def get_coords_for_channel(channel_name=None, **kwargs):
config_dict = kwargs.copy()
if channel_name:
config_dict.update(get_config_as_dict("Diagnostic", channel_name))
coord_name = "dummy"
coord_values = (0.0, 0.0, 0.0)
transforms = []
for k in config_dict.keys():
if k.startswith("coords_"):
coord_name = k[7:]
coord_values = tuple(map(float, config_dict[k].split(",")))
coords_instance = Coords(coord_name, coord_values)
if "coord_transform" in config_dict:
transform_list = pyfusion.config.pf_options("CoordTransform", config_dict["coord_transform"])
for transform_name in transform_list:
# this seems to return all the globals too
transform_class_str = pyfusion.config.pf_get(
"CoordTransform", config_dict["coord_transform"], transform_name
)
# so tyr to exclude the globals
if pyfusion.config.has_option("global", transform_name):
continue
transform_class = import_from_str(transform_class_str)
# if not hasattr(transform_class, 'output_coord'):
# raise Exception('??')
coords_instance.load_transform(transform_class)
debug_(pyfusion.DEBUG, 1, key=["coord", "device_name"])
return coords_instance
def get_coords_for_channel(channel_name=None, **kwargs):
config_dict = kwargs.copy()
if channel_name:
config_dict.update(get_config_as_dict('Diagnostic', channel_name))
coord_name = 'dummy'
coord_values = (0.0,0.0,0.0)
transforms = []
for k in config_dict.keys():
if k.startswith('coords_'):
coord_name = k[7:]
coord_values = tuple(map(float,config_dict[k].split(',')))
coords_instance = Coords(coord_name, coord_values)
if 'coord_transform' in config_dict:
transform_list = pyfusion.config.pf_options('CoordTransform', config_dict['coord_transform'])
for transform_name in transform_list:
# this seems to return all the globals too
transform_class_str = pyfusion.config.pf_get('CoordTransform', config_dict['coord_transform'], transform_name)
# so tyr to exclude the globals
if pyfusion.config.has_option('global',transform_name):
continue
transform_class = import_from_str(transform_class_str)
#if not hasattr(transform_class, 'output_coord'):
# raise Exception('??')
coords_instance.load_transform(transform_class)
debug_(pyfusion.DEBUG,1, key=['coord', 'device_name'])
return coords_instance
def load_from_config(self, **kwargs):
for kw in kwargs.iteritems():
if kw[0] == 'coord_transform':
transform_list = pyfusion.config.pf_options('CoordTransform', kw[1])
for transform_name in transform_list:
transform_class_str = pyfusion.config.pf_get('CoordTransform', kw[1], transform_name)
transform_class = import_from_str(transform_class_str)
self.load_transform(transform_class)
elif kw[0].startswith('coords_'):
coord_values = tuple(map(float,kw[1].split(',')))
self.add_coords(**{kw[0][7:]: coord_values})
def __init__(self, config_name, **kwargs):
if pyfusion.config.pf_has_section('Device', config_name):
self.__dict__.update(get_config_as_dict('Device', config_name))
self.__dict__.update(kwargs)
self.name = config_name
#### attach acquisition
if hasattr(self, 'acq_name'):
acq_class_str = pyfusion.config.pf_get('Acquisition',
self.acq_name, 'acq_class')
self.acquisition = import_from_str(acq_class_str)(self.acq_name)
# shortcut
self.acq = self.acquisition
else:
pyfusion.logging.warning(
"No acquisition class specified for device")
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 get_coords_for_channel(channel_name=None, **kwargs):
config_dict = kwargs.copy()
if channel_name:
config_dict.update(get_config_as_dict('Diagnostic', channel_name))
coord_name = 'dummy'
coord_values = (0.0,0.0,0.0)
transforms = []
for k in config_dict.keys():
if k.startswith('coords_'):
coord_name = k[7:]
coord_values = tuple(map(float,config_dict[k].split(',')))
coords_instance = Coords(coord_name, coord_values)
if config_dict.has_key('coord_transform'):
transform_list = pyfusion.config.pf_options('CoordTransform', config_dict['coord_transform'])
for transform_name in transform_list:
transform_class_str = pyfusion.config.pf_get('CoordTransform', config_dict['coord_transform'], transform_name)
transform_class = import_from_str(transform_class_str)
coords_instance.load_transform(transform_class)
return coords_instance
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 getDevice(device_name):
"""Find and instantiate Device (sub)class from config."""
dev_class_str = pyfusion.config.pf_get('Device', device_name, 'dev_class')
return import_from_str(dev_class_str)(device_name)
def check_module(self, module_name):
path = 'pyfusion.acquisition'
import_from_str('.'.join([path, module_name]))
import_from_str('.'.join([path, module_name, 'acq']))
import_from_str('.'.join([path, module_name, 'fetch']))
def test_import_from_str(self):
from pyfusion.conf.utils import import_from_str
string_value = "pyfusion.acquisition.FakeData.acq.FakeDataAcquisition"
from pyfusion.acquisition.FakeData.acq import FakeDataAcquisition
self.assertEqual(import_from_str(string_value), FakeDataAcquisition)
def check_module(self, module_name):
path = 'pyfusion.acquisition'
import_from_str('.'.join([path, module_name]))
import_from_str('.'.join([path, module_name, 'acq']))
import_from_str('.'.join([path, module_name, 'fetch']))
def test_import_from_str(self):
from pyfusion.conf.utils import import_from_str
string_value = "pyfusion.acquisition.FakeData.acq.FakeDataAcquisition"
from pyfusion.acquisition.FakeData.acq import FakeDataAcquisition
self.assertEqual(import_from_str(string_value), FakeDataAcquisition)