class LiveImage(CallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
"""
def __init__(self, field, *, fs=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
if fs is None:
import filestore.api as fs
self.fs = fs
def event(self, doc):
uid = doc['data'][self.field]
data = self.fs.retrieve(uid)
self.update(data)
super().event(doc)
def update(self, data):
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
class LiveImage(CallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
Note
----
Requires a matplotlib fix that is not released as of this writing. The
relevant commit is a951b7.
"""
def __init__(self, field):
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
def event(self, doc):
uid = doc['data'][self.field]
data = fsapi.retrieve(uid)
self.cs.update_image(data)
self.cs._fig.canvas.draw()
self.cs._fig.canvas.flush_events()
class SRXLiveImage(CallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string name of data field in an Event
Note
----
Requires a matplotlib fix that is not released as of this writing. The
relevant commit is a951b7.
"""
def __init__(self, field):
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
def event(self, doc):
uid = doc['data'][self.field]
data = fsapi.retrieve(uid)
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
def __init__(self,
field,
*,
cmap=None,
norm=None,
limit_func=None,
auto_redraw=True,
interpolation=None,
window_title=None,
aspect='equal',
tofile=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
self.tofile = tofile
super().__init__()
fig = plt.figure()
self.field = field
self._plot_norm = norm
# the None field is supposed to be norm
self.cs = CrossSection(fig, cmap, None, limit_func, auto_redraw,
interpolation)
# not supported feature but do anyway...
# need to set aspect ratio!!!!
# (get rid of xray vision in the future...)
self.cs._im_ax.set_aspect(aspect)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
def _show_image(light, title):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
options = dict(cmap='gray', interpolation='nearest')
fig = plt.figure()
cs = CrossSection(fig)
cs.update_image(light)
# fig, axes = plt.subplots(1, 1, figsize=(4, 4))
# axes.imshow(light, **options)
cs._ax_h.set_title(title)
def _show_image(light, title):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
options = dict(cmap='gray', interpolation='nearest')
fig = plt.figure()
cs = CrossSection(fig)
cs.update_image(light)
# fig, axes = plt.subplots(1, 1, figsize=(4, 4))
# axes.imshow(light, **options)
cs._ax_h.set_title(title)
def __init__(self, field, *, fs=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
if fs is None:
import filestore.api as fs
self.fs = fs
class LiveImage(BrokerCallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
fs: Registry instance
The Registry instance to pull the data from
cmap : str, colormap, or None
color map to use. Defaults to gray
norm : Normalize or None
Normalization function to use
limit_func : callable, optional
function that takes in the image and returns clim values
auto_redraw : bool, optional
interpolation : str, optional
Interpolation method to use. List of valid options can be found in
CrossSection2DView.interpolation
"""
def __init__(self,
field,
*,
db=None,
cmap=None,
norm=None,
limit_func=None,
auto_redraw=True,
interpolation=None,
window_title=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__((field, ), db=db)
fig = plt.figure()
self.field = field
self.cs = CrossSection(fig, cmap, norm, limit_func, auto_redraw,
interpolation)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
def event(self, doc):
super().event(doc)
data = doc['data'][self.field]
self.update(data)
def update(self, data):
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
def __init__(self, field):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
class LiveImage(BrokerCallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
fs: Registry instance
The Registry instance to pull the data from
cmap : str, colormap, or None
color map to use. Defaults to gray
norm : Normalize or None
Normalization function to use
limit_func : callable, optional
function that takes in the image and returns clim values
auto_redraw : bool, optional
interpolation : str, optional
Interpolation method to use. List of valid options can be found in
CrossSection2DView.interpolation
"""
def __init__(self, field, *, db=None, cmap=None, norm=None,
limit_func=None, auto_redraw=True, interpolation=None,
window_title=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__((field,), db=db)
fig = plt.figure()
self.field = field
self.cs = CrossSection(fig, cmap, norm,
limit_func, auto_redraw, interpolation)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
def event(self, doc):
super().event(doc)
data = doc['data'][self.field]
self.update(data)
def update(self, data):
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
def __init__(self,
field,
*,
db=None,
cmap=None,
norm=None,
limit_func=None,
auto_redraw=True,
interpolation=None,
window_title=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__((field, ), db=db)
fig = plt.figure()
self.field = field
self.cs = CrossSection(fig, cmap, norm, limit_func, auto_redraw,
interpolation)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
def __init__(self, field, *, db=None, cmap=None, norm=None,
limit_func=None, auto_redraw=True, interpolation=None,
window_title=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__((field,), db=db)
fig = plt.figure()
self.field = field
self.cs = CrossSection(fig, cmap, norm,
limit_func, auto_redraw, interpolation)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
class LiveImage(CallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
"""
def __init__(self, field):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
def event(self, doc):
import filestore.api as fsapi
uid = doc['data'][self.field]
data = fsapi.retrieve(uid)
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
def descriptor(self, doc):
self.fields = [
k for k, v in doc["data_keys"].items()
if len(v["shape"]) == 2 or (len(v["shape"]) == 3 and len(
[dim for dim in v["shape"] if dim > 0]) == 2)
]
data_keys = doc["data_keys"]
if self.aspect is None:
aspects = []
for field in self.fields:
aspect_ratio = data_keys[field]["shape"][0] / data_keys[field][
"shape"][1]
if any(s == -1 for s in data_keys[field]["shape"]):
aspects.append('auto')
elif aspect_ratio > 1.25 or aspect_ratio < .75:
aspects.append('auto')
else:
aspects.append('equal')
else:
aspects = [self.aspect] * len(self.fields)
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
# only make new figure for new data otherwise use old data
for field, asp in zip(self.fields, aspects):
if field in self.cs_dict and plt.fignum_exists(
self.cs_dict[field]._fig.number):
continue
fig = plt.figure(field)
cs = CrossSection(
fig,
self.cmap,
self.norm,
self.limit_func,
self.auto_redraw,
self.interpolation,
aspect=asp,
)
cs._fig.canvas.set_window_title(field)
cs._fig.show()
self.cs_dict[field] = cs
def __init__(self, field):
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
def cli():
import argparse
parser = argparse.ArgumentParser(description='Plot image based on input file')
parser.add_argument('-d', '--dat_file', dest='dat_file', default='',
help ='input .dat file')
parser.add_argument('-g', '--graph', dest='graph', default='',
help='create graph', action='store_true')
parser.add_argument('-vp', '--vert_pos', dest='vert_pos', default='',
help='input vertical slice position', type=str)
parser.add_argument('-hp', '--horiz_pos', dest='horiz_pos', default='',
help='input horizontal slice position', type=str)
parser.add_argument('-vl', '--vert_label', dest='vert_label', default='',
help='input vertical label string', type=str)
parser.add_argument('-hl', '--horiz_label', dest='horiz_label', default='',
help='input horizontal label string', type=str)
parser.add_argument('-e', '--extent_labels', dest='extent_labels', default=None,
help='input extent labels for image ranges', nargs='+', type=int)
parser.add_argument('-t', '--title', dest='title',default=None,
help='input title', type=str)
args = parser.parse_args()
initial_data = {'photon': {}, 'horizontal': {}, 'vertical': {},}
matrix = [[]]
try:
get_parameters(initial_data, file_name=args.dat_file)
except:
print('no data file found - specify with (-d <filename>)')
quit()
horizontal = initial_data['horizontal']['points']
vertical = initial_data['vertical']['points']
if args.graph and args.dat_file:
import matplotlib.pyplot as plt
from xray_vision.backend.mpl.cross_section_2d import CrossSection
img = np.loadtxt(args.dat_file)
img = img.reshape((vertical, horizontal))
fig = plt.figure()
kwargs = {'fig': fig}
if args.vert_pos:
if args.vert_pos == 'right':
args.vert_pos = 'right'
kwargs['vert_loc'] = args.vert_pos
if args.horiz_pos:
if args.horiz_pos == 'bottom':
args.horiz_pos = 'bottom'
kwargs['horiz_loc'] = args.horiz_pos
if args.vert_label:
kwargs['vert_label'] = args.vert_label
if args.horiz_label:
kwargs['horiz_label'] = args.horiz_label
if args.extent_labels:
kwargs['extent_labels'] = args.extent_labels
if args.title:
kwargs['title'] = args.title
cs = CrossSection(**kwargs)
cs.update_image(img)
plt.show()
else:
if args.dat_file:
file = args.dat_file
matrix = populate_matrix_smart(matrix, horizontal, vertical, data_file=file)
print(initial_data)
class LiveImage(CallbackBase):
"""
Stream 2D images in a cross-section viewer.
Parameters
----------
field : string
name of data field in an Event
fs: Registry instance
The Registry instance to pull the data from
cmap : str, colormap, or None
color map to use. Defaults to gray
norm : Normalize or None
Normalization function to use
limit_func : callable, optional
function that takes in the image and returns clim values
auto_redraw : bool, optional
interpolation : str, optional
Interpolation method to use. List of valid options can be found in
CrossSection2DView.interpolation
"""
def __init__(self,
field,
*,
cmap=None,
norm=None,
limit_func=None,
auto_redraw=True,
interpolation=None,
window_title=None,
aspect='equal',
tofile=None):
from xray_vision.backend.mpl.cross_section_2d import CrossSection
import matplotlib.pyplot as plt
self.tofile = tofile
super().__init__()
fig = plt.figure()
self.field = field
self._plot_norm = norm
# the None field is supposed to be norm
self.cs = CrossSection(fig, cmap, None, limit_func, auto_redraw,
interpolation)
# not supported feature but do anyway...
# need to set aspect ratio!!!!
# (get rid of xray vision in the future...)
self.cs._im_ax.set_aspect(aspect)
if window_title:
self.cs._fig.canvas.set_window_title(window_title)
self.cs._fig.show()
def event(self, doc):
super().event(doc)
if self.field in doc['data']:
print("field : {}".format(self.field))
data = doc['data'][self.field]
if self._plot_norm is not None:
data = self._plot_norm(data)
self.update(data)
if self.tofile is not None:
plt.savefig(self.tofile)
def update(self, data):
self.cs.update_image(data)
self.cs._fig.canvas.draw_idle()
def __init__(self, field):
super().__init__()
self.field = field
fig = plt.figure()
self.cs = CrossSection(fig)
self.cs._fig.show()
if args.horiz_pos:
if args.horiz_pos == 'bottom':
args.horiz_pos = 'bottom'
kwargs['horiz_loc'] = args.horiz_pos
if args.vert_label:
kwargs['vert_label'] = args.vert_label
if args.horiz_label:
kwargs['horiz_label'] = args.horiz_label
if args.extent_labels:
kwargs['extent_labels'] = args.extent_labels
cs = CrossSection(**kwargs)
cs.update_image(img)
plt.show()
else:
matrix = populate_matrix_smart(matrix, horizontal, vertical)
fig = plt.figure(figsize=(8, 10))
title = f'After Propagation (E={initial_data["photon"]["initial_energy"]} {initial_data["photon"]["units"]})'
axis_data = [
initial_data['horizontal']['axis_label'] + " [µm]",
initial_data['vertical']['axis_label'] + " [µm]",
"Intensity " + initial_data['intensity']
]
cs = CrossSection(fig,
horiz_loc='top',
vert_loc='right',
