def do_plot(fig, file):
img = ctx.open_file(file)
ax = fig.subplots()
if align:
ctx.align(img)
if preprocess:
ctx.pre_process(img)
prj = ctx.get_projection(img)
plotutils.imshow_image(ax, img, projection=prj, **kwargs)
if not align:
core_offset = ctx.get_core_offset()
if core_offset is not None:
x, y = core_offset.get(img.get_epoch())
x, y = prj.s2p([x, y])
# print core_offset, x, y
ax.scatter(x, y, marker='*', s=40, c=plotutils.black)
# if not preprocess:
# bg_mask = imgutils.Image(np.zeros_like(img.data, dtype=np.int8))
# bg = ctx.get_bg(bg_mask)
# if bg is not None and isinstance(bg, np.ndarray):
# bg.fill(1)
if ctx.get_mask() is not None and show_mask is True:
mask = ctx.get_mask()
ctx.pre_process(mask)
ax.contour(mask.data, [0.5])
for region in show_regions:
plotutils.plot_region(ax, region, prj, text=True)
def plot_displacements(ax, features1, features2, delta_info, num=False, projection=None, mode='com',
bg=None, beam=True, cmap=None, **kwargs):
"""Display displacements of features on a map.
If bg is not set and features1 and features2 are both SegmentedImage, a two color map,
one color for the segments of each SegmentedImage, will be used as bg.
Parameters
----------
ax : :class:`matplotlib.axes.Axes`
features1 : :class:`wise.features.FeaturesGroup`
The features of the first epoch.
features2 : :class:`wise.features.FeaturesGroup`
The features of the second epoch.
delta_info : :class:`wise.features.DeltaInformation`
An object containing the displacements information.
num : bool, optional
Whatever to optionally annotate the segments with there ids.
projection : :class:`libwise.imgutils.Projection`, optional
mode : str, optional
Coord mode for the location of the features: 'lm', 'com' or 'cos'.
bg : :class:`libwise.imgutils.Image`, optional
The image to be used as background map.
beam : bool, optional
Whatever to optionally display the beam of the image. Default is True.
cmap : :class:`matplotlib.cm.ColorMap` or str, optional
A color map for the background map.
**kwargs:
Additional arguments to be passed to :func:`plot_displacement_vector`
.. _tags: plt_matching
"""
alpha = 0.8
if isinstance(features1, wds.SegmentedImages):
projection = plotutils.get_projection(features1.get_img(), projection)
if bg is None:
data = ((features1.get_labels() > 1) * 2 + (features2.get_labels() > 1) * 4).astype(np.int8)
bg = imgutils.Image.from_image(features1.get_img(), data)
alpha = 0.5
else:
assert bg is not None
assert projection is not None
contour = False
cmap = plotutils.get_cmap(cmap)
plotutils.imshow_image(ax, bg, projection=projection, beam=beam, title=False,
alpha=0.8, cmap=cmap)
if num:
plot_segmentid(ax, features1)
plot_features(ax, features1, mode=mode, c=plotutils.blue, alpha=0.8)
plot_features(ax, features2, mode=mode, c=plotutils.orange, alpha=0.8)
plot_displacement_vector(ax, delta_info, mode=mode, fc='k', ec='k', **kwargs)
plot_segments_contour(ax, features1, colors=plotutils.dblue)
plot_segments_contour(ax, features2, colors=plotutils.red)
def do_plot(fig):
ax = fig.subplots()
plotutils.imshow_image(ax, stack_img, projection=ctx.get_projection(stack_img),
intensity_colorbar=intensity_colorbar, **kwargs)
if ctx.get_mask() is not None and show_mask is True:
ax.contour(ctx.get_mask().data, [0.5])
for region in show_regions:
plotutils.plot_region(ax, region, ctx.get_projection(stack_img), text=False, fill=True)
def after_update(self, result):
self.ax1.clear()
self.ax2.clear()
scale = int(self.scale.get())
plotutils.imshow_image(self.ax1, self.img.get(), title=False, norm=plotutils.Normalize())
self.ax1.set_title('Original')
plotutils.imshow_image(self.ax2, result[scale - 1], title=False, norm=plotutils.Normalize())
self.ax2.set_title('Scale %s' % scale)
self.view.draw()
def plot_ms_set_map(ax, img, ms_set, projection, mode='com', color_style='date', colorbar_setting=None,
map_cmap='jet', **kwargs):
"""Display all features of ms_set on a map.
Parameters
----------
ax : :class:`matplotlib.axes.Axes`
img : Image
An image to be used as background map.
ms_set : :class:`wise.wds.MultiScaleImageSet`
An object containing all the features to be displayed.
projection : :class:`libwise.imgutils.Projection`
mode : str, optional
Coord mode for the location of the features: 'lm', 'com' or 'cos'.
color_style : str, optional
'scale': display one color per scale. 'date': color correspond to the epoch.
colorbar_setting : :class:`libwise.ColorbarSetting, optional
Settings for the color bar if color_style is 'date'.
map_cmap : :class:`matplotlib.cm.ColorMap` or str, optional
**kwargs :
Additional arguments to be passed to :func:`libwise.plotutils.imshow_image`.
.. _tags: plt_detection
"""
if colorbar_setting is None and color_style == 'date':
colorbar_setting = plotutils.ColorbarSetting(ticks_locator=mdates.AutoDateLocator(),
ticks_formatter=mdates.DateFormatter('%m/%y'))
epochs = ms_set.get_epochs()
intensities = [k.get_intensity() for k in ms_set.features_iter()]
int_norm = plotutils.Normalize(min(intensities), max(intensities))
marker_select = plotutils.MarkerSelector()
epochs_map = plotutils.build_epochs_mappable(epochs, colorbar_setting.get_cmap())
if img is not None:
plotutils.imshow_image(ax, img, projection=projection, title=False, cmap=plotutils.get_cmap(map_cmap), **kwargs)
color_fct = None
if color_style == 'date':
color_fct = lambda f: epochs_map.to_rgba(f.get_epoch())
colorbar_setting.add_colorbar(epochs_map, ax)
elif color_style is 'scale':
pass
for ms_segments in ms_set:
for segments in ms_segments:
# if segments.get_scale() != 2:
# continue
s = 10 * segments.get_scale()
marker = marker_select.get(segments.get_scale())
# s = 500 * int_norm(segments.get_intensities())
# s = 200
plot_features(ax, segments, mode=mode, color_fct=color_fct, s=s, alpha=0.7, marker=marker)
def after_update(self, result):
self.ax1.clear()
self.ax2.clear()
scale = int(self.scale.get())
plotutils.imshow_image(self.ax1,
self.img.get(),
title=False,
norm=plotutils.Normalize())
self.ax1.set_title('Original')
plotutils.imshow_image(self.ax2,
result[scale - 1],
title=False,
norm=plotutils.Normalize())
self.ax2.set_title('Scale %s' % scale)
self.view.draw()
def do_plot(fig):
ax_all = fig.subplots()
plotutils.imshow_image(ax_all, ref_img, projection=projection, **img_kargs)
if region_list is not None:
for region, gdata in data.df.groupby('region'):
features = wds.DatedFeaturesGroupScale(0, features=gdata.features.values)
wiseutils.plot_features(ax_all, features, mode='com', c=region.get_color(), label=region.get_name())
plotutils.plot_region(ax_all, region, projection=projection, text=False,
color=region.get_color(), fill=True)
else:
features = wds.DatedFeaturesGroupScale(0, features=data.df.features.values)
wiseutils.plot_features(ax_all, features, mode='com')
if legend:
ax_all.legend(loc='best')
def after_update(self, result):
print "Start update"
img, noisy, denoised = result
for ax in [self.ax1, self.ax2, self.ax3]:
ax.clear()
plotutils.imshow_image(self.ax1,
img,
title=False,
norm=plotutils.Normalize())
self.ax1.set_title('Original')
plotutils.imshow_image(self.ax2,
noisy,
title=False,
norm=plotutils.Normalize())
self.ax2.set_title('Original + noise')
plotutils.imshow_image(self.ax3,
denoised,
title=False,
norm=plotutils.Normalize())
self.ax3.set_title('Denoised')
self.view.figure.tight_layout()
self.view.draw()
print "Done update"
def imshow_segmented_image(ax, segmented_image, projection=None, title=True, beam=True, num=False,
bg=None, mode='com', **kwargs):
"""Display the segmented image on the axes.
Parameters
----------
ax : :class:`matplotlib.axes.Axes`
segmented_image : :class:`wise.wds.SegmentedImages`
projection : :class:`libwise.imgutils.Projection`, optional
title : bool, optional
Whatever to optionally display a title. Default is True.
beam : bool, optional
Whatever to optionally display the beam of the image. Default is True.
num : bool, optional
Whatever to optionally annotate the segments with there ids. Default is False.
bg : :class:`libwise.imgutils.Image`, optional
Diplay bg as background image instead of the on from segmented_image.
mode : str, optional
Coord mode for the location of the features: 'lm', 'com' or 'cos'.
**kwargs :
Additional arguments to be passed to :func:`libwise.plotutils.imshow_image`.
.. _tags: plt_detection
"""
if bg is None:
bg = segmented_image.get_img()
prj = plotutils.imshow_image(ax, bg, projection=projection, title=False, beam=beam, **kwargs)
if title is True:
title = "Segmented image"
if isinstance(segmented_image, wds.AbstractScale):
title += " at scale %s" % prj.get_sky(segmented_image.get_scale())
if len(segmented_image.get_img().get_title()) > 0:
title += "\n%s" % segmented_image.get_img().get_title()
ax.set_title(title)
plot_segments_contour(ax, segmented_image)
plot_features(ax, segmented_image, num=num, c=plotutils.orange, mode=mode)
def preview_detection_stack(ctx, stack_detection_name, count_threshold=0, ms_set=None,
date_filter=None, show_regions=[]):
''' Plot detection in stack'''
stack = plotutils.FigureStack()
stack_img, img_snr, img_count = load_detection_stack_image(ctx, stack_detection_name, preprocess=True)
img_snr.data[img_count.data < count_threshold] = 0
img_count.data[img_count.data < count_threshold] = 0
prj = ctx.get_projection(stack_img)
fig, ax = stack.add_subplots("Stack image")
plotutils.imshow_image(ax, stack_img, projection=prj)
for region in show_regions:
plotutils.plot_region(ax, region, prj, text=True)
fig, ax1 = stack.add_subplots("Stack detection SNR")
plotutils.imshow_image(ax1, img_snr, projection=prj, cmap=plotutils.get_cmap('jet'))
for region in show_regions:
plotutils.plot_region(ax1, region, prj, text=True)
fig, ax2 = stack.add_subplots("Stack detection count")
plotutils.imshow_image(ax2, img_count, projection=prj, cmap=plotutils.get_cmap('jet'))
for region in show_regions:
plotutils.plot_region(ax2, region, prj, text=True)
if ms_set is not None:
colorbar_setting = plotutils.ColorbarSetting(cmap='jet', ticks_locator=mdates.AutoDateLocator(),
ticks_formatter=mdates.DateFormatter('%m/%y'))
def feature_filter(feature):
if img_snr.data[tuple(feature.get_coord())] == 0:
return False
if date_filter is not None and not date_filter(feature.get_epoch()):
return False
return True
ms_set = wds.MultiScaleImageSet.from_file(os.path.join(ctx.get_data_dir(), j),
feature_filter=feature_filter)
plot_ms_set_map(ax1, None, ms_set, prj, colorbar_setting=colorbar_setting)
plot_ms_set_map(ax2, None, ms_set, prj, colorbar_setting=colorbar_setting)
add_features_tooltip(stack, ax1, ms_set.features_iter(), projection=prj, epoch=True, tol=1)
add_features_tooltip(stack, ax2, ms_set.features_iter(), projection=prj, epoch=True, tol=1)
stack.show()
def after_update(self, result):
print "Start update"
img, noisy, denoised = result
for ax in [self.ax1, self.ax2, self.ax3]:
ax.clear()
plotutils.imshow_image(self.ax1, img, title=False, norm=plotutils.Normalize())
self.ax1.set_title('Original')
plotutils.imshow_image(self.ax2, noisy, title=False, norm=plotutils.Normalize())
self.ax2.set_title('Original + noise')
plotutils.imshow_image(self.ax3, denoised, title=False, norm=plotutils.Normalize())
self.ax3.set_title('Denoised')
self.view.figure.tight_layout()
self.view.draw()
print "Done update"
def __init__(self, img, prj=None, max_ds=10, current_folder=None):
self.max_ds = max_ds
self.showverts = True
self.current_folder = current_folder
uiutils.UI.__init__(self, 750, 600, "PolyRegion Editor")
vbox = QtGui.QVBoxLayout()
self.setLayout(vbox)
canva_box = QtGui.QHBoxLayout()
vbox.addLayout(canva_box)
self.canvas = plotutils.BaseCustomCanvas()
canva_box.addWidget(self.canvas)
ctl = QtGui.QHBoxLayout()
vbox.addLayout(ctl)
ctl.addWidget(plotutils.NavigationToolbar(self.canvas, self))
self.title_entry = uiutils.EntryDescription("Title")
ctl.addWidget(self.title_entry)
self.color_entry = uiutils.EntryDescription("Color")
ctl.addWidget(self.color_entry)
save_bn = QtGui.QPushButton("Save")
save_bn.clicked.connect(self.on_save_clicked)
ctl.addWidget(save_bn)
load_bn = QtGui.QPushButton("Load")
load_bn.clicked.connect(self.on_load_clicked)
ctl.addWidget(load_bn)
save_bn = QtGui.QPushButton("New")
save_bn.clicked.connect(self.on_new_clicked)
ctl.addWidget(save_bn)
self.ax = self.canvas.figure.subplots()
if prj is None:
prj = img.get_projection()
self.prj = prj
self.img = img
plotutils.imshow_image(self.ax, self.img, projection=self.prj, title=False)
self.poly = Polygon([[0, 0]], animated=True,
fc='b', ec='none', alpha=0.4)
self.ax.add_patch(self.poly)
self.ax.set_clip_on(False)
self.ax.set_title("Click and drag a point to move it; "
"'i' to insert; 'd' to delete.")
x, y = zip(*self.poly.xy)
self.line = plt.Line2D(x, y, color='none', marker='o', mfc='r',
alpha=0.8, animated=True, lw=2, markersize=self.max_ds)
self._update_line()
self.ax.add_line(self.line)
self.poly.add_callback(self.poly_changed)
self._ind = None # the active vert
canvas = self.poly.figure.canvas
canvas.mpl_connect('draw_event', self.draw_callback)
canvas.mpl_connect('button_press_event', self.button_press_callback)
canvas.mpl_connect('button_release_event', self.button_release_callback)
canvas.mpl_connect('key_press_event', self.key_press_callback)
canvas.mpl_connect('motion_notify_event', self.motion_notify_callback)
self.canvas = canvas
self.load_default()
self.canvas.setFocus()
def plot_links_map(ax, img, projection, links, color_style='link', mode='com', colorbar_setting=None,
map_cmap='jet', vector_width=4, link_id_label=False, num_bbox=None,
ang_vel_arrows=False, ang_vel_unit=u.mas / u.year, pix_per_ang_vel_unit=1, **kwargs):
"""Display features links on a map.
Parameters
----------
ax : :class:`matplotlib.axes.Axes`
img : Image
An image to be used as background map.
projection : :class:`libwise.imgutils.Projection`
links : a list of :class:`wise.matcher.FeaturesLink`
color_style : str, optional
'link': one color per link.
'date': map the features epochs to a color.
any color string: use one color for each displacements vectors.
function: a function that take a feature as argument and return a color.
mode : str, optional
Coord mode for the location of the features: 'lm', 'com' or 'cos'.
colorbar_setting : ColorBar, optional
Settings for the color bar if color_style is 'date'.
map_cmap : :class:`matplotlib.cm.ColorMap` or str, optional
vector_width : int, optional
Width of the displacements vector arrows. Default is 4.
link_id_label : bool, optional
Annotate the links with there ids.
num_bbox : dict, optional
**kwargs:
Additional arguments to be passed to :func:`libwise.plotutils.imshow_image`.
.. _tags: plt_matching
"""
color_fct = None
if color_style == 'date':
all_epochs = matcher.get_all_epochs(links)
epochs_map = plotutils.build_epochs_mappable(all_epochs, colorbar_setting.get_cmap())
if colorbar_setting is None:
colorbar_setting = plotutils.ColorbarSetting(ticks_locator=mdates.AutoDateLocator(),
ticks_formatter=mdates.DateFormatter('%m/%y'))
colorbar_setting.add_colorbar(epochs_map, ax)
color_fct = lambda f: epochs_map.to_rgba(f.get_epoch())
elif color_style is not 'link' and isinstance(color_style, str):
color_fct = lambda f: color_style
elif nputils.is_callable(color_style):
color_fct = color_style
plotutils.imshow_image(ax, img, projection=projection, title=False, cmap=plotutils.get_cmap(map_cmap), **kwargs)
for link in links:
delta_info = link.get_delta_info(measured_delta=False)
if ang_vel_arrows:
plot_velocity_vector(ax, delta_info, projection, ang_vel_unit, pix_per_ang_vel_unit,
color_fct=color_fct, mode=mode, lw=0.5,
fc=link.get_color(), ec='k', alpha=0.9, zorder=link.size(), width=vector_width)
else:
plot_displacement_vector(ax, delta_info, color_fct=color_fct, mode=mode, lw=0.5,
fc=link.get_color(), ec='k', alpha=0.9, zorder=link.size(), width=vector_width)
# y, x = link.get_features()[int(np.random.normal(s / 2, s / 4))].get_coord()
if link_id_label:
y, x = link.last().get_coord()
if num_bbox is None:
props = dict(boxstyle='round', facecolor='wheat', alpha=0.7, edgecolor=link.get_color(), lw=1.5)
ax.text(x, y, link.get_id(), bbox=num_bbox, zorder=200, size='small')
def __init__(self, img, prj=None, max_ds=10, current_folder=None):
self.max_ds = max_ds
self.showverts = True
self.current_folder = current_folder
uiutils.UI.__init__(self, 750, 600, "PolyRegion Editor")
vbox = QtGui.QVBoxLayout()
self.setLayout(vbox)
canva_box = QtGui.QHBoxLayout()
vbox.addLayout(canva_box)
self.canvas = plotutils.BaseCustomCanvas()
canva_box.addWidget(self.canvas)
ctl = QtGui.QHBoxLayout()
vbox.addLayout(ctl)
ctl.addWidget(plotutils.NavigationToolbar(self.canvas, self))
self.title_entry = uiutils.EntryDescription("Title")
ctl.addWidget(self.title_entry)
self.color_entry = uiutils.EntryDescription("Color")
ctl.addWidget(self.color_entry)
save_bn = QtGui.QPushButton("Save")
save_bn.clicked.connect(self.on_save_clicked)
ctl.addWidget(save_bn)
load_bn = QtGui.QPushButton("Load")
load_bn.clicked.connect(self.on_load_clicked)
ctl.addWidget(load_bn)
save_bn = QtGui.QPushButton("New")
save_bn.clicked.connect(self.on_new_clicked)
ctl.addWidget(save_bn)
self.ax = self.canvas.figure.subplots()
if prj is None:
prj = img.get_projection()
self.prj = prj
self.img = img
plotutils.imshow_image(self.ax, self.img, projection=self.prj, title=False)
self.poly = Polygon([[0, 0]], animated=True,
fc='b', ec='none', alpha=0.4)
self.ax.add_patch(self.poly)
self.ax.set_clip_on(False)
self.ax.set_title("Click and drag a point to move it; "
"'i' to insert; 'd' to delete.")
x, y = zip(*self.poly.xy)
self.line = plt.Line2D(x, y, color='none', marker='o', mfc='r',
alpha=0.8, animated=True, lw=2, markersize=self.max_ds)
self._update_line()
self.ax.add_line(self.line)
self.poly.add_callback(self.poly_changed)
self._ind = None # the active vert
canvas = self.poly.figure.canvas
canvas.mpl_connect('draw_event', self.draw_callback)
canvas.mpl_connect('button_press_event', self.button_press_callback)
canvas.mpl_connect('button_release_event', self.button_release_callback)
canvas.mpl_connect('key_press_event', self.key_press_callback)
canvas.mpl_connect('motion_notify_event', self.motion_notify_callback)
self.canvas = canvas
self.load_default()
self.canvas.setFocus()
