io/fill_from.py

@@ -1,7 +1,6 @@
 """Methods for filling data from scenario files."""
 
 import copy
-import logging
 
 import numpy as np
 import pandas as pd
@@ -26,8 +25,6 @@
     time_convert,
 )
 
-logger = logging.getLogger(__name__)
-
 
 def _check_csv(df, runmode):
     # check our three metadata columns are present
@@ -70,23 +67,11 @@ def _check_csv(df, runmode):
     return times
 
 
-def _bounds_warning(firstlast, runmode, filetime, problemtime):
-    # Don't raise error if time is out of range because we can still fill in emissions
-    # by directly modifying attributes, but user might have made a mistake so warn
-    earlierlater = {"first": "later", "last": "earlier"}
-    return logger.warning(
-        f"The {firstlast} time in the {runmode} file ({filetime}) is "
-        f"{earlierlater[firstlast]} than the {firstlast} time in the problem "
-        f"definition ({problemtime})."
-    )
-
-
 def _parse_unit(unit, specie, is_ghg):
     try:
         prefix = unit.split()[0]
         compound = unit.split()[1].split("/")[0]
         time = unit.split()[1].split("/")[1]
-        logger.debug(f"prefix={prefix}, compound={compound}, time={time}")
     except IndexError:
         raise UnitParseError(
             "Units must be given in the format MASS SPECIE/TIME (with a whitespace "
@@ -108,12 +93,6 @@ def _parse_unit(unit, specie, is_ghg):
     # compound may be novel if it is user defined, but we can't convert it if so. In
     # which case add to our desired unit lists to prevent later errors.
     if compound not in compound_convert:
-        logger.warning(
-            f"{compound} is not in fair's default list of species masses for "
-            f"{specie}, so I can't convert it. For my non-native species, greenhouse "
-            "gas emissions are reported in kt/yr, short-lived forcer emissions in "
-            "Mt/yr, greenhouse gas concentrations in ppt, and forcings in W/m2."
-        )
         if is_ghg:
             desired_emissions_units[specie] = f"kt {compound}/yr"
             desired_concentration_units[specie] = "ppt"
@@ -145,11 +124,6 @@ def _concentration_unit_convert(concentration, unit, specie):
             f"values, which are {list(mixing_ratio_convert.keys())}."
         )
     if specie not in desired_concentration_units:
-        logger.warning(
-            f"{specie} is not in the default list of greenhouse gases known to fair, "
-            "so I'm going to convert concentrations to ppt and report back-calculated "
-            "emissions in kt/yr."
-        )
         desired_concentration_units[specie] = "ppt"
     concentration = concentration * (
         mixing_ratio_convert[unit][desired_concentration_units[specie]]
@@ -201,10 +175,6 @@ def fill_from_csv(
             df = pd.read_csv(mode_options[mode]["file"])
             df.columns = df.columns.str.lower()
             times = _check_csv(df, runmode=mode)  # list of strings
-            if float(times[0]) > mode_options[mode]["time"][0]:
-                _bounds_warning("first", mode, times[0], mode_options[mode]["time"][0])
-            if float(times[-1]) < self.timepoints[-1]:
-                _bounds_warning("last", mode, times[-1], mode_options[mode]["time"][-1])
             times_array = np.array(times, dtype=float)
 
             for scenario in self.scenarios:
@@ -218,17 +188,8 @@ def fill_from_csv(
                             times[0] : times[-1],
                         ].values
 
-                        # warn if data missing; it might be an error by the user, but
-                        # it's not fatal; we can fill in later
-                        if data_in.shape[0] == 0:
-                            logger.warning(
-                                f"I can't find a value for scenario='{scenario}', "
-                                f"variable='{specie}', region='World' in "
-                                f"{mode_options[mode]['file']} file."
-                            )
-                            continue
-                        # duplicates are ambigious however, and are an error
-                        elif data_in.shape[0] > 1:
+                        # duplicates are ambigious and are an error
+                        if data_in.shape[0] > 1:
                             raise DuplicateScenarioError(
                                 f"In {mode_options[mode]['file']} there are duplicate "
                                 f"rows for variable='{specie}, scenario='{scenario}'."

src/fair/io/param_sets.py

@@ -1,14 +1,9 @@
 """Methods for filling species and climate config parameters in."""
 
-import logging
-
 import pandas as pd
 
 from ..interface import fill
 
-logger = logging.getLogger(__name__)
-
-
 energy_balance_parameters = [
     "gamma_autocorrelation",
     "ocean_heat_capacity",
@@ -47,17 +42,7 @@ def override_defaults(self, filename):
     """
     df_configs = pd.read_csv(filename, index_col=0)
     for config in self.configs:
-        logger.debug("Checking for missing config label")
-        # warn if config is not present in file; it might be an error by the user, but
-        # its not fatal; it can still be filled in before calling run()
-        if config not in df_configs.index:
-            logger.warning(
-                f"I can't find a config with label '{config}' in the supplied file "
-                f"{filename}."
-            )
-            continue
         for col in df_configs.columns:
-            logger.debug("Checking whether this is an array")
             # should really do some error checking here; hopefully python's default
             # errors will be obvious enough if a user made a mistake
             if len(col.split("[")) > 1:
@@ -68,10 +53,8 @@ def override_defaults(self, filename):
                 param_index = None
 
             if param_name in energy_balance_parameters:
-                logger.debug(f"Found climate_config parameter {param_name}")
                 # error checking required?
                 if param_index is not None:
-                    logger.debug(f"Filling layer {param_index}")
                     fill(
                         self.climate_configs[param_name],
                         df_configs.loc[config, col],
@@ -86,16 +69,10 @@ def override_defaults(self, filename):
                     )
 
             else:
-                logger.debug(f"Found species_config parameter {param_name}")
                 # error checking required?
                 if param_index is not None:
                     if param_index not in self.species:
-                        logger.warning(
-                            f"{param_index} is not a specie defined in this `fair` "
-                            f"instance for column name {col} in {filename}."
-                        )
                         continue
-                    logger.debug(f"Filling specie {param_index}")
                     fill(
                         self.species_configs[param_name],
                         df_configs.loc[config, col],

tests/unit_tests/io/fill_from_test.py

@@ -1,6 +1,5 @@
 """Module for testing fill_from functions."""
 
-import logging
 import os
 
 import numpy as np
@@ -91,20 +90,6 @@ def test__check_csv():
         )
 
 
-def test__parse_unit(caplog):
-    caplog.set_level(logging.DEBUG)
-    f = minimal_problem_def()
-
-    with pytest.raises(UnitParseError):
-        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-unit.csv"))
-
-    with pytest.raises(UnitParseError):
-        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-prefix.csv"))
-
-    with pytest.raises(UnitParseError):
-        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-time.csv"))
-
-
 def test__non_default_specie(caplog):
     f = FAIR()
     species = ["HFC-152", "Hydrogen"]
@@ -127,12 +112,22 @@ def test__non_default_specie(caplog):
     f.define_configs(["UKESM1-0-LL"])
     f.allocate()
     f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "new-specie.csv"))
-    assert "HFC152 is not in fair's default list" in caplog.text
-    assert "H2 is not in fair's default list" in caplog.text
 
 
-def test__concentration_unit_convert(caplog):
-    caplog.set_level(logging.DEBUG)
+def test__parse_unit():
+    f = minimal_problem_def()
+
+    with pytest.raises(UnitParseError):
+        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-unit.csv"))
+
+    with pytest.raises(UnitParseError):
+        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-prefix.csv"))
+
+    with pytest.raises(UnitParseError):
+        f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bad-time.csv"))
+
+
+def test__concentration_unit_convert():
     f = FAIR()
     species = ["CO2"]
     properties = {}
@@ -169,30 +164,10 @@ def test__concentration_unit_convert(caplog):
     f.fill_from_csv(
         concentration_file=os.path.join(TEST_DATA_PATH, "new-concentration-specie.csv")
     )
-    assert "PF3 is not in the default list of greenhouse gases " in caplog.text
-
-
-def test__bounds_warning(caplog):
-    caplog.set_level(logging.DEBUG)
-    f = minimal_problem_def()
-    f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "bounds-early.csv"))
-    assert ("The first time in the emissions file " in caplog.text) & (
-        "is later than the first time in the problem definition" in caplog.text
-    )
 
 
 # this one unfinished
-def test_fill_from_csv(caplog):
-    caplog.set_level(logging.DEBUG)
-    f = minimal_problem_def()
-    f.fill_from_csv(
-        emissions_file=os.path.join(TEST_DATA_PATH, "minimal-emissions.csv")
-    )
-    assert (
-        "The last time in the emissions file (1752) is earlier than the last time "
-        "in the problem definition (1752.5)" in caplog.text
-    )
-
+def test_fill_from_csv():
     f = minimal_problem_def(input_mode="concentration")
     f.fill_from_csv(
         concentration_file=os.path.join(TEST_DATA_PATH, "minimal-concentration.csv")
@@ -201,13 +176,6 @@ def test_fill_from_csv(caplog):
     f = minimal_problem_def(input_mode="forcing", species=["Solar", "Volcanic"])
     f.fill_from_csv(forcing_file=os.path.join(TEST_DATA_PATH, "minimal-forcing.csv"))
 
-    f = minimal_problem_def()
-    f.fill_from_csv(emissions_file=os.path.join(TEST_DATA_PATH, "new-specie.csv"))
-    assert (
-        "I can't find a value for scenario='test', variable='CO2', region='World' in"
-        in caplog.text
-    )
-
     f = minimal_problem_def()
     f.fill_from_csv(
         emissions_file=os.path.join(TEST_DATA_PATH, "minimal-emissions.csv")

tests/unit_tests/io/param_sets_test.py

@@ -1,8 +1,9 @@
 """Module for testing fill_from functions."""
 
-import logging
 import os
 
+import pytest
+
 from fair import FAIR
 from fair.io import read_properties
 
@@ -33,21 +34,19 @@ def minimal_problem_def(configs=["one", "two", "three"]):
     return fair_obj
 
 
-def test_override_defaults(caplog):
-    caplog.set_level(logging.DEBUG)
+def test_override_defaults():
     f = minimal_problem_def()
     f.fill_from_csv(
         emissions_file=os.path.join(EMISSIONS_PATH, "minimal-emissions.csv")
     )
     f.fill_species_configs()
     f.override_defaults(PARAMS_FILE)
 
+    # "four" is not in the configs file, so should raise an error
     f = minimal_problem_def(configs=["four"])
     f.fill_from_csv(
         emissions_file=os.path.join(EMISSIONS_PATH, "minimal-emissions.csv")
     )
     f.fill_species_configs()
-    f.override_defaults(PARAMS_FILE)
-    assert (
-        "I can't find a config with label 'four' in the supplied file " in caplog.text
-    )
+    with pytest.raises(KeyError):
+        f.override_defaults(PARAMS_FILE)