Fixed usage of statistics=std_dev option in multi-model statistics preprocessors

doc/conf.py

@@ -424,7 +424,7 @@
     'numpy': ('https://numpy.org/doc/stable/', None),
     'pyesgf': ('https://esgf-pyclient.readthedocs.io/en/latest/', None),
     'python': ('https://docs.python.org/3/', None),
-    'scipy': ('https://docs.scipy.org/doc/scipy/reference/', None),
+    'scipy': ('https://scipy.github.io/devdocs/', None),
 }
 
 # -- Custom Document processing ----------------------------------------------

doc/recipe/preprocessor.rst

@@ -936,7 +936,7 @@ observational data, these biases have a significantly lower statistical impact
 when using a multi-model ensemble. ESMValTool has the capability of computing a
 number of multi-model statistical measures: using the preprocessor module
 ``multi_model_statistics`` will enable the user to ask for either a multi-model
-``mean``, ``median``, ``max``, ``min``, ``std``, and / or ``pXX.YY`` with a set
+``mean``, ``median``, ``max``, ``min``, ``std_dev``, and / or ``pXX.YY`` with a set
 of argument parameters passed to ``multi_model_statistics``. Percentiles can be
 specified like ``p1.5`` or ``p95``. The decimal point will be replaced by a dash
 in the output file.

esmvalcore/_recipe_checks.py

@@ -13,6 +13,7 @@
 from ._data_finder import get_start_end_year
 from .exceptions import InputFilesNotFound, RecipeError
 from .preprocessor import TIME_PREPROCESSORS, PreprocessingTask
+from .preprocessor._multimodel import STATISTIC_MAPPING
 
 logger = logging.getLogger(__name__)
 
@@ -221,7 +222,7 @@ def extract_shape(settings):
 
 def _verify_statistics(statistics, step):
     """Raise error if multi-model statistics cannot be verified."""
-    valid_names = ["mean", "median", "std", "min", "max"]
+    valid_names = ['std'] + list(STATISTIC_MAPPING.keys())
     valid_patterns = [r"^(p\d{1,2})(\.\d*)?$"]
 
     for statistic in statistics:

tests/integration/test_recipe_checks.py

@@ -282,15 +282,11 @@ def test_invalid_multi_model_settings():
 
 
 def test_invalid_multi_model_statistics():
-    with pytest.raises(RecipeError) as rec_err:
+    msg = (r"Invalid value encountered for `statistic` in preprocessor "
+           r"multi_model_statistics. Valid values are .* Got 'wrong'.")
+    with pytest.raises(RecipeError, match=msg):
         check._verify_statistics(
             INVALID_MM_SETTINGS['statistics'], 'multi_model_statistics')
-    assert str(rec_err.value) == (
-        "Invalid value encountered for `statistic` in preprocessor "
-        "multi_model_statistics. Valid values are "
-        "['mean', 'median', 'std', 'min', 'max'] "
-        "or patterns matching ['^(p\\\\d{1,2})(\\\\.\\\\d*)?$']. "
-        "Got 'wrong'.")
 
 
 def test_invalid_multi_model_span():
@@ -323,11 +319,7 @@ def test_invalid_multi_model_keep_input():
 
 
 def test_invalid_ensemble_statistics():
-    with pytest.raises(RecipeError) as rec_err:
+    msg = (r"Invalid value encountered for `statistic` in preprocessor "
+           r"ensemble_statistics. Valid values are .* Got 'wrong'.")
+    with pytest.raises(RecipeError, match=msg):
         check._verify_statistics(['wrong'], 'ensemble_statistics')
-    assert str(rec_err.value) == (
-        "Invalid value encountered for `statistic` in preprocessor "
-        "ensemble_statistics. Valid values are "
-        "['mean', 'median', 'std', 'min', 'max'] "
-        "or patterns matching ['^(p\\\\d{1,2})(\\\\.\\\\d*)?$']. "
-        "Got 'wrong'.")