def test_return_correct_type(self):
from pyfusion import config
# a setting of type float:
sample_freq = config.pf_get('Diagnostic', 'test_types', 'sample_freq')
self.assertTrue(type(sample_freq) == float)
# a setting of type int:
n_samples = config.pf_get('Diagnostic', 'test_types', 'n_samples')
self.assertTrue(type(n_samples) == int)
# a setting of type boolean:
test_bool = config.pf_get('Diagnostic', 'test_types', 'testboolean')
self.assertTrue(type(test_bool) == bool)
# test unknown type raises exception
from pyfusion.conf.exceptions import UnknownVariableTypeError
self.assertRaises(UnknownVariableTypeError, config.pf_get,
'Diagnostic', 'test_types', 'unknowntype')
def test_config_as_dict(self):
from pyfusion import config, conf
config_option_list = config.pf_options('Acquisition', 'test_fakedata')
config_map = lambda x: (x, config.pf_get('Acquisition', 'test_fakedata', x))
config_dict_1 = dict(map(config_map, config_option_list))
config_dict_2 = conf.utils.get_config_as_dict('Acquisition', 'test_fakedata')
self.assertEqual(config_dict_1, config_dict_2)
def test_return_correct_type(self):
from pyfusion import config
# a setting of type float:
sample_freq = config.pf_get('Diagnostic', 'test_types', 'sample_freq')
self.assertTrue(type(sample_freq) == float)
# a setting of type int:
n_samples = config.pf_get('Diagnostic', 'test_types', 'n_samples')
self.assertTrue(type(n_samples) == int)
# a setting of type boolean:
test_bool = config.pf_get('Diagnostic', 'test_types', 'testboolean')
self.assertTrue(type(test_bool) == bool)
# test unknown type raises exception
from pyfusion.conf.exceptions import UnknownVariableTypeError
self.assertRaises(UnknownVariableTypeError,
config.pf_get,
'Diagnostic',
'test_types',
'unknowntype')
def test_config_as_dict(self):
from pyfusion import config, conf
config_option_list = config.pf_options('Acquisition', 'test_fakedata')
config_map = lambda x: (
x, config.pf_get('Acquisition', 'test_fakedata', x))
config_dict_1 = dict(map(config_map, config_option_list))
config_dict_2 = conf.utils.get_config_as_dict('Acquisition',
'test_fakedata')
self.assertEqual(config_dict_1, config_dict_2)
def testDeviceConnection(self):
"""Check that using config loads the correct acquisition."""
from pyfusion.devices.base import Device
test_device = Device('TestDevice')
from pyfusion import conf, config
acq_name = config.pf_get('Device', 'TestDevice', 'acq_name')
test_acq = conf.utils.import_setting('Acquisition', acq_name,
'acq_class')
self.assertTrue(isinstance(test_device.acquisition, test_acq))
# test that device.acq shortcut works
self.assertEqual(test_device.acquisition, test_device.acq)
def testDeviceConnection(self):
"""Check that using config loads the correct acquisition."""
from pyfusion.devices.base import Device
test_device = Device("TestDevice")
from pyfusion import conf, config
acq_name = config.pf_get("Device", "TestDevice", "acq_name")
test_acq = conf.utils.import_setting("Acquisition", acq_name, "acq_class")
self.assertTrue(isinstance(test_device.acquisition, test_acq))
# test that device.acq shortcut works
self.assertEqual(test_device.acquisition, test_device.acq)
def getdata(self, shot, config_name=None, **kwargs):
"""Get the data and return prescribed subclass of BaseData.
:param shot: shot number
:param config_name: ?? bdb name of a fetcher class in the configuration file
:returns: an instance of a subclass of \
:py:class:`~pyfusion.data.base.BaseData` or \
:py:class:`~pyfusion.data.base.BaseDataSet`
This method needs to know which data fetcher class to use, if a
config_name argument is supplied then the
``[Diagnostic:config_name]`` section must exist in the
configuration file and contain a ``data_fetcher`` class
specification, for example::
[Diagnostic:H1_mirnov_array_1_coil_1]
data_fetcher = pyfusion.acquisition.H1.fetch.H1DataFetcher
mds_path = \h1data::top.operations.mirnov:a14_14:input_1
coords_cylindrical = 1.114, 0.7732, 0.355
coord_transform = H1_mirnov
If a ``data_fetcher`` keyword argument is supplied, it overrides
the configuration file specification.
The fetcher class is instantiated, including any supplied
keyword arguments, and the result of the ``fetch`` method of the
fetcher class is returned.
"""
from pyfusion import config
# if there is a data_fetcher arg, use that, otherwise get from config
if 'data_fetcher' in kwargs:
fetcher_class_name = kwargs['data_fetcher']
else:
fetcher_class_name = config.pf_get('Diagnostic',
config_name,
'data_fetcher')
fetcher_class = import_from_str(fetcher_class_name)
## Problem: no check to see if it is a diag of the right device!??
d = fetcher_class(self, shot,
config_name=config_name, **kwargs).fetch()
d.history += "\n:: shot: {s} :: config: {c}".format(s=shot, c=config_name)
return d
def test_kwarg_config_handler(self):
from pyfusion.conf.utils import kwarg_config_handler
from pyfusion import config
# config values should be overridden by kwargs
# test against [Device:TestDevice]
# take acquisition from config, and database from kwarsg
# give an additional kwarg not in config
test_kwargs = {'database': 'dummy_database', 'other_var': 'other_val'}
output_vars = kwarg_config_handler('Device', 'TestDevice',
**test_kwargs)
#make sure test_kwargs are returned
for kwarg_item in test_kwargs.items():
self.assertTrue(kwarg_item in output_vars.items())
# make sure that config vars not in test_kwargs are included in kwargs
for config_var in config.pf_options('Device', 'TestDevice'):
if not config_var in test_kwargs.keys():
self.assertEqual(
output_vars[config_var],
config.pf_get('Device', 'TestDevice', config_var))
def getdata(self, shot, config_name=None, **kwargs):
"""Get the data and return prescribed subclass of BaseData.
:param shot: shot number
:param config_name: ?? bdb name of a fetcher class in the configuration file
:returns: an instance of a subclass of \
:py:class:`~pyfusion.data.base.BaseData` or \
:py:class:`~pyfusion.data.base.BaseDataSet`
This method needs to know which data fetcher class to use, if a
config_name argument is supplied then the
``[Diagnostic:config_name]`` section must exist in the
configuration file and contain a ``data_fetcher`` class
specification, for example::
[Diagnostic:H1_mirnov_array_1_coil_1]
data_fetcher = pyfusion.acquisition.H1.fetch.H1DataFetcher
mds_path = \h1data::top.operations.mirnov:a14_14:input_1
coords_cylindrical = 1.114, 0.7732, 0.355
coord_transform = H1_mirnov
If a ``data_fetcher`` keyword argument is supplied, it overrides
the configuration file specification.
The fetcher class is instantiated, including any supplied
keyword arguments, and the result of the ``fetch`` method of the
fetcher class is returned.
"""
from pyfusion import config
# if there is a data_fetcher arg, use that, otherwise get from config
if kwargs.has_key('data_fetcher'):
fetcher_class_name = kwargs['data_fetcher']
else:
fetcher_class_name = config.pf_get('Diagnostic', config_name,
'data_fetcher')
fetcher_class = import_from_str(fetcher_class_name)
d = fetcher_class(self, shot, config_name=config_name,
**kwargs).fetch()
d.history += "\n:: shot: %d\n:: config: %s" % (shot, config_name)
return d
def test_kwarg_config_handler(self):
from pyfusion.conf.utils import kwarg_config_handler
from pyfusion import config
# config values should be overridden by kwargs
# test against [Device:TestDevice]
# take acquisition from config, and database from kwarsg
# give an additional kwarg not in config
test_kwargs = {'database': 'dummy_database',
'other_var': 'other_val'}
output_vars = kwarg_config_handler('Device',
'TestDevice', **test_kwargs)
#make sure test_kwargs are returned
for kwarg_item in test_kwargs.items():
self.assertTrue(kwarg_item in output_vars.items())
# make sure that config vars not in test_kwargs are included in kwargs
for config_var in config.pf_options('Device', 'TestDevice'):
if not config_var in test_kwargs.keys():
self.assertEqual(output_vars[config_var],
config.pf_get('Device',
'TestDevice', config_var))
