本文整理汇总了Python中matplotlib.widgets.CheckButtons.is_checked方法的典型用法代码示例。如果您正苦于以下问题：Python CheckButtons.is_checked方法的具体用法？Python CheckButtons.is_checked怎么用？Python CheckButtons.is_checked使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.widgets.CheckButtons的用法示例。
在下文中一共展示了CheckButtons.is_checked方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: visualize_in_scan
# 需要导入模块: from matplotlib.widgets import CheckButtons [as 别名]
# 或者: from matplotlib.widgets.CheckButtons import is_checked [as 别名]
def visualize_in_scan(self, verbose=True):
"""
Interactive visualization of the slices of the scan along with scan
and annotation information. The visualization begins
(but is not limited to) the first slice where the nodule occurs
(according to the annotation). Contours are plotted atop the images
for visualization and can be toggled on and off.
"""
images = self.scan.load_all_dicom_images(verbose)
# Preload contours and sort them by z pos.
contours = sorted(self.contours, key=lambda c: c.image_z_position)
fnames = self.scan.sorted_dicom_file_names.split(',')
index_of_contour = [fnames.index(c.dicom_file_name) for c in contours]
fig = plt.figure(figsize=(16,8))
min_slice = min(index_of_contour)
max_slice = max(index_of_contour)
current_slice = min_slice
ax_image = fig.add_axes([0.5,0.0,0.5,1.0])
img = ax_image.imshow(images[current_slice].pixel_array,
cmap=plt.cm.gray)
contour_lines = []
# We draw all the contours initally and set the visibility
# to False. This works better than trying create and destroy
# plots every time we update the image.
for i,c in enumerate(contours):
arr = c.to_matrix()
cc, = ax_image.plot(arr[:,0], arr[:,1], '-r')
cc.set_visible(i==0) # Set the first contour visible.
contour_lines.append( cc )
ax_image.set_xlim(-0.5,511.5); ax_image.set_ylim(511.5,-0.5)
ax_image.axis('off')
# Add the scan info table
ax_scan_info = fig.add_axes([0.1, 0.8, 0.3, 0.1])
ax_scan_info.set_axis_bgcolor('w')
scan_info_table = ax_scan_info.table(
cellText=[
['Patient ID:', self.scan.patient_id],
['Slice thickness:', '%.3f mm' % self.scan.slice_thickness],
['Pixel spacing:', '%.3f mm'%self.scan.pixel_spacing]
],
loc='center', cellLoc='left'
)
# Remove the cell borders.
# It Seems like there should be an easier way to do this...
for cell in scan_info_table.properties()['child_artists']:
cell.set_color('w')
ax_scan_info.set_title('Scan Info')
ax_scan_info.set_xticks([])
ax_scan_info.set_yticks([])
# Add annotations / characteristics table.
ax_annotation_info = fig.add_axes([0.1, 0.45, 0.3, 0.25])
ax_annotation_info.set_axis_bgcolor('w')
# Create the rows to be displayed in the annotations table.
cell_text = []
for c in _all_characteristics_:
row = []
cname = c.capitalize()
if cname.startswith('Int'):
cname = 'InternalStructure'
row.append(cname)
row.append(getattr(self,cname)())
row.append(getattr(self,c))
cell_text.append(row)
annotation_info_table = ax_annotation_info.table(
cellText=cell_text,
loc='center', cellLoc='left', colWidths=[0.45,0.45,0.1]
)
# Again, remove cell borders.
for cell in annotation_info_table.properties()['child_artists']:
cell.set_color('w')
ax_annotation_info.set_title('Annotation Info')
ax_annotation_info.set_xticks([])
ax_annotation_info.set_yticks([])
# Add the checkbox for turning contours on / off.
ax_contour_checkbox = fig.add_axes([0.1, 0.25, 0.1, 0.15])
ax_contour_checkbox.set_axis_bgcolor('w')
contour_checkbox = CheckButtons(ax_contour_checkbox,
('Show Contours',), (True,))
contour_checkbox.is_checked = True
# Add the widgets.
ax_slice = fig.add_axes([0.1, 0.1, 0.3, 0.05])
ax_slice.set_axis_bgcolor('w')
txt = 'Z: %.3f'%float(images[current_slice].ImagePositionPatient[-1])
sslice = Slider(ax_slice,
#.........这里部分代码省略.........