import warnings import numpy as np import scipy.ndimage as ndi from skimage.util.dtype import dtype_range from .plotplugin import PlotPlugin from ..canvastools import ThickLineTool __all__ = ['LineProfile'] class LineProfile(PlotPlugin): """Plugin to compute interpolated intensity under a scan line on an image. See PlotPlugin and Plugin classes for additional details. Parameters ---------- maxdist : float Maximum pixel distance allowed when selecting end point of scan line. epsilon : float Deprecated. Use `maxdist` instead. limits : tuple or {None, 'image', 'dtype'} (minimum, maximum) intensity limits for plotted profile. The following special values are defined: None : rescale based on min/max intensity along selected scan line. 'image' : fixed scale based on min/max intensity in image. 'dtype' : fixed scale based on min/max intensity of image dtype. """ name = 'Line Profile' def __init__(self, maxdist=10, epsilon='deprecated', limits='image', **kwargs): super(LineProfile, self).__init__(**kwargs) if not epsilon == 'deprecated': warnings.warn("Parameter `epsilon` deprecated; use `maxdist`.") maxdist = epsilon self.maxdist = maxdist self._limit_type = limits print(self.help()) def attach(self, image_viewer): super(LineProfile, self).attach(image_viewer) image = image_viewer.original_image if self._limit_type == 'image': self.limits = (np.min(image), np.max(image)) elif self._limit_type == 'dtype': self._limit_type = dtype_range[image.dtype.type] elif self._limit_type is None or len(self._limit_type) == 2: self.limits = self._limit_type else: raise ValueError("Unrecognized `limits`: %s" % self._limit_type) if not self._limit_type is None: self.ax.set_ylim(self.limits) h, w = image.shape x = [w / 3, 2 * w / 3] y = [h / 2] * 2 self.line_tool = ThickLineTool(self.image_viewer.ax, maxdist=self.maxdist, on_move=self.line_changed, on_change=self.line_changed) self.line_tool.end_points = np.transpose([x, y]) scan_data = profile_line(image, self.line_tool.end_points) self.profile = self.ax.plot(scan_data, 'k-')[0] self._autoscale_view() def help(self): helpstr = ("Line profile tool", "+ and - keys or mouse scroll changes width of scan line.", "Select and drag ends of the scan line to adjust it.") return '\n'.join(helpstr) def get_profile(self): """Return intensity profile of the selected line. Returns ------- end_points: (2, 2) array The positions ((x1, y1), (x2, y2)) of the line ends. profile: 1d array Profile of intensity values. """ profile = self.profile.get_ydata() return self.line_tool.end_points, profile def _autoscale_view(self): if self.limits is None: self.ax.autoscale_view(tight=True) else: self.ax.autoscale_view(scaley=False, tight=True) def line_changed(self, end_points): x, y = np.transpose(end_points) self.line_tool.end_points = end_points scan = profile_line(self.image_viewer.original_image, end_points, linewidth=self.line_tool.linewidth) self.profile.set_xdata(np.arange(scan.shape[0])) self.profile.set_ydata(scan) self.ax.relim() if self.useblit: self.ax.draw_artist(self.profile) self._autoscale_view() self.redraw() def profile_line(img, end_points, linewidth=1): """Return the intensity profile of an image measured along a scan line. Parameters ---------- img : 2d array The image. end_points: (2, 2) list End points ((x1, y1), (x2, y2)) of scan line. linewidth: int Width of the scan, perpendicular to the line Returns ------- return_value : array The intensity profile along the scan line. The length of the profile is the ceil of the computed length of the scan line. """ point1, point2 = end_points x1, y1 = point1 = np.asarray(point1, dtype=float) x2, y2 = point2 = np.asarray(point2, dtype=float) dx, dy = point2 - point1 # Quick calculation if perfectly horizontal or vertical (remove?) if x1 == x2: pixels = img[min(y1, y2): max(y1, y2) + 1, x1 - linewidth / 2: x1 + linewidth / 2 + 1] intensities = pixels.mean(axis=1) return intensities elif y1 == y2: pixels = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1, min(x1, x2): max(x1, x2) + 1] intensities = pixels.mean(axis=0) return intensities theta = np.arctan2(dy, dx) a = dy / dx b = y1 - a * x1 length = np.hypot(dx, dy) line_x = np.linspace(min(x1, x2), max(x1, x2), np.ceil(length)) line_y = line_x * a + b y_width = abs(linewidth * np.cos(theta) / 2) perp_ys = np.array([np.linspace(yi - y_width, yi + y_width, linewidth) for yi in line_y]) perp_xs = - a * perp_ys + (line_x + a * line_y)[:, np.newaxis] perp_lines = np.array([perp_ys, perp_xs]) pixels = ndi.map_coordinates(img, perp_lines) intensities = pixels.mean(axis=1) return intensities