def plot2d(arr, size=(700, 600), palette=gray, dontscale=False):
if dontscale:
im = pilutil.toimage(MLab.flipud(arr), pal=palette, cmin=0., cmax=1.)
else:
im = pilutil.toimage(MLab.flipud(arr), pal=palette)
if size:
im = im.resize(size)
im.show()
def setPalette(self, palette):
self.palette = palette
if self.array:
self.image = pilutil.toimage(MLab.flipud(self.array), pal=palette)
self.doPlotImage()
if self.legend:
self.legend.setImagePlot(self)
def setArray(self, arr, palette=palettes["brownish"]):
self.array = arr
# if no_scaling: #for subplots and stuff like that...
# im = pilutil.toimage(MLab.flipud(arr), pal = palette, cmin = 0., cmax = 1.)
self.image = pilutil.toimage(MLab.flipud(arr), pal=palette)
self.afterResize()
def setArray(self, arr, palette=None, axis_x_max=None, axis_y_max=None):
self.array = arr
self.palette = palette or palettes["brownish"]
s = shape(arr)
axis_y_max = axis_y_max or s[0]
axis_x_max = axis_x_max or s[1]
self.setAxisScale(QwtPlot.xBottom, 0, axis_x_max)
self.setAxisScale(QwtPlot.yLeft, 0, axis_y_max)
self.replot()
# if no_scaling: #for subplots and stuff like that...
# im = pilutil.toimage(MLab.flipud(arr), pal = palette, cmin = 0., cmax = 1.)
self.image = pilutil.toimage(MLab.flipud(arr), pal=self.palette)
if hasattr(self, "image_unzoomed"):
self.image_unzoomed = self.image
self.doPlotImage()
if self.legend:
self.legend.setImagePlot(self)
def setImagePlot(self, implot, arr=None):
self.implot = implot
implot.legend = self
self.parent_array = arr or implot.array
self.palette = implot.palette
r = ravel(self.parent_array)
r_min, r_max = min(r), max(r)
dif = r_max - r_min
if dif == 0:
r_max = r_min + 1
self.array = arange(r_min, r_max, dif / 256.)[:, NewAxis]
self.setAxisScale(QwtPlot.yLeft, r_min, r_max)
self.replot()
# if no_scaling: #for subplots and stuff like that...
# im = pilutil.toimage(MLab.flipud(arr), pal = palette, cmin = 0., cmax = 1.)
self.image = pilutil.toimage(MLab.flipud(self.array), pal=self.palette)
self.doPlotImage()
def zoom(self, x0, y0, x1, y1):
x0, y0, x1, y1 = map(int, (x0, y0, x1, y1))
if not self.rescale_on_zoom:
if not hasattr(self, "image_unzoomed"):
self.image_unzoomed = copy.copy(self.image)
unz = self.image_unzoomed
y_top = unz.size[1]
flip = lambda y: y_top - y
if y1 > y0:
y0, y1 = y1, y0
self.image = copy.copy(unz)
self.image = self.image.transform(unz.size, Image.EXTENT,
(x0, flip(y0), x1, flip(y1)))
else:
if y1 < y0:
y0, y1 = y1, y0
#print x0, x1, y0, y1
#print shape(self.array)
arr = self.array[y0:y1, x0:x1]
self.image = pilutil.toimage(MLab.flipud(arr), pal=self.palette)
if self.legend:
self.legend.setImagePlot(self, arr)
self.doPlotImage()
def pseudocolor(M, draw=1):
"""Draws a psuedo-color representation of a matrix.
Comments:
* Use keyword setting draw=0 to just return the plot object without
first drawing the plot.
* Routine actually inverts the ordering of the matrix so it is
viewed as we generally think of matrices (i.e. with row indices
increasing as we move down, and column indices increasing as we
move to the right)
"""
nr, nc = M.shape
plot = contours.ColorPlot()
ai = plots.auto_axis(Num.ravel(M))
plot.axes.zaxis(min = ai.min, max = ai.max,
tickstart = ai.start, tickstep = ai.step)
plot.axes(autoresolution = (nr,nc))
clrmatrix = contours.ColorMatrix(MLab.flipud(M), nr, nc)
plot.add(clrmatrix)
if draw:
plot.draw()
return plot
