def test_n_combinations():
coll = [1, 2, 3, 4]
combs = df_metrics.n_combinations(coll,
n=2,
must_include=[1],
permutations=False)
assert combs == [(1, 2), (1, 3), (1, 4)]
coll = [1, 2, 3, 4]
combs = df_metrics.n_combinations(coll, n=3, permutations=False)
assert combs == [(1, 2, 3), (1, 2, 4), (1, 3, 4), (2, 3, 4)]
def __init__(self,
other_names=('k1', 'k2', 'k3'),
calc_tau=False,
dataset_names=None,
metadata_template=None):
other_names = list(other_names)
super(IntercomparisonMetrics,
self).__init__(other_name=other_names,
metadata_template=metadata_template)
# string that splits the dataset names and metric names in the output
# e.g. 'metric_between_dataset1_and_dataset2'
self.ds_names_split, self.metric_ds_split = '_and_', '_between_'
self.df_columns = ['ref'] + self.other_name
self.calc_tau = calc_tau
if dataset_names is None:
self.ds_names = self.df_columns
else:
self.ds_names = dataset_names
self.ds_names_lut = {}
for name, col in zip(self.ds_names, self.df_columns):
self.ds_names_lut[col] = name
combis = n_combinations(self.df_columns, 2, must_include='ref')
self.tds_names = []
for combi in combis:
self.tds_names.append("{1}{0}{2}".format(self.ds_names_split,
*combi))
# metrics that are equal for all datasets
metrics_common = ['n_obs']
# metrics that are calculated between dataset pairs
metrics_tds = [
'R', 'p_R', 'rho', 'p_rho', 'BIAS', 'RMSD', 'mse', 'RSS',
'mse_corr', 'mse_bias', 'urmsd', 'mse_var', 'tau', 'p_tau'
]
metrics_common = _get_metric_template(metrics_common)
metrics_tds = _get_metric_template(metrics_tds)
for metric in metrics_common.keys():
self.result_template[metric] = metrics_common[metric].copy()
for tds_name in self.tds_names:
split_tds_name = tds_name.split(self.ds_names_split)
tds_name_key = \
self.ds_names_split.join([self.ds_names_lut[split_tds_name[0]],
self.ds_names_lut[split_tds_name[1]]])
for metric in metrics_tds.keys():
key = self.metric_ds_split.join([metric, tds_name_key])
self.result_template[key] = metrics_tds[metric].copy()
if not calc_tau:
self.result_template.pop('tau', None)
self.result_template.pop('p_tau', None)
def _make_names(self):
tds_names, thds_names = [], []
combis_2 = n_combinations(self.df_columns,
2,
must_include=[self.ref_name])
combis_3 = n_combinations(self.df_columns,
3,
must_include=[self.ref_name])
for combi in combis_2:
tds_names.append(self.ds_names_split.join(combi))
for combi in combis_3:
thds_names.append("{1}{0}{2}{0}{3}".format(self.ds_names_split,
*combi))
return tds_names, thds_names
