mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 17:53:25 +08:00
Josh Warner (Mac)
210 lines
6.7 KiB
Python
210 lines
6.7 KiB
Python
import warnings
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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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from ..canvastools import ThickLineTool
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__all__ = ['LineProfile']
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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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maxdist : float
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Maximum pixel distance allowed when selecting end point of scan line.
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epsilon : float
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Deprecated. Use `maxdist` instead.
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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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def __init__(self, maxdist=10, epsilon='deprecated',
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limits='image', **kwargs):
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super(LineProfile, self).__init__(**kwargs)
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if not epsilon == 'deprecated':
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warnings.warn("Parameter `epsilon` deprecated; use `maxdist`.")
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maxdist = epsilon
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self.maxdist = maxdist
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self._limit_type = limits
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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._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[0:2]
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x = [w / 3, 2 * w / 3]
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y = [h / 2] * 2
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self.line_tool = ThickLineTool(self.image_viewer.ax,
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maxdist=self.maxdist,
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on_move=self.line_changed,
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on_change=self.line_changed)
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self.line_tool.end_points = np.transpose([x, y])
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scan_data = profile_line(image, self.line_tool.end_points)
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self.reset_axes(scan_data)
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self._autoscale_view()
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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_profiles(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_points: (2, 2) array
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The positions ((x1, y1), (x2, y2)) of the line ends.
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profile: list of 1d arrays
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Profile of intensity values. Length 1 (grayscale) or 3 (rgb).
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"""
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profiles = [data.get_ydata() for data in self.profile]
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return self.line_tool.end_points, profiles
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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 line_changed(self, end_points):
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x, y = np.transpose(end_points)
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self.line_tool.end_points = end_points
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scan = profile_line(self.image_viewer.original_image, end_points,
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linewidth=self.line_tool.linewidth)
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if scan.shape[1] != len(self.profile):
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self.reset_axes(scan)
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for i in range(len(scan[0])):
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self.profile[i].set_xdata(np.arange(scan.shape[0]))
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self.profile[i].set_ydata(scan[:, i])
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self.ax.relim()
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self._autoscale_view()
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self.redraw()
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def reset_axes(self, scan_data):
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# Clear lines out
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for line in self.ax.lines:
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self.ax.lines = []
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if scan_data.shape[1] == 1:
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self.profile = self.ax.plot(scan_data, 'k-')
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else:
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self.profile = self.ax.plot(scan_data[:, 0], 'r-',
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scan_data[:, 1], 'g-',
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scan_data[:, 2], 'b-')
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def _calc_vert(img, x1, x2, y1, y2, linewidth):
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# Quick calculation if perfectly horizontal
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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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# Reverse index if necessary
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if y2 > y1:
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pixels = pixels[::-1, :]
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return pixels.mean(axis=1)[:, np.newaxis]
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def profile_line(img, end_points, 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 or 3d array
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The image, in grayscale (2d) or RGB (3d) format.
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end_points: (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_points
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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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channels = 1
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if img.ndim == 3:
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channels = 3
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# Quick calculation if perfectly vertical; shortcuts div0 error
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if x1 == x2:
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if channels == 1:
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img = img[:, :, np.newaxis]
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img = np.rollaxis(img, -1)
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intensities = np.hstack([_calc_vert(im, x1, x2, y1, y2, linewidth)
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for im in img])
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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(x2, x1, 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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if img.ndim == 3:
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pixels = [ndi.map_coordinates(img[..., i], perp_lines)
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for i in range(3)]
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pixels = np.transpose(np.asarray(pixels), (1, 2, 0))
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else:
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pixels = ndi.map_coordinates(img, perp_lines)
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pixels = pixels[..., np.newaxis]
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intensities = pixels.mean(axis=1)
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if intensities.ndim == 1:
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return intensities[..., np.newaxis]
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else:
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return intensities
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