def run(self, ref_dataset, target_dataset):
'''Calculate the spatial correlation between a reference and target dataset.
Using: scipy.stats.pearsonr
.. note::
Overrides BinaryMetric.run()
:param ref_dataset: The reference dataset to use in this metric run.
:type ref_dataset: Dataset.
:param target_dataset: The target dataset to evaluate against the
reference dataset in this metric run.
:type target_dataset: Dataset.
:returns: The spatial correlation between a reference and target dataset.
'''
# This is calcClimYear function for ref_dataset
reshaped_ref_data = utils.reshape_monthly_to_annually(ref_dataset)
ref_t_series = reshaped_ref_data.mean(axis=1)
ref_means = ref_t_series.mean(axis=0)
# This is calcClimYear function for target_dataset
reshaped_target_data = utils.reshape_monthly_to_annually(
target_dataset)
target_t_series = reshaped_target_data.mean(axis=1)
target_means = target_t_series.mean(axis=0)
pattern_correlation, p_value = stats.pearsonr(target_means.flatten(),
ref_means.flatten())
return pattern_correlation, p_value
def run(self, ref_dataset, target_dataset):
'''Calculate the ratio of spatial std. dev. between a reference and
target dataset.
.. note::
Overrides BinaryMetric.run()
:param ref_dataset: The reference dataset to use in this metric run.
:type ref_dataset: Dataset.
:param target_dataset: The target dataset to evaluate against the
reference dataset in this metric run.
:type target_dataset: Dataset.
:returns: The ratio of standard deviation of the reference and target
dataset.
'''
# This is calcClimYear function for ref_dataset
reshaped_ref_data = utils.reshape_monthly_to_annually(ref_dataset)
ref_t_series = reshaped_ref_data.mean(axis=1)
ref_means = ref_t_series.mean(axis=0)
# This is calcClimYear function for target_dataset
reshaped_target_data = utils.reshape_monthly_to_annually(
target_dataset)
target_t_series = reshaped_target_data.mean(axis=1)
target_means = target_t_series.mean(axis=0)
return numpy.std(ref_means) / numpy.std(target_means)
def run(self, ref_dataset, target_dataset):
'''Calculate the spatial correlation between a reference and target dataset.
Using: scipy.stats.pearsonr
.. note::
Overrides BinaryMetric.run()
:param ref_dataset: The reference dataset to use in this metric run.
:type ref_dataset: Dataset.
:param target_dataset: The target dataset to evaluate against the
reference dataset in this metric run.
:type target_dataset: Dataset.
:returns: The spatial correlation between a reference and target dataset.
'''
# This is calcClimYear function for ref_dataset
reshaped_ref_data = utils.reshape_monthly_to_annually(ref_dataset)
ref_t_series = reshaped_ref_data.mean(axis=1)
ref_means = ref_t_series.mean(axis=0)
# This is calcClimYear function for target_dataset
reshaped_target_data = utils.reshape_monthly_to_annually(target_dataset)
target_t_series = reshaped_target_data.mean(axis=1)
target_means = target_t_series.mean(axis=0)
pattern_correlation, p_value = stats.pearsonr(target_means.flatten(),ref_means.flatten())
return pattern_correlation, p_value
def run(self, ref_dataset, target_dataset):
'''Calculate the ratio of spatial std. dev. between a reference and
target dataset.
.. note::
Overrides BinaryMetric.run()
:param ref_dataset: The reference dataset to use in this metric run.
:type ref_dataset: Dataset.
:param target_dataset: The target dataset to evaluate against the
reference dataset in this metric run.
:type target_dataset: Dataset.
:returns: The ratio of standard deviation of the reference and target
dataset.
'''
# This is calcClimYear function for ref_dataset
reshaped_ref_data = utils.reshape_monthly_to_annually(ref_dataset)
ref_t_series = reshaped_ref_data.mean(axis=1)
ref_means = ref_t_series.mean(axis=0)
# This is calcClimYear function for target_dataset
reshaped_target_data = utils.reshape_monthly_to_annually(target_dataset)
target_t_series = reshaped_target_data.mean(axis=1)
target_means = target_t_series.mean(axis=0)
return numpy.std(ref_means) / numpy.std(target_means)
def test_reshape_full_year(self):
new_values = self.value.reshape(2, 12, 5, 5)
np.testing.assert_array_equal(
utils.reshape_monthly_to_annually(self.test_dataset), new_values)
def test_reshape_full_year(self):
new_values = self.value.reshape(2, 12, 5, 5)
np.testing.assert_array_equal(
utils.reshape_monthly_to_annually(self.test_dataset), new_values)