Python pylab.fill方法代碼示例

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def fill_polygon(g, o):
    a = asarray(g.exterior)
    pylab.fill(a[:,0], a[:,1], o, alpha=0.5) 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def drawDef(dfeat, dy, dx, mindef=0.001, distr="father"):
    """
        auxiliary funtion to draw recursive levels of deformation
    """
    from matplotlib.patches import Ellipse
    pylab.ioff()
    if distr == "father":
        py = [0, 0, 2, 2]
        px = [0, 2, 0, 2]
    if distr == "child":
        py = [0, 1, 1, 2]
        px = [1, 2, 0, 1]
    ordy = [0, 0, 1, 1]
    ordx = [0, 1, 0, 1]
    x1 = -0.5 + dx
    x2 = 2.5 + dx
    y1 = -0.5 + dy
    y2 = 2.5 + dy
    if distr == "father":
        pylab.fill([x1, x1, x2, x2, x1], [y1, y2, y2, y1, y1],
                   "r", alpha=0.15, edgecolor="b", lw=1)
    for l in range(len(py)):
        aux = dfeat[ordy[l], ordx[l], :].clip(-1, -mindef)
        wh = numpy.exp(-mindef / aux[0]) / numpy.exp(1)
        hh = numpy.exp(-mindef / aux[1]) / numpy.exp(1)
        e = Ellipse(
            xy=[(px[l] + dx), (py[l] + dy)], width=wh, height=hh, alpha=0.35)
        x1 = -0.75 + dx + px[l]
        x2 = 0.75 + dx + px[l]
        y1 = -0.76 + dy + py[l]
        y2 = 0.75 + dy + py[l]
        col = numpy.array([wh * hh] * 3).clip(0, 1)
        if distr == "father":
            col[0] = 0
        e.set_facecolor(col)
        pylab.gca().add_artist(e)
        if distr == "father":
            pylab.fill([x1, x1, x2, x2, x1], [y1, y2, y2, y1, y1],
                       "b", alpha=0.15, edgecolor="b", lw=1) 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def rgb_patch_plot (
    rgb_colors,
    color_names,
    title,
    filename,
    patch_gap = 0.05,
    num_across = 6):
    '''Draw a set of color patches, specified as linear rgb colors.'''

    def draw_patch (x0, y0, color, name, patch_gap):
        '''Draw a patch of color.'''
        # patch relative vertices
        m = patch_gap
        omm = 1.0 - m
        poly_dx = [m, m, omm, omm]
        poly_dy = [m, omm, omm, m]
        # construct vertices
        poly_x = [ x0 + dx_i for dx_i in poly_dx ]
        poly_y = [ y0 + dy_i for dy_i in poly_dy ]
        pylab.fill (poly_x, poly_y, color)
        if name != None:
            dtext = 0.1
            pylab.text (x0+dtext, y0+dtext, name, size=8.0)

    # make plot with each color with one patch
    pylab.clf()
    num_colors = len (rgb_colors)
    for i in range (0, num_colors):
        (iy, ix) = divmod (i, num_across)
        # get color as a displayable string
        colorstring = colormodels.irgb_string_from_rgb (rgb_colors [i])
        if color_names != None:
            name = color_names [i]
        else:
            name = None
        draw_patch (float (ix), float (-iy), colorstring, name, patch_gap)
    pylab.axis ('off')
    pylab.title (title)
    print ('Saving plot %s' % str (filename))
    pylab.savefig (filename) 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def spectrum_subplot (spectrum):
    '''Plot a spectrum, with x-axis the wavelength, and y-axis the intensity.
    The curve is colored at that wavelength by the (approximate) color of a
    pure spectral color at that wavelength, with intensity constant over wavelength.
    (This means that dark looking colors here mean that wavelength is poorly viewed by the eye.

    This is not a complete plotting function, e.g. no file is saved, etc.
    It is assumed that this function is being called by one that handles those things.'''
    (num_wl, num_cols) = spectrum.shape
    # get rgb colors for each wavelength
    rgb_colors = numpy.empty ((num_wl, 3))
    for i in range (0, num_wl):
        wl_nm = spectrum [i][0]
        xyz = ciexyz.xyz_from_wavelength (wl_nm)
        rgb_colors [i] = colormodels.rgb_from_xyz (xyz)
    # scale to make brightest rgb value = 1.0
    rgb_max = numpy.max (rgb_colors)
    scaling = 1.0 / rgb_max
    rgb_colors *= scaling
    # draw color patches (thin vertical lines matching the spectrum curve) in color
    for i in range (0, num_wl-1):    # skipping the last one here to stay in range
        x0 = spectrum [i][0]
        x1 = spectrum [i+1][0]
        y0 = spectrum [i][1]
        y1 = spectrum [i+1][1]
        poly_x = [x0,  x1,  x1, x0]
        poly_y = [0.0, 0.0, y1, y0]
        color_string = colormodels.irgb_string_from_rgb (rgb_colors [i])
        pylab.fill (poly_x, poly_y, color_string, edgecolor=color_string)
    # plot intensity as a curve
    pylab.plot (
        spectrum [:,0], spectrum [:,1],
        color='k', linewidth=2.0, antialiased=True) 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def drawDeform(dfeat, mindef=0.001):
    """
        draw the deformation weight of an object model
    """
    from matplotlib.patches import Ellipse
    lev = len(dfeat)
    if 1:
        sy = 1
        sx = lev
    else:
        sy = lev
        sx = 1
    pylab.subplot(sy, sx, 1)
    x1 = -0.5
    x2 = 0.5
    y1 = -0.5
    y2 = 0.5
    pylab.fill([x1, x1, x2, x2, x1], [y1, y2, y2, y1, y1],
               "b", alpha=0.15, edgecolor="b", lw=1)
    pylab.fill([x1, x1, x2, x2, x1], [y1, y2, y2, y1, y1],
               "r", alpha=0.15, edgecolor="r", lw=1)
    wh = numpy.exp(-mindef / dfeat[0][0, 0, 0]) / numpy.exp(1)
    hh = numpy.exp(-mindef / dfeat[0][0, 0, 1]) / numpy.exp(1)
    e = Ellipse(xy=[0, 0], width=wh, height=hh, alpha=0.35)
    col = numpy.array([wh * hh] * 3).clip(0, 1)
    col[0] = 0
    e.set_facecolor(col)
    pylab.axis("off")
    pylab.gca().add_artist(e)
    pylab.gca().set_ylim(-0.5, 0.5)
    pylab.gca().set_xlim(-0.5, 0.5)
    for l in range(1, lev):
        pylab.subplot(sy, sx, l + 1)
        for ry in range(2 ** (l - 1)):
            for rx in range(2 ** (l - 1)):
                drawDef(dfeat[l][ry * 2:(ry + 1) * 2, rx * 2:(rx + 1)
                                 * 2, 2:] * 4 ** l, 4 * ry, 4 * rx, distr="child")
                drawDef(dfeat[l][ry * 2:(ry + 1) * 2, rx * 2:(rx + 1) * 2, :2] *
                        4 ** l, ry * 2 ** (l), rx * 2 ** (l), mindef=mindef, distr="father")
        # pylab.gca().set_ylim(-0.5,(2.6)**l)
        pylab.axis("off")
        pylab.gca().set_ylim((2.6) ** l, -0.5)
        pylab.gca().set_xlim(-0.5, (2.6) ** l) 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def spectrum_plot (
    spectrum,
    title,
    filename,
    xlabel = 'Wavelength ($nm$)',
    ylabel = 'Intensity ($W/m^2$)'):
    '''Plot for a single spectrum -
    In a two part graph, plot:
    top: color of the spectrum, as a large patch.
    low: graph of spectrum intensity vs wavelength (x axis).
    The graph is colored by the (approximated) color of each wavelength.
    Each wavelength has equal physical intensity, so the variation in
    apparent intensity (e.g. 400, 800 nm are very dark, 550 nm is bright),
    is due to perceptual factors in the eye.  This helps show how much
    each wavelength contributes to the percieved color.

    spectrum - spectrum to plot
    title    - title for plot
    filename - filename to save plot to
    xlabel   - label for x axis
    ylabel   - label for y axis
    '''
    pylab.clf ()
    # upper plot - solid patch of color that matches the spectrum color
    pylab.subplot (2,1,1)
    pylab.title (title)
    color_string = colormodels.irgb_string_from_rgb (
        colormodels.rgb_from_xyz (ciexyz.xyz_from_spectrum (spectrum)))
    poly_x = [0.0, 1.0, 1.0, 0.0]
    poly_y = [0.0, 0.0, 1.0, 1.0]
    pylab.fill (poly_x, poly_y, color_string)
    # draw a solid line around the patch to look nicer
    pylab.plot (poly_x, poly_y, color='k', linewidth=2.0)
    pylab.axis ('off')
    # lower plot - spectrum vs wavelength, with colors of the associated spectral lines below
    pylab.subplot (2,1,2)
    spectrum_subplot (spectrum)
    tighten_x_axis (spectrum [:,0])
    pylab.xlabel (xlabel)
    pylab.ylabel (ylabel)
    # done
    print ('Saving plot %s' % str (filename))
    pylab.savefig (filename)

#
# Color vs param plot
# 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def color_vs_param_plot (
    param_list,
    rgb_colors,
    title,
    filename,
    tight    = False,
    plotfunc = pylab.plot,
    xlabel   = 'param',
    ylabel   = 'RGB Color'):
    '''Plot for a color that varies with a parameter -
    In a two part figure, draw:
    top: color as it varies with parameter (x axis)
    low: r,g,b values, as linear 0.0-1.0 values, of the attempted color.

    param_list - list of parameters (x axis)
    rgb_colors - numpy array, one row for each param in param_list
    title      - title for plot
    filename   - filename to save plot to
    plotfunc   - optional plot function to use (default pylab.plot)
    xlabel     - label for x axis
    ylabel     - label for y axis (default 'RGB Color')
    '''
    pylab.clf ()
    # draw color bars in upper plot
    pylab.subplot (2,1,1)
    pylab.title (title)
    # no xlabel, ylabel in upper plot
    num_points = len (param_list)
    for i in range (0, num_points-1):
        x0 = param_list [i]
        x1 = param_list [i+1]
        y0 = 0.0
        y1 = 1.0
        poly_x = [x0, x1, x1, x0]
        poly_y = [y0, y0, y1, y1]
        color_string = colormodels.irgb_string_from_rgb (rgb_colors [i])
        pylab.fill (poly_x, poly_y, color_string, edgecolor=color_string)
    if tight:
        tighten_x_axis (param_list)
    # draw rgb curves in lower plot
    pylab.subplot (2,1,2)
    # no title in lower plot
    plotfunc (param_list, rgb_colors [:,0], color='r', label='Red')
    plotfunc (param_list, rgb_colors [:,1], color='g', label='Green')
    plotfunc (param_list, rgb_colors [:,2], color='b', label='Blue')
    if tight:
        tighten_x_axis (param_list)
    pylab.xlabel (xlabel)
    pylab.ylabel (ylabel)
    print ('Saving plot %s' % str (filename))
    pylab.savefig (filename)

#
# Some specialized plots
# 

# 需要導入模塊: import pylab [as 別名]
# 或者: from pylab import fill [as 別名]
def  plot_item_triangles(self, m, ind, x, r, k, label, U,
                           rerr, feature_weights, band_ind):
    """plot_item_triangles(self, m, ind, x, r, k, label, U,
       rerr, feature_weights, band_ind)

    Plot selection m (index ind, data in x) with triangles to
    mark the largest residual values on band_ind indices
    (i.e., you need to pick them before calling this).

    To use this, define plot_item() in your data set's class
    to call this function instead.
    """

    if x == [] or r == []: 
      print "Error: No data in x and/or r."
      return
  
    pylab.clf()
    # xvals, x, and r need to be column vectors
    pylab.plot(self.xvals, r, 'r-',  linewidth=0.5, label='Expected')
    pylab.plot(self.xvals, x, 'b.-', linewidth=1,   label='Observations')
    # Boost font sizes for axis and tick labels
    pylab.xlabel(self.xlabel) #, fontsize=16)
    pylab.ylabel(self.ylabel) #, fontsize=16)
    '''
    pylab.xticks(fontsize=16)
    pylab.yticks(fontsize=16)
    '''
    pylab.title('DEMUD selection %d (%s), item %d, using K=%d' % \
                (m, label, ind, k))
    pylab.legend(fontsize=10)

    # width of triangles to plot
    width = (self.xvals.max() - self.xvals.min())/100.0
    
    for band in band_ind:
      w = float(self.xvals[band])
      reproj = r[band]
      # Draw a triangle that points up if r > x
      # or down if r < x
      pylab.fill([w-width, w+width, w],
                 [reproj,  reproj,  x[band]],
                 '0.6', zorder=1)

    outdir  = os.path.join('results', self.name)
    if not os.path.exists(outdir):
      os.mkdir(outdir)
    figfile = os.path.join(outdir, 'sel-%d-k-%d-(%s).pdf' % (m, k, label))
    pylab.savefig(figfile)
    print 'Wrote plot to %s' % figfile
    pylab.close()