mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 12:58:49 +08:00
Andreas Mueller
251 lines
8.3 KiB
Python
251 lines
8.3 KiB
Python
import numpy as np
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import scipy.ndimage as ndi
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from skimage.util.dtype import dtype_range
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from .plotplugin import PlotPlugin
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__all__ = ['LineProfile']
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#TODO: Extract line tool and add it to a new `canvastools` subpackage.
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class LineProfile(PlotPlugin):
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"""Plugin to compute interpolated intensity under a scan line on an image.
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See PlotPlugin and Plugin classes for additional details.
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Parameters
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----------
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linewidth : float
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Line width for interpolation. Wider lines average over more pixels.
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epsilon : float
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Maximum pixel distance allowed when selecting end point of scan line.
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limits : tuple or {None, 'image', 'dtype'}
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(minimum, maximum) intensity limits for plotted profile. The following
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special values are defined:
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None : rescale based on min/max intensity along selected scan line.
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'image' : fixed scale based on min/max intensity in image.
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'dtype' : fixed scale based on min/max intensity of image dtype.
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"""
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name = 'Line Profile'
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draws_on_image = True
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def __init__(self, linewidth=1, epsilon=5, limits='image', **kwargs):
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super(LineProfile, self).__init__(**kwargs)
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self.linewidth = linewidth
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self.epsilon = epsilon
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self._active_pt = None
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self._limit_type = limits
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self.line_kwargs = dict(color='y', lw=linewidth, alpha=0.5, marker='s',
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markersize=5, solid_capstyle='butt')
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print self.help()
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def attach(self, image_viewer):
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super(LineProfile, self).attach(image_viewer)
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image = image_viewer.original_image
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if self._limit_type == 'image':
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self.limits = (np.min(image), np.max(image))
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elif self._limit_type == 'dtype':
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self.self._limit_type = dtype_range[image.dtype.type]
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elif self._limit_type is None or len(self._limit_type) == 2:
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self.limits = self._limit_type
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else:
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raise ValueError("Unrecognized `limits`: %s" % self._limit_type)
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if not self._limit_type is None:
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self.ax.set_ylim(self.limits)
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h, w = image.shape
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self._init_end_pts = np.array([[w / 3, h / 2], [2 * w / 3, h / 2]])
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self.end_pts = self._init_end_pts.copy()
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x, y = np.transpose(self.end_pts)
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self.scan_line = image_viewer.ax.plot(x, y, **self.line_kwargs)[0]
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self.artists.append(self.scan_line)
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scan_data = profile_line(image, self.end_pts)
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self.profile = self.ax.plot(scan_data, 'k-')[0]
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self._autoscale_view()
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self.connect_image_event('key_press_event', self.on_key_press)
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self.connect_image_event('button_press_event', self.on_mouse_press)
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self.connect_image_event('button_release_event', self.on_mouse_release)
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self.connect_image_event('motion_notify_event', self.on_move)
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self.connect_image_event('scroll_event', self.on_scroll)
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self.image_viewer.redraw()
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def help(self):
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helpstr = ("Line profile tool",
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"+ and - keys or mouse scroll changes width of scan line.",
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"Select and drag ends of the scan line to adjust it.")
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return '\n'.join(helpstr)
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def get_profile(self):
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"""Return intensity profile of the selected line.
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Returns
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-------
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end_pts: (2, 2) array
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The positions ((x1, y1), (x2, y2)) of the line ends.
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profile: 1d array
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Profile of intensity values.
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"""
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end_pts = self.scan_line.get_xydata()
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profile = self.profile.get_ydata()
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return end_pts, profile
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def on_scroll(self, event):
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if not event.inaxes:
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return
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if event.button == 'up':
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self._thicken_scan_line()
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elif event.button == 'down':
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self._shrink_scan_line()
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def on_key_press(self, event):
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if not event.inaxes:
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return
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elif event.key == '+':
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self._thicken_scan_line()
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elif event.key == '-':
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self._shrink_scan_line()
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elif event.key == 'r':
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self.reset()
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def _thicken_scan_line(self):
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self.linewidth += 1
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self.line_changed(None, None)
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def _shrink_scan_line(self):
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if self.linewidth > 1:
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self.linewidth -= 1
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self.line_changed(None, None)
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def _autoscale_view(self):
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if self.limits is None:
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self.ax.autoscale_view(tight=True)
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else:
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self.ax.autoscale_view(scaley=False, tight=True)
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def get_pt_under_cursor(self, event):
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"""Return index of the end point under cursor, if sufficiently close"""
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xy = np.asarray(self.scan_line.get_xydata())
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xyt = self.scan_line.get_transform().transform(xy)
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xt, yt = xyt[:, 0], xyt[:, 1]
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d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
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indseq = np.nonzero(np.equal(d, np.amin(d)))[0]
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ind = indseq[0]
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if d[ind] >= self.epsilon:
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ind = None
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return ind
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def on_mouse_press(self, event):
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if event.button != 1:
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return
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if event.inaxes == None:
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return
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self._active_pt = self.get_pt_under_cursor(event)
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def on_mouse_release(self, event):
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if event.button != 1:
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return
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self._active_pt = None
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def on_move(self, event):
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if event.button != 1:
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return
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if self._active_pt is None:
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return
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if not self.image_viewer.ax.in_axes(event):
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return
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x, y = event.xdata, event.ydata
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self.line_changed(x, y)
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def reset(self):
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self.end_pts = self._init_end_pts.copy()
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self.scan_line.set_data(np.transpose(self.end_pts))
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self.line_changed(None, None)
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def line_changed(self, x, y):
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if x is not None:
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self.end_pts[self._active_pt, :] = x, y
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self.scan_line.set_data(np.transpose(self.end_pts))
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self.scan_line.set_linewidth(self.linewidth)
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scan = profile_line(self.image_viewer.original_image, self.end_pts,
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linewidth=self.linewidth)
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self.profile.set_xdata(np.arange(scan.shape[0]))
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self.profile.set_ydata(scan)
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self.ax.relim()
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if self.useblit:
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self.image_viewer.canvas.restore_region(self.img_background)
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self.ax.draw_artist(self.scan_line)
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self.ax.draw_artist(self.profile)
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self.image_viewer.canvas.blit(self.image_viewer.ax.bbox)
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self._autoscale_view()
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self.image_viewer.redraw()
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self.redraw()
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def profile_line(img, end_pts, linewidth=1):
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"""Return the intensity profile of an image measured along a scan line.
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Parameters
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----------
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img : 2d array
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The image.
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end_pts: (2, 2) list
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End points ((x1, y1), (x2, y2)) of scan line.
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linewidth: int
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Width of the scan, perpendicular to the line
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Returns
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-------
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return_value : array
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The intensity profile along the scan line. The length of the profile
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is the ceil of the computed length of the scan line.
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"""
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point1, point2 = end_pts
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x1, y1 = point1 = np.asarray(point1, dtype=float)
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x2, y2 = point2 = np.asarray(point2, dtype=float)
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dx, dy = point2 - point1
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# Quick calculation if perfectly horizontal or vertical (remove?)
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if x1 == x2:
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pixels = img[min(y1, y2): max(y1, y2) + 1,
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x1 - linewidth / 2: x1 + linewidth / 2 + 1]
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intensities = pixels.mean(axis=1)
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return intensities
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elif y1 == y2:
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pixels = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1,
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min(x1, x2): max(x1, x2) + 1]
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intensities = pixels.mean(axis=0)
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return intensities
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theta = np.arctan2(dy, dx)
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a = dy / dx
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b = y1 - a * x1
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length = np.hypot(dx, dy)
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line_x = np.linspace(min(x1, x2), max(x1, x2), np.ceil(length))
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line_y = line_x * a + b
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y_width = abs(linewidth * np.cos(theta) / 2)
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perp_ys = np.array([np.linspace(yi - y_width,
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yi + y_width, linewidth) for yi in line_y])
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perp_xs = - a * perp_ys + (line_x + a * line_y)[:, np.newaxis]
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perp_lines = np.array([perp_ys, perp_xs])
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pixels = ndi.map_coordinates(img, perp_lines)
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intensities = pixels.mean(axis=1)
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return intensities
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