def create_metrics(ref, test, ref_regrid, test_regrid, diff):
"""Creates the mean, max, min, rmse, corr in a dictionary"""
metrics_dict = {}
metrics_dict['ref'] = {
'min': min_cdms(ref),
'max': max_cdms(ref),
'mean': mean(ref)
}
metrics_dict['test'] = {
'min': min_cdms(test),
'max': max_cdms(test),
'mean': mean(test)
}
metrics_dict['diff'] = {
'min': min_cdms(diff),
'max': max_cdms(diff),
'mean': mean(diff)
}
metrics_dict['misc'] = {
'rmse': rmse(test_regrid, ref_regrid),
'corr': corr(test_regrid, ref_regrid)
}
return metrics_dict
def create_metrics(ref, test, ref_regrid, test_regrid, diff):
"""Creates the mean, max, min, rmse, corr in a dictionary"""
orig_bounds = cdms2.getAutoBounds()
cdms2.setAutoBounds(1)
lev = ref.getLevel()
if lev is not None:
lev.setBounds(None)
lev = test.getLevel()
if lev is not None:
lev.setBounds(None)
lev = test_regrid.getLevel()
if lev is not None:
lev.setBounds(None)
lev = ref_regrid.getLevel()
if lev is not None:
lev.setBounds(None)
lev = diff.getLevel()
if lev is not None:
lev.setBounds(None)
cdms2.setAutoBounds(orig_bounds)
metrics_dict = {}
metrics_dict['ref'] = {
'min': min_cdms(ref),
'max': max_cdms(ref),
#'mean': numpy.nan #mean(ref, axis='yz')
'mean': mean(ref, axis='yz')
}
metrics_dict['test'] = {
'min': min_cdms(test),
'max': max_cdms(test),
#'mean': numpy.nan #mean(test, axis='yz')
'mean': mean(test, axis='yz')
}
metrics_dict['diff'] = {
'min': min_cdms(diff),
'max': max_cdms(diff),
#'mean': numpy.nan #mean(diff, axis='yz')
'mean': mean(diff, axis='yz')
}
metrics_dict['misc'] = {
'rmse': rmse(test_regrid, ref_regrid, axis='yz'),
'corr': corr(test_regrid, ref_regrid, axis='yz')
}
return metrics_dict
def create_metrics(ref, test, ref_regrid, test_regrid, diff):
"""
Creates the mean, max, min, rmse, corr in a dictionary.
"""
orig_bounds = cdms2.getAutoBounds()
cdms2.setAutoBounds(1)
lev = ref.getLevel()
if lev is not None:
lev.setBounds(None)
lev = test.getLevel()
if lev is not None:
lev.setBounds(None)
lev = test_regrid.getLevel()
if lev is not None:
lev.setBounds(None)
lev = ref_regrid.getLevel()
if lev is not None:
lev.setBounds(None)
lev = diff.getLevel()
if lev is not None:
lev.setBounds(None)
cdms2.setAutoBounds(orig_bounds)
metrics_dict = {}
metrics_dict["ref"] = {
"min": min_cdms(ref),
"max": max_cdms(ref),
"mean": mean(ref, axis="xz"),
}
metrics_dict["test"] = {
"min": min_cdms(test),
"max": max_cdms(test),
"mean": mean(test, axis="xz"),
}
metrics_dict["diff"] = {
"min": min_cdms(diff),
"max": max_cdms(diff),
"mean": mean(diff, axis="xz"),
}
metrics_dict["misc"] = {
"rmse": rmse(test_regrid, ref_regrid, axis="xz"),
"corr": corr(test_regrid, ref_regrid, axis="xz"),
}
return metrics_dict
def create_single_metrics_dict(values):
d = {
'min': float(min_cdms(values)),
'max': float(max_cdms(values)),
'mean': float(mean(values)),
'std': float(std(values))
}
return d
def create_single_metrics_dict(values):
d = {
"min": float(min_cdms(values)),
"max": float(max_cdms(values)),
"mean": float(mean(values)),
"std": float(std(values)),
}
return d