def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label, load_data
paths, fac = self._get_paths_and_factory()
result = []
# Check that the user didn't select a .glu file by mistake
for path in paths:
if path.endswith('.glu'):
mb = QtWidgets.QMessageBox(QtWidgets.QMessageBox.Critical,
"Error loading data",
"It looks like you have selected "
"a .glu session file. You should open "
"this using 'Open Session' under the "
"'File' menu instead")
mb.exec_()
return []
with set_cursor_cm(Qt.WaitCursor):
for path in paths:
self._curfile = path
d = load_data(path, factory=fac.function)
if not isinstance(d, list):
if not d.label:
d.label = data_label(path)
d = [d]
result.extend(d)
return result
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label, load_data
paths, fac = self._get_paths_and_factory()
result = []
# Check that the user didn't select a .glu file by mistake
for path in paths:
if path.endswith('.glu'):
mb = QtWidgets.QMessageBox(
QtWidgets.QMessageBox.Critical, "Error loading data",
"It looks like you have selected "
"a .glu session file. You should open "
"this using 'Open Session' under the "
"'File' menu instead")
mb.exec_()
return []
with set_cursor_cm(Qt.WaitCursor):
for path in paths:
self._curfile = path
d = load_data(path, factory=fac.function)
if not isinstance(d, list):
if not d.label:
d.label = data_label(path)
d = [d]
result.extend(d)
return result
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A constructed data object, or None
"""
from glue.core.data_factories import data_label
path, fac = self._get_path_and_factory()
if path is not None:
result = fac.function(path)
result.label = data_label(path)
return result
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label
path, fac = self._get_path_and_factory()
if path is not None:
result = fac.function(path)
if isinstance(result, list):
return result
#single data object
result.label = data_label(path)
return [result]
return []
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label
path, fac = self._get_path_and_factory()
if path is not None:
result = fac.function(path)
if isinstance(result, list):
return result
#single data object
result.label = data_label(path)
return [result]
return []
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label, load_data
paths, fac = self._get_paths_and_factory()
result = []
for path in paths:
d = load_data(path, factory=fac.function)
if not isinstance(d, list):
d.label = data_label(path)
d = [d]
result.extend(d)
return result
def load_data(self):
"""Highest level method to interactively load a data set.
:rtype: A list of constructed data objects
"""
from glue.core.data_factories import data_label, load_data
paths, fac = self._get_paths_and_factory()
result = []
for path in paths:
d = load_data(path, factory=fac.function)
if not isinstance(d, list):
d.label = data_label(path)
d = [d]
result.extend(d)
return result
def yt_data(path):
"""Use yt to load a gridded dataset
This function will extract all particle and field datasets
(excluding derived datasets) from a file. Currently,
you cannot make images from this data.
The resulting Field dataset refers to the highest-resolution
subgrids
Paramters
---------
path : str
Path to file to load. This is what get's passed to yt.mods.load()
Returns
-------
One or two Glue data objects
"""
ds = load(path)
dd = ds.h.all_data()
particles = [f for f in ds.h.field_list if ds.field_info[f].particle_type]
fields = [f for f in ds.h.field_list if not ds.field_info[f].particle_type]
lbl = data_label(path)
result = []
if len(particles) > 0:
d1 = Data(label=lbl + "_particle")
shp = dd[particles[0]].shape
for p in particles:
d1.add_component(YtComponent(ds, p, shp), p)
result.append(d1)
if len(fields) > 0:
d2 = Data(label=lbl + "_field")
shp = dd[fields[0]].shape
for f in fields:
d2.add_component(YtComponent(ds, f, shp), f)
result.append(d2)
return result
def test_data_label():
assert df.data_label('test.fits') == 'test'
assert df.data_label('/Leading/Path/test.fits') == 'test'
assert df.data_label('') == ''
assert df.data_label('/Leading/Path/no_extension') == 'no_extension'
assert df.data_label('no_extension') == 'no_extension'
def test_data_label():
assert df.data_label('test.fits') == 'test'
assert df.data_label('/Leading/Path/test.fits') == 'test'
assert df.data_label('') == ''
assert df.data_label('/Leading/Path/no_extension') == 'no_extension'
assert df.data_label('no_extension') == 'no_extension'
