def stats_cmd(main_arguments):
"""
Main routine for handling calls to the statistics command.
:param main_arguments: The command line arguments (minus the stats command)
"""
from cis.stats import StatsAnalyzer
from cis.data_io.gridded_data import GriddedDataList
data_reader = DataReader()
data_list = data_reader.read_datagroups(main_arguments.datagroups)
analyzer = StatsAnalyzer(*data_list)
results = analyzer.analyze()
header = "RESULTS OF STATISTICAL COMPARISON:"
note = "Compared all points which have non-missing values in both variables"
header_length = max(len(header), len(note))
print(header_length * '=')
print(header)
print(header_length * '-')
print(note)
print(header_length * '=')
for result in results:
print(result.pprint())
if main_arguments.output:
cubes = GriddedDataList([result.as_cube() for result in results])
variables = []
filenames = []
for datagroup in main_arguments.datagroups:
variables.extend(datagroup['variables'])
filenames.extend(datagroup['filenames'])
history = "Statistical comparison performed using CIS version " + __version__ + \
"\n variables: " + str(variables) + \
"\n from files: " + str(set(filenames))
cubes.add_history(history)
cubes.save_data(main_arguments.output)
def stats_cmd(main_arguments):
"""
Main routine for handling calls to the statistics command.
:param main_arguments: The command line arguments (minus the stats command)
"""
from cis.stats import StatsAnalyzer
from cis.data_io.gridded_data import GriddedDataList
data_reader = DataReader()
data_list = data_reader.read_datagroups(main_arguments.datagroups)
analyzer = StatsAnalyzer(*data_list)
results = analyzer.analyze()
header = "RESULTS OF STATISTICAL COMPARISON:"
note = "Compared all points which have non-missing values in both variables"
header_length = max(len(header), len(note))
print(header_length * '=')
print(header)
print(header_length * '-')
print(note)
print(header_length * '=')
for result in results:
print(result.pprint())
if main_arguments.output:
cubes = GriddedDataList([result.as_cube() for result in results])
variables = []
filenames = []
for datagroup in main_arguments.datagroups:
variables.extend(datagroup['variables'])
filenames.extend(datagroup['filenames'])
history = "Statistical comparison performed using CIS version " + __version__ + \
"\n variables: " + str(variables) + \
"\n from files: " + str(set(filenames))
cubes.add_history(history)
cubes.save_data(main_arguments.output)
def test_gridded_list_write_no_time_has_no_unlimited_dimension(self):
data = GriddedDataList([make_from_cube(make_mock_cube())])
data[0].var_name = 'rain'
data.save_data(tmp_file)
self.d = Dataset(tmp_file)
for d in self.d.dimensions.values():
assert not d.isunlimited()
def test_gridded_list_write_time_as_unlimited_dimension(self):
data = GriddedDataList(
[make_from_cube(make_mock_cube(time_dim_length=7))])
data[0].var_name = 'rain'
data.save_data(tmp_file)
self.d = Dataset(tmp_file)
assert self.d.dimensions['time'].isunlimited()
def test_gridded_list_write_no_time_has_no_unlimited_dimension(self):
data = GriddedDataList([make_from_cube(make_mock_cube())])
data[0].var_name = 'rain'
data.save_data(tmp_file)
self.d = Dataset(tmp_file)
for d in self.d.dimensions.values():
assert not d.isunlimited()
def test_gridded_list_write_time_as_unlimited_dimension(self):
data = GriddedDataList([make_from_cube(make_mock_cube(time_dim_length=7))])
data[0].var_name = 'rain'
data.save_data(tmp_file)
self.d = Dataset(tmp_file)
assert self.d.dimensions['time'].isunlimited()
