10 examples of 'plot histogram python' in Python

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def plot_histogram(values, num_bins=100):
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    """
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    Generates a plot of the histograms of grasps by probability of force closure
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    """
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    bin_edges = np.linspace(np.min(values), np.max(values), num_bins+1)
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    plt.figure()
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    n, bins, patches = plt.hist(values, bin_edges)

330
def plot_histogram(x, fname, bins=np.arange(0, 7) + 0.5, xlabel="proposal", ylabel="Counts"):
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    plt.figure()
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    plt.hist(x, bins, histtype='bar', facecolor='green', rwidth=0.8)
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    plt.xlabel(xlabel)
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    plt.ylabel(ylabel)
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    plt.savefig(fname + ".png")
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    plt.close()

70
def plot_histogram(self, naxes, hist_edges, hist):
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    hist_width = 256/len(hist)
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    if naxes not in self.histograms:
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        self.histograms[naxes] = self.axes[naxes].bar(
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            hist_edges[:-1], hist, width=hist_width, facecolor="#dbdbdb",
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            align="edge")
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    else:
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        for i, rect in enumerate(self.histograms[naxes]):
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            rect.set_height(hist[i])
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            rect.set_x(hist_edges[i])
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        if naxes == len(self.histograms)-1:
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            self.canvas.draw()

18
def plot_2d_hist(x1, x2, bins=10):
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    plt.hist2d(x1, x2, bins=10, norm=LogNorm())
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    plt.colorbar()
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    plt.show()

88
def plot_hist(axes, data, xlabel=None, log=False, avg=True, median=True, bins=None, **kwargs):
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    time_max = max(data)
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    time_min = min(data)
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    time_avg = np.average(data)
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    time_median = np.median(data)
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    if bins is None:
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        bins = time_max - time_min + 1
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    hist = axes.hist(data, bins=bins, log=log, **kwargs)
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    if avg:
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        axes.axvline(x=time_avg, alpha=0.7, linestyle="dotted", color="blue", label="avg = {}".format(time_avg))
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    if median:
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        axes.axvline(x=time_median, alpha=0.7, linestyle="dotted", color="green", label="median = {}".format(time_median))
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    axes.set_ylabel("count" + ("\n(log)" if log else ""))
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    axes.set_xlabel("time" if xlabel is None else xlabel)
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    axes.xaxis.set_major_locator(ticker.MaxNLocator())
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    if avg or median:
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        axes.legend(loc="best")
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    return hist

23
@timing_func
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def plotHistogram3D(image, num_bins, color_space, ax):
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    font_size = 15
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    plt.title("%s: %s bins" % (color_space, num_bins), fontsize=font_size)
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    hist3D = Hist3D(image, num_bins=num_bins, color_space=color_space)
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    hist3D.plot(ax)

23
def show_hist_with_matplotlib_gray(hist, title, pos, color):
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    """Shows the histogram using matplotlib capabilities"""
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    ax = plt.subplot(2, 3, pos)
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    # plt.title(title)
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    plt.xlabel("bins")
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    plt.ylabel("number of pixels")
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    plt.xlim([0, 256])
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    plt.plot(hist, color=color)

134
def compare_hist(hist, bins, like, x, figname, discrete=False):
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    """Plot and save a figure comparing the histogram with the
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    probability.
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    :Parameters:
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      - `samples`: random variables.
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      - `like`: probability values.
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      - `bins`: histogram bins.
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      - `x`: values at which like is computed.
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      - `figname`: Name of figure to save.
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    """
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    ax = P.subplot(111)
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    width = 0.9*(bins[1]-bins[0])
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    ax.bar(bins, hist, width)
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    P.setp(ax.patches, alpha=.5)
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    if discrete:
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        ax.plot(x, like, 'k', linestyle='steps')
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    else:
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        ax.plot(x, like, 'k')
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    P.savefig('figs/' + figname)
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    P.close()

147
def histogram(image):
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	hist = cv2.calcHist([image], [0], None, [256], [0, 256])
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	# cv2.calcHist(images, channels, mask, histSize, ranges[, hist[, accumulate]]) 
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	plt.plot(hist)
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	plt.show()

685
def plot_probabilities_histogram(Y):
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    plt.hist(Y, bins=10)
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    plt.xlabel("Probability of SPAM")
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    plt.ylabel("Number of data points")
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    plt.show()