def _load_data(self):
""" Interactively loads data from a data set. Adds
as new layer """
from glue.qt.glue_application import GlueApplication
layers = qtutil.data_wizard()
GlueApplication.add_datasets(self.data_collection, layers)
def qglue(**kwargs):
"""
Quickly send python variables to Glue for visualization.
The generic calling sequence is::
qglue(label1=data1, label2=data2, ..., [links=links])
The kewyords label1, label2, ... can be named anything besides ``links``
data1, data2, ... can be in many formats:
* A pandas data frame
* A path to a file
* A numpy array, or python list
* A numpy rec array
* A dictionary of numpy arrays with the same shape
* An astropy Table
``Links`` is an optional list of link descriptions, each of which has
the format: ([left_ids], [right_ids], forward, backward)
Each ``left_id``/``right_id`` is a string naming a component in a dataset
(i.e., ``data1.x``). ``forward`` and ``backward`` are functions which
map quantities on the left to quantities on the right, and vice
versa. `backward` is optional
Examples::
balls = {'kg': [1, 2, 3], 'radius_cm': [10, 15, 30]}
cones = {'lbs': [5, 3, 3, 1]}
def lb2kg(lb):
return lb / 2.2
def kg2lb(kg):
return kg * 2.2
links = [(['balls.kg'], ['cones.lbs'], lb2kg, kg2lb)]
qglue(balls=balls, cones=cones, links=links)
:returns: A :class:`~glue.qt.glue_application.GlueApplication` object
"""
from .core import DataCollection
from glue.qt.glue_application import GlueApplication
links = kwargs.pop('links', None)
dc = DataCollection()
for label, data in kwargs.items():
dc.extend(parse_data(data, label))
if links is not None:
dc.add_link(_parse_links(dc, links))
with restore_io():
ga = GlueApplication(dc)
ga.start()
return ga
def qglue(**kwargs):
"""
Quickly send python variables to Glue for visualization.
The generic calling sequence is::
qglue(label1=data1, label2=data2, ..., [links=links])
The kewyords label1, label2, ... can be named anything besides ``links``
data1, data2, ... can be in many formats:
* A pandas data frame
* A path to a file
* A numpy array, or python list
* A numpy rec array
* A dictionary of numpy arrays with the same shape
* An astropy Table
``Links`` is an optional list of link descriptions, each of which has
the format: ([left_ids], [right_ids], forward, backward)
Each ``left_id``/``right_id`` is a string naming a component in a dataset
(i.e., ``data1.x``). ``forward`` and ``backward`` are functions which
map quantities on the left to quantities on the right, and vice
versa. `backward` is optional
Examples::
balls = {'kg': [1, 2, 3], 'radius_cm': [10, 15, 30]}
cones = {'lbs': [5, 3, 3, 1]}
def lb2kg(lb):
return lb / 2.2
def kg2lb(kg):
return kg * 2.2
links = [(['balls.kg'], ['cones.lbs'], lb2kg, kg2lb)]
qglue(balls=balls, cones=cones, links=links)
:returns: A :class:`~glue.qt.glue_application.GlueApplication` object
"""
from .core import DataCollection
from glue.qt.glue_application import GlueApplication
links = kwargs.pop('links', None)
dc = DataCollection()
for label, data in kwargs.items():
dc.extend(parse_data(data, label))
if links is not None:
dc.add_link(_parse_links(dc, links))
with restore_io():
ga = GlueApplication(dc)
ga.start()
return ga
def test_multi_tab(self):
d = core.Data(label="hist", x=[[1, 2], [2, 3]])
dc = core.DataCollection([d])
app = GlueApplication(dc)
w1 = app.new_data_viewer(HistogramWidget, data=d)
app.new_tab()
w2 = app.new_data_viewer(HistogramWidget, data=d)
assert app.viewers == ((w1,), (w2,))
self.check_clone(app)
def test_cube(self):
d = core.Data(label='cube',
x=np.zeros((2, 2, 2)))
dc = core.DataCollection([d])
app = GlueApplication(dc)
w = app.new_data_viewer(ImageWidget, d)
w.slice = ('x', 'y', 1)
assert w.slice == ('x', 'y', 1)
c = self.check_clone(app)
w2 = c.viewers[0][0]
assert w2.ui.slice.slice == w.slice
def test_close_on_last_layer_remove(self):
# regression test for 391
d1 = Data(x=np.random.random((2,) * self.ndim))
d2 = Data(y=np.random.random((2,) * self.ndim))
dc = DataCollection([d1, d2])
app = GlueApplication(dc)
with patch.object(self.widget_cls, 'close') as close:
w = app.new_data_viewer(self.widget_cls, data=d1)
w.add_data(d2)
dc.remove(d1)
dc.remove(d2)
assert close.call_count >= 1
def export_glue(ds, data, name):
from glue.core import Data, DataCollection
from glue.qt.glue_application import GlueApplication
import numpy as np
d = Data(label=name)
d.add_component(ytComponent(data, ds, name), label='x')
dc = DataCollection(d)
ga = GlueApplication(dc)
ga.start()
class TestGlueApplication(unittest.TestCase):
def setUp(self):
self.qapp = QApplication([""])
self.app = GlueApplication()
def tearDown(self):
self.app.close()
del self.app
del self.qapp
def test_new_tabs(self):
t0 = tab_count(self.app)
self.app._new_tab()
self.assertEquals(t0 + 1, tab_count(self.app))
def test_histogram(self):
d = core.Data(label="hist", x=[[1, 2], [2, 3]])
dc = core.DataCollection([d])
app = GlueApplication(dc)
w = app.new_data_viewer(HistogramWidget, data=d)
self.check_clone(app)
dc.new_subset_group()
assert len(w.layers) == 2
self.check_clone(app)
w.nbins = 7
self.check_clone(app)
def test_scatter_viewer(self):
d = core.Data(label="x", x=[1, 2, 3, 4, 5], y=[2, 3, 4, 5, 6])
dc = core.DataCollection([d])
app = GlueApplication(dc)
w = app.new_data_viewer(ScatterWidget, data=d)
self.check_clone(app)
s1 = dc.new_subset_group()
s2 = dc.new_subset_group()
assert len(w.layers) == 3
l1, l2, l3 = w.layers
l1.zorder, l2.zorder = l2.zorder, l1.zorder
l3.visible = False
assert l3.visible is False
copy = self.check_clone(app)
assert copy.viewers[0][0].layers[-1].visible is False
def start_glue(gluefile=None, config=None, datafiles=None):
"""Run a glue session and exit
:param gluefile: An optional .glu file to restore
:type gluefile: str
:param config: An optional configuration file to use
:type config: str
:param datafiles: An optional list of data files to load
:type datafiles: list of str
"""
import glue
from glue.qt.glue_application import GlueApplication
# Start off by loading plugins. We need to do this before restoring
# the session or loading the configuration since these may use existing
# plugins.
load_plugins()
datafiles = datafiles or []
data, hub = None, None
if gluefile is not None:
app = restore_session(gluefile)
return app.start()
if config is not None:
glue.env = glue.config.load_configuration(search_path=[config])
if datafiles:
data = load_data_files(datafiles)
if not data:
data = glue.core.DataCollection()
hub = data.hub
session = glue.core.Session(data_collection=data, hub=hub)
ga = GlueApplication(session=session)
#ga.show()
#splash.close()
#ga.raise_()
#QApplication.instance().processEvents()
return ga.start()
def test_single_draw_call_on_create(self):
d = Data(x=np.random.random((2,) * self.ndim))
dc = DataCollection([d])
app = GlueApplication(dc)
try:
from ..mpl_widget import MplCanvas
draw = MplCanvas.draw
MplCanvas.draw = MagicMock()
app.new_data_viewer(self.widget_cls, data=d)
# each Canvas instance gives at most 1 draw call
selfs = [c[0][0] for c in MplCanvas.draw.call_arg_list]
assert len(set(selfs)) == len(selfs)
finally:
MplCanvas.draw = draw
def start_glue(gluefile=None, config=None, datafiles=None):
"""Run a glue session and exit
:param gluefile: An optional .glu file to restore
:type gluefile: str
:param config: An optional configuration file to use
:type config: str
:param datafiles: An optional list of data files to load
:type datafiles: list of str
"""
import glue
from glue.qt.glue_application import GlueApplication
# Start off by loading plugins. We need to do this before restoring
# the session or loading the configuration since these may use existing
# plugins.
load_plugins()
datafiles = datafiles or []
data, hub = None, None
if gluefile is not None:
app = restore_session(gluefile)
return app.start()
if config is not None:
glue.env = glue.config.load_configuration(search_path=[config])
if datafiles:
data = load_data_files(datafiles)
if not data:
data = glue.core.DataCollection()
hub = data.hub
session = glue.core.Session(data_collection=data, hub=hub)
ga = GlueApplication(session=session)
#ga.show()
#splash.close()
#ga.raise_()
#QApplication.instance().processEvents()
return ga.start()
def start_glue(gluefile=None, config=None, datafiles=None):
"""Run a glue session and exit
:param gluefile: An optional .glu file to restore
:type gluefile: str
:param config: An optional configuration file to use
:type config: str
:param datafiles: An optional list of data files to load
:type datafiles: list of str
"""
#from PyQt4.QtGui import QApplication
#app = QApplication.instance() or QApplication(sys.argv)
#splash = get_splash()
import glue
from glue.qt.glue_application import GlueApplication
datafiles = datafiles or []
data, hub = None, None
if gluefile is not None:
data, hub = restore_session(gluefile)
if config is not None:
glue.env = glue.config.load_configuration(search_path=[config])
if datafiles:
data = load_data_files(datafiles)
if not hub:
if data:
hub = glue.core.Hub(data)
else:
hub = glue.core.Hub()
ga = GlueApplication(data_collection=data, hub=hub)
#ga.show()
#splash.close()
#ga.raise_()
#QApplication.instance().processEvents()
return ga.start()
def setup_method(self, method):
LinkSame = core.link_helpers.LinkSame
d = core.Data(label='im', x=[[1, 2], [2, 3]], y=[[2, 3], [4, 5]])
d2 = core.Data(label='cat',
x=[0, 1, 0, 1],
y=[0, 0, 1, 1],
z=[1, 2, 3, 4])
dc = core.DataCollection([d, d2])
dc.add_link(LinkSame(d.get_pixel_component_id(0), d2.id['x']))
dc.add_link(LinkSame(d.get_pixel_component_id(1), d2.id['y']))
app = GlueApplication(dc)
w = app.new_data_viewer(ImageWidget, data=d)
self.d = d
self.app = app
self.w = w
self.d2 = d2
self.dc = dc
def to_glue(self, label="yt", data_collection=None):
"""
Takes the data in the FITSImageData instance and exports it to
Glue (http://www.glueviz.org) for interactive analysis. Optionally
add a *label*. If you are already within the Glue environment, you
can pass a *data_collection* object, otherwise Glue will be started.
"""
from glue.core import DataCollection, Data
from glue.core.coordinates import coordinates_from_header
from glue.qt.glue_application import GlueApplication
image = Data(label=label)
image.coords = coordinates_from_header(self.wcs.to_header())
for k,f in self.items():
image.add_component(f.data, k)
if data_collection is None:
dc = DataCollection([image])
app = GlueApplication(dc)
app.start()
else:
data_collection.append(image)
def to_glue(self, label="yt", data_collection=None):
"""
Takes the data in the FITSImageData instance and exports it to
Glue (http://www.glueviz.org) for interactive analysis. Optionally
add a *label*. If you are already within the Glue environment, you
can pass a *data_collection* object, otherwise Glue will be started.
"""
from glue.core import DataCollection, Data
from glue.core.coordinates import coordinates_from_header
from glue.qt.glue_application import GlueApplication
image = Data(label=label)
image.coords = coordinates_from_header(self.wcs.to_header())
for k, f in self.items():
image.add_component(f.data, k)
if data_collection is None:
dc = DataCollection([image])
app = GlueApplication(dc)
app.start()
else:
data_collection.append(image)
def start_glue(gluefile=None, config=None, datafiles=None):
"""Run a glue session and exit
:param gluefile: An optional .glu file to restore
:type gluefile: str
:param config: An optional configuration file to use
:type config: str
:param datafiles: An optional list of data files to load
:type datafiles: list of str
"""
import glue
from glue.qt.glue_application import GlueApplication
datafiles = datafiles or []
data, hub = None, None
if gluefile is not None:
data, hub = restore_session(gluefile)
if config is not None:
glue.env = glue.config.load_configuration(search_path=[config])
if datafiles:
data = load_data_files(datafiles)
if not hub:
if data:
hub = glue.core.Hub(data)
else:
hub = glue.core.Hub()
ga = GlueApplication(data_collection=data, hub=hub)
#ga.show()
#splash.close()
#ga.raise_()
#QApplication.instance().processEvents()
return ga.start()
def test_viewer_size(self, tmpdir):
# regression test for #781
# viewers were not restored with the right size
d1 = Data(x=np.random.random((2,) * self.ndim))
d2 = Data(x=np.random.random((2,) * self.ndim))
dc = DataCollection([d1, d2])
app = GlueApplication(dc)
w = app.new_data_viewer(self.widget_cls, data=d1)
w.viewer_size = (300, 400)
filename = tmpdir.join('session.glu').strpath
app.save_session(filename, include_data=True)
app2 = GlueApplication.restore_session(filename)
for viewer in app2.viewers:
assert viewer[0].viewer_size == (300, 400)
app.close()
app2.close()
h2cocube.label='H2CO 303202 Cube'
catalog = astropy_tabular_data(hpath('PPV_H2CO_Temperature.ipac'), format='ipac')
catalog.label='Fitted Catalog'
h2cocube.add_component(dendcube.get_component('structure'), 'structure')
dc = DataCollection(dendrogram)
dc.append(h2cocube)
dc.append(catalog)
dc.append(dendcube)
dc.merge(h2cocube,dendcube)
dc.merge(dendro, catalog)
app = GlueApplication(dc)
cube_viewer = app.new_data_viewer(ImageWidget)
cube_viewer.add_data(h2cocube)
h2cocube.join_on_key(dendro, 'structure', dendro.pixel_component_ids[0])
scatter = app.new_data_viewer(ScatterWidget)
scatter.add_data(dendro)
scatter.yatt = dendro.id['temperature_chi2']
scatter.xatt = catalog.id['r321303']
dendview = app.new_data_viewer(DendroWidget)
dendview.add_data(dendro)
subset_tem_bt_40_60 = ((catalog.id['temperature_chi2'] < 60) &
from glue.core.data_factories import load_data
from glue.core import DataCollection
from glue.core.link_helpers import LinkSame
from glue.qt.glue_application import GlueApplication
#load 2 datasets from files
image = load_data('w5.fits')
catalog = load_data('w5_psc.vot')
dc = DataCollection([image, catalog])
# link positional information
dc.add_link(LinkSame(image.id['World x: RA---TAN'], catalog.id['RAJ2000']))
dc.add_link(LinkSame(image.id['World y: DEC--TAN'], catalog.id['DEJ2000']))
#start Glue
app = GlueApplication(dc)
app.start()
from glue.core import Component
from glue.core import Data, DataCollection
from glue.qt.glue_application import GlueApplication
import numpy as np
import yt
from simple_fullres import ytSliceComponent
ds = yt.load("GasSloshing/sloshing_nomag2_hdf5_plt_cnt_0150")
d = Data(label=str(ds))
for field in ("density", "temperature", "velocity_x",
"velocity_y", "velocity_z"):
d.add_component(ytSliceComponent(ds, field), label=field)
dc = DataCollection(d)
ga = GlueApplication(dc)
ga.start()
'variables': ('B40', 'B30',),
'dimensions': {'X': {'range': (147.875, 148.125)},
'Y': {'range': (-37.0 + 0.875, -36.0 + 0.125)},
# 'T': {'range': (start_date, end_date),
# 'array_range': (0, 4)
# 'crs': 'SSE', # Seconds since epoch
# 'grouping_function': g.null_grouping
# }
}
}
# In[6]:
d = g.get_data(data_request_descriptor)
print "d shape: ", d['arrays']['B30'].shape
# plotContourf(d, 'B30')
# plotImages(d['arrays']['B30'])
# In[ ]:
from glue.core import Data, DataCollection
from glue.qt.glue_application import GlueApplication
44 # In[ ]:
my_data1 = Data(x=d['arrays']['B40'], label='B40')
collection = DataCollection([my_data1, ])
# collection.merge(my_data1,my_data2,my_data3)
app = GlueApplication(collection)
app.start()
def restore_session(gluefile):
"""Load a .glu file and return a DataCollection, Hub tuple"""
from glue.qt.glue_application import GlueApplication
return GlueApplication.restore(gluefile)
def setUp(self):
self.qapp = QApplication([""])
self.app = GlueApplication()
def restore_session(gluefile):
"""Load a .glu file and return a DataCollection, Hub tuple"""
from glue.qt.glue_application import GlueApplication
return GlueApplication.restore(gluefile)
def kms_to_ms(x):
return x * 1e3
dc.add_link(
LinkTwoWay(cube.id['Vrad'], catalog.id['center'], ms_to_kms, kms_to_ms))
subset_tem_lt_60 = (catalog.id['temperature_chi2'] < 60) & (
catalog.id['temperature_chi2'] > 10) & (catalog.id['area'] < 0.015)
subset_tem_gt_60 = (catalog.id['temperature_chi2'] > 60) & (catalog.id['area']
< 0.015)
app = GlueApplication(dc)
# plot x vs y, flip the x axis, log-scale y axis
scatter = app.new_data_viewer(ScatterWidget)
scatter.add_data(catalog)
scatter.yatt = catalog.id['temperature_chi2']
scatter.xatt = catalog.id['higaldusttem']
#scatter.xflip = True
#scatter.ylog = True
cube_viewer = app.new_data_viewer(ImageWidget)
cube_viewer.add_data(cube)
#cube_viewer.add_subset(subset_tem_lt_60)
#cube_viewer.add_subset(subset_tem_gt_60)
#cube_viewer.add_data(catalog)
dc = DataCollection([cube, catalog, cube2, cube3, higaltem]) dc.merge(cube,cube2,cube3) dc.add_link(LinkSame(cube.id['Galactic Longitude'], catalog.id['GLON'])) dc.add_link(LinkSame(cube.id['Galactic Latitude'], catalog.id['GLAT'])) def ms_to_kms(x): return x/1e3 def kms_to_ms(x): return x*1e3 dc.add_link(LinkTwoWay(cube.id['Vrad'], catalog.id['center'], ms_to_kms, kms_to_ms)) subset_tem_lt_60 = (catalog.id['temperature_chi2'] < 60) & (catalog.id['temperature_chi2'] > 10) & (catalog.id['area'] < 0.015) subset_tem_gt_60 = (catalog.id['temperature_chi2'] > 60) & (catalog.id['area'] < 0.015) app = GlueApplication(dc) # plot x vs y, flip the x axis, log-scale y axis scatter = app.new_data_viewer(ScatterWidget) scatter.add_data(catalog) scatter.yatt = catalog.id['temperature_chi2'] scatter.xatt = catalog.id['higaldusttem'] #scatter.xflip = True #scatter.ylog = True cube_viewer = app.new_data_viewer(ImageWidget) cube_viewer.add_data(cube) #cube_viewer.add_subset(subset_tem_lt_60) #cube_viewer.add_subset(subset_tem_gt_60) #cube_viewer.add_data(catalog)
nc = Component.autotyped(cc, units=uu)
catalog.add_component(nc, column_name)
# if column_name != 'parent' else '_flarent_'
catalog.join_on_key(dendro, '_idx', dendro.pixel_component_ids[0])
dc = DataCollection(dendrogram)
#dc = DataCollection([cube, dendrogram, catalog])
#dc.merge(cube,sncube)
#sncube.join_on_key(dendro, 'structure', dendro.pixel_component_ids[0])
#dc.merge(catalog, dendro)
# UNCOMMENT THIS LINE TO BREAK THE VIEWER
dc.append(catalog)
app = GlueApplication(dc)
cube_viewer = app.new_data_viewer(ImageWidget)
cube_viewer.add_data(sncube)
# link positional information
dc.add_link(LinkSame(sncube.id['structure'], catalog.id['_idx']))
#dc.add_link(LinkSame(image.id['World y: DEC--TAN'], catalog.id['DEJ2000']))
dc.add_link(LinkSame(cube.id['Galactic Longitude'], catalog.id['x_cen']))
dc.add_link(LinkSame(cube.id['Galactic Latitude'], catalog.id['y_cen']))
def ms_to_kms(x):
return x / 1e3
