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BboxImage implemented and two examples added.
svn path=/trunk/matplotlib/; revision=7423
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‎CHANGELOG‎

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2009-08-07 BboxImage implemented. Two examples, demo_bboximage.py and
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demo_ribbon_box.py added. - JJL
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2009-08-07 In an effort to simplify the backend API, all clipping rectangles
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and paths are now passed in using GraphicsContext objects, even
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on collections and images. Therefore:

‎examples/pylab_examples/demo_bboximage.py‎

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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib.image import BboxImage
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from matplotlib.transforms import Bbox, TransformedBbox
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if __name__ == "__main__":
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fig = plt.figure(1)
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ax = plt.subplot(121)
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txt = ax.text(0.5, 0.5, "test", size=30, ha="center", color="w")
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kwargs = dict()
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bbox_image = BboxImage(txt.get_window_extent,
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norm = None,
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origin=None,
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clip_on=False,
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**kwargs
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)
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a = np.arange(256).reshape(1,256)/256.
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bbox_image.set_data(a)
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ax.add_artist(bbox_image)
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ax = plt.subplot(122)
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a = np.linspace(0, 1, 256).reshape(1,-1)
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a = np.vstack((a,a))
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maps = sorted(m for m in plt.cm.datad if not m.endswith("_r"))
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#nmaps = len(maps) + 1
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#fig.subplots_adjust(top=0.99, bottom=0.01, left=0.2, right=0.99)
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ncol = 2
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nrow = len(maps)//ncol + 1
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xpad_fraction = 0.3
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dx = 1./(ncol + xpad_fraction*(ncol-1))
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ypad_fraction = 0.3
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dy = 1./(nrow + ypad_fraction*(nrow-1))
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for i,m in enumerate(maps):
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ix, iy = divmod(i, nrow)
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#plt.figimage(a, 10, i*10, cmap=plt.get_cmap(m), origin='lower')
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bbox0 = Bbox.from_bounds(ix*dx*(1+xpad_fraction),
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1.-iy*dy*(1+ypad_fraction)-dy,
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dx, dy)
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bbox = TransformedBbox(bbox0, ax.transAxes)
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bbox_image = BboxImage(bbox,
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cmap = plt.get_cmap(m),
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norm = None,
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origin=None,
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**kwargs
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)
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bbox_image.set_data(a)
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ax.add_artist(bbox_image)
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plt.draw()
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plt.show()

‎examples/pylab_examples/demo_ribbon_box.py‎

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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib.image import BboxImage
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from matplotlib._png import read_png
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import matplotlib.colors
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from matplotlib.cbook import get_sample_data
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class RibbonBox(object):
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original_image = read_png(get_sample_data("Minduka_Present_Blue_Pack.png",
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asfileobj=False))
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cut_location = 70
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b_and_h = original_image[:,:,2]
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color = original_image[:,:,2] - original_image[:,:,0]
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alpha = original_image[:,:,3]
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nx = original_image.shape[1]
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def __init__(self, color):
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rgb = matplotlib.colors.colorConverter.to_rgb(color)
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im = np.empty(self.original_image.shape,
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self.original_image.dtype)
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im[:,:,:3] = self.b_and_h[:,:,np.newaxis]
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im[:,:,:3] -= self.color[:,:,np.newaxis]*(1.-np.array(rgb))
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im[:,:,3] = self.alpha
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self.im = im
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def get_stretched_image(self, stretch_factor):
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stretch_factor = max(stretch_factor, 1)
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ny, nx, nch = self.im.shape
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ny2 = int(ny*stretch_factor)
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stretched_image = np.empty((ny2, nx, nch),
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self.im.dtype)
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cut = self.im[self.cut_location,:,:]
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stretched_image[:,:,:] = cut
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stretched_image[:self.cut_location,:,:] = \
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self.im[:self.cut_location,:,:]
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stretched_image[-(ny-self.cut_location):,:,:] = \
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self.im[-(ny-self.cut_location):,:,:]
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self._cached_im = stretched_image
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return stretched_image
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class RibbonBoxImage(BboxImage):
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zorder = 1
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def __init__(self, bbox, color,
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cmap = None,
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norm = None,
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interpolation=None,
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origin=None,
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filternorm=1,
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filterrad=4.0,
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resample = False,
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**kwargs
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):
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BboxImage.__init__(self, bbox,
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cmap = None,
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norm = None,
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interpolation=None,
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origin=None,
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filternorm=1,
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filterrad=4.0,
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resample = False,
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**kwargs
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)
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self._ribbonbox = RibbonBox(color)
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self._cached_ny = None
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def draw(self, renderer, *args, **kwargs):
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bbox = self.get_window_extent(renderer)
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stretch_factor = bbox.height / bbox.width
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ny = int(stretch_factor*self._ribbonbox.nx)
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if self._cached_ny != ny:
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arr = self._ribbonbox.get_stretched_image(stretch_factor)
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self.set_array(arr)
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self._cached_ny = ny
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BboxImage.draw(self, renderer, *args, **kwargs)
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if 1:
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from matplotlib.transforms import Bbox, TransformedBbox
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from matplotlib.ticker import ScalarFormatter
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fig = plt.gcf()
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fig.clf()
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ax = plt.subplot(111)
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years = np.arange(2004, 2009)
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box_colors = [(0.8, 0.2, 0.2),
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(0.2, 0.8, 0.2),
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(0.2, 0.2, 0.8),
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(0.7, 0.5, 0.8),
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(0.3, 0.8, 0.7),
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]
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heights = np.random.random(years.shape) * 7000 + 3000
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fmt = ScalarFormatter(useOffset=False)
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ax.xaxis.set_major_formatter(fmt)
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for year, h, bc in zip(years, heights, box_colors):
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bbox0 = Bbox.from_extents(year-0.4, 0., year+0.4, h)
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bbox = TransformedBbox(bbox0, ax.transData)
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rb_patch = RibbonBoxImage(bbox, bc)
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ax.add_artist(rb_patch)
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ax.annotate(r"%d" % (int(h/100.)*100),
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(year, h), va="bottom", ha="center")
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patch_gradient = BboxImage(ax.bbox,
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interpolation="bicubic",
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zorder=0.1,
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)
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gradient = np.zeros((2, 2, 4), dtype=np.float)
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gradient[:,:,:3] = [1, 1, 0.]
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gradient[:,:,3] = [[0.1, 0.3],[0.3, 0.5]] # alpha channel
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patch_gradient.set_array(gradient)
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ax.add_artist(patch_gradient)
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ax.set_xlim(years[0]-0.5, years[-1]+0.5)
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ax.set_ylim(0, 10000)
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plt.show()
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‎lib/matplotlib/image.py‎

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# the image namespace:
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from matplotlib._image import *
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from matplotlib.transforms import BboxBase
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class AxesImage(martist.Artist, cm.ScalarMappable):
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zorder = 1
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# map interpolation strings to module constants
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rows, cols, buffer = im.as_rgba_str()
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_png.write_png(buffer, cols, rows, fname)
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class BboxImage(AxesImage):
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"""
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The Image class whose size is determined by the given bbox.
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"""
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zorder = 1
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def __init__(self, bbox,
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cmap = None,
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norm = None,
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interpolation=None,
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origin=None,
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filternorm=1,
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filterrad=4.0,
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resample = False,
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**kwargs
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):
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"""
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cmap is a colors.Colormap instance
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norm is a colors.Normalize instance to map luminance to 0-1
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kwargs are an optional list of Artist keyword args
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"""
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AxesImage.__init__(self, ax=None,
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cmap = cmap,
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norm = norm,
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interpolation=interpolation,
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origin=origin,
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filternorm=filternorm,
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filterrad=filterrad,
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resample = resample,
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**kwargs
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)
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self.bbox = bbox
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def get_window_extent(self, renderer=None):
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if renderer is None:
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renderer = self.get_figure()._cachedRenderer
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if isinstance(self.bbox, BboxBase):
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return self.bbox
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elif callable(self.bbox):
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return self.bbox(renderer)
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else:
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raise ValueError("unknown type of bbox")
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def contains(self, mouseevent):
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"""Test whether the mouse event occured within the image.
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"""
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if callable(self._contains): return self._contains(self,mouseevent)
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if not self.get_visible():# or self.get_figure()._renderer is None:
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return False,{}
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x, y = mouseevent.x, mouseevent.y
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inside = self.get_window_extent().contains(x, y)
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return inside,{}
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def get_size(self):
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'Get the numrows, numcols of the input image'
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if self._A is None:
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raise RuntimeError('You must first set the image array')
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return self._A.shape[:2]
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def make_image(self, renderer, magnification=1.0):
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if self._A is None:
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raise RuntimeError('You must first set the image array or the image attribute')
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if self._imcache is None:
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if self._A.dtype == np.uint8 and len(self._A.shape) == 3:
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im = _image.frombyte(self._A, 0)
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im.is_grayscale = False
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else:
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if self._rgbacache is None:
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x = self.to_rgba(self._A, self._alpha)
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self._rgbacache = x
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else:
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x = self._rgbacache
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im = _image.fromarray(x, 0)
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if len(self._A.shape) == 2:
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im.is_grayscale = self.cmap.is_gray()
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else:
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im.is_grayscale = False
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self._imcache = im
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if self.origin=='upper':
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im.flipud_in()
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else:
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im = self._imcache
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if 0:
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fc = self.axes.patch.get_facecolor()
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bg = mcolors.colorConverter.to_rgba(fc, 0)
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im.set_bg( *bg)
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# image input dimensions
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im.reset_matrix()
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im.set_interpolation(self._interpd[self._interpolation])
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im.set_resample(self._resample)
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l, b, r, t = self.get_window_extent(renderer).extents #bbox.extents
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widthDisplay = (round(r) + 0.5) - (round(l) - 0.5)
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heightDisplay = (round(t) + 0.5) - (round(b) - 0.5)
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widthDisplay *= magnification
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heightDisplay *= magnification
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#im.apply_translation(tx, ty)
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numrows, numcols = self._A.shape[:2]
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# resize viewport to display
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rx = widthDisplay / numcols
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ry = heightDisplay / numrows
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#im.apply_scaling(rx*sx, ry*sy)
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im.apply_scaling(rx, ry)
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#im.resize(int(widthDisplay+0.5), int(heightDisplay+0.5),
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# norm=self._filternorm, radius=self._filterrad)
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im.resize(int(widthDisplay), int(heightDisplay),
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norm=self._filternorm, radius=self._filterrad)
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return im
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@allow_rasterization
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def draw(self, renderer, *args, **kwargs):
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if not self.get_visible(): return
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# todo: we should be able to do some cacheing here
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image_mag = renderer.get_image_magnification()
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im = self.make_image(renderer, image_mag)
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l, b, r, t = self.get_window_extent(renderer).extents
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gc = renderer.new_gc()
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self._set_gc_clip(gc)
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#gc.set_clip_path(self.get_clip_path())
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renderer.draw_image(gc, round(l), round(b), im)
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def imread(fname):
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"""
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Return image file in *fname* as :class:`numpy.array`.

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