10 examples of 'plot histogram python' in Python

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48def plot_histogram(values, num_bins=100):
49 """
50 Generates a plot of the histograms of grasps by probability of force closure
51 """
52 bin_edges = np.linspace(np.min(values), np.max(values), num_bins+1)
53 plt.figure()
54 n, bins, patches = plt.hist(values, bin_edges)
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330def plot_histogram(x, fname, bins=np.arange(0, 7) + 0.5, xlabel="proposal", ylabel="Counts"):
331 plt.figure()
332 plt.hist(x, bins, histtype='bar', facecolor='green', rwidth=0.8)
333 plt.xlabel(xlabel)
334 plt.ylabel(ylabel)
335 plt.savefig(fname + ".png")
336 plt.close()
70def plot_histogram(self, naxes, hist_edges, hist):
71 hist_width = 256/len(hist)
72 if naxes not in self.histograms:
73 self.histograms[naxes] = self.axes[naxes].bar(
74 hist_edges[:-1], hist, width=hist_width, facecolor="#dbdbdb",
75 align="edge")
76 else:
77 for i, rect in enumerate(self.histograms[naxes]):
78 rect.set_height(hist[i])
79 rect.set_x(hist_edges[i])
80 if naxes == len(self.histograms)-1:
81 self.canvas.draw()
18def plot_2d_hist(x1, x2, bins=10):
19 plt.hist2d(x1, x2, bins=10, norm=LogNorm())
20 plt.colorbar()
21 plt.show()
88def plot_hist(axes, data, xlabel=None, log=False, avg=True, median=True, bins=None, **kwargs):
89 time_max = max(data)
90 time_min = min(data)
91 time_avg = np.average(data)
92 time_median = np.median(data)
93 if bins is None:
94 bins = time_max - time_min + 1
95 hist = axes.hist(data, bins=bins, log=log, **kwargs)
96 if avg:
97 axes.axvline(x=time_avg, alpha=0.7, linestyle="dotted", color="blue", label="avg = {}".format(time_avg))
98 if median:
99 axes.axvline(x=time_median, alpha=0.7, linestyle="dotted", color="green", label="median = {}".format(time_median))
100 axes.set_ylabel("count" + ("\n(log)" if log else ""))
101 axes.set_xlabel("time" if xlabel is None else xlabel)
102 axes.xaxis.set_major_locator(ticker.MaxNLocator())
103 if avg or median:
104 axes.legend(loc="best")
105 return hist
23@timing_func
24def plotHistogram3D(image, num_bins, color_space, ax):
25 font_size = 15
26 plt.title("%s: %s bins" % (color_space, num_bins), fontsize=font_size)
27
28 hist3D = Hist3D(image, num_bins=num_bins, color_space=color_space)
29 hist3D.plot(ax)
23def show_hist_with_matplotlib_gray(hist, title, pos, color):
24 """Shows the histogram using matplotlib capabilities"""
25
26 ax = plt.subplot(2, 3, pos)
27 # plt.title(title)
28 plt.xlabel("bins")
29 plt.ylabel("number of pixels")
30 plt.xlim([0, 256])
31 plt.plot(hist, color=color)
134def compare_hist(hist, bins, like, x, figname, discrete=False):
135 """Plot and save a figure comparing the histogram with the
136 probability.
137
138 :Parameters:
139 - `samples`: random variables.
140 - `like`: probability values.
141 - `bins`: histogram bins.
142 - `x`: values at which like is computed.
143 - `figname`: Name of figure to save.
144 """
145 ax = P.subplot(111)
146 width = 0.9*(bins[1]-bins[0])
147 ax.bar(bins, hist, width)
148 P.setp(ax.patches, alpha=.5)
149 if discrete:
150 ax.plot(x, like, 'k', linestyle='steps')
151 else:
152 ax.plot(x, like, 'k')
153 P.savefig('figs/' + figname)
154 P.close()
147def histogram(image):
148 hist = cv2.calcHist([image], [0], None, [256], [0, 256])
149 # cv2.calcHist(images, channels, mask, histSize, ranges[, hist[, accumulate]])
150 plt.plot(hist)
151 plt.show()
685def plot_probabilities_histogram(Y):
686 plt.hist(Y, bins=10)
687 plt.xlabel("Probability of SPAM")
688 plt.ylabel("Number of data points")
689 plt.show()

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