Python matplotlib.pyplot 模块，FuncFormatter() 实例源码

def saveHistogram(fname, x, bins=50):
    def to_percent(y, pos):
        s = str(100*y)
        if plt.rcParams['text.usetex'] is True:
            return s + r'$\%$'
        else:
            return s + '%'

    # plt.hist(x, bins=bins, normed=True, cumulative=True)
    plt.hist(x, bins=bins)
    # formatter = plt.FuncFormatter(to_percent)
    # plt.gca().yaxis.set_major_formatter(formatter)

    plt.savefig(fname)
    plt.close()

def plot3D(data, taxid_list):
    colors = cm.rainbow(np.linspace(0, 1, len(taxid_list)))

    fig = plt.figure(figsize=(12,9))
    ax = fig.add_subplot(111, projection='3d')
    fig.suptitle("NCTU receipts")

    c_index = 0
    for taxid in taxid_list:

        (x, y, z) = data[taxid]
        print "{} {}".format(taxid, colors[c_index])
        #print len(X[taxid]), len(Y[taxid]), len(Z[taxid])
        ax.scatter(np.log(x),y,z,c=colors[c_index],marker='o',\
        s=20, alpha=0.2, edgecolors='none')
        #x2, y2, _ = proj3d.proj_transform(x,y,z, ax.get_proj())
        #label = plt.annotate(\
        #taxid,\
        #xy = (x2, y2), xytext = (-20, 20),\
        #textcoords = 'offset points', ha = 'right', va = 'bottom',\
        #bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.1),\
        #arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))

        c_index += 1


    ax.set_xlabel('num')
    #ax.set_xscale('log',nonposx='clip')
    ax.set_ylabel('med')
    ax.set_zlabel('ratio')
    ax.zaxis.set_major_formatter(plt.FuncFormatter(\
        lambda x, loc: "{:,}".format(int(x))))
    #fig.canvas.mpl_connect('button_release_event', update_position)
    plt.show()

def plot_hist(self, ax, overlapping=False, formatted_yaxis=True, **kwargs):
        """Returns a matplotlib style histogram (matplotlib.pyplot.hist)

        Uses the matplotlib object oriented interface to add a Histogram to an matplotlib Axes object.
        All named arguments from pyplot.hist can be used. A new argument called "type" makes it possible to
        make overlapping histogram plots.

        Args:
            :ax: (`Axes`)
                An matplotlib Axes object on which the histogram will be plot
            :overlapping (`bool`, optional):
                If set to true, this will generate an overlapping plot.
                When set to False it will generate a normal grouped histogram. Defaults to False.
            :formatted_yaxis: (`bool`, optional).
                If set to true, the numbers on the yaxis will be formatted
                for better readability. E.g. 1500000 will become 1.5M. Defaults to True
            :\*\*kwargs:
                The keyword arguments as used in matplotlib.pyplot.hist
        """
        self.build()

        if formatted_yaxis:
            # Round the y-axis value to nearest thousand, million, or billion for readable y-axis
            formatter = plt.FuncFormatter(Histogram._convert_number_bmk)
            ax.yaxis.set_major_formatter(formatter)

        if overlapping:
            for colname in self.hist_dict:
                ax.hist(self._get_bin_centers(),
                        bins=self.bin_list,
                        alpha=0.5,
                        label=self.hist_dict.keys(),
                        weights=self.hist_dict[colname],
                        **kwargs
                        )
        else:
            weights_multi = [self.hist_dict[colname] for colname in self.hist_dict]
            return ax.hist([self._get_bin_centers()] * len(self.hist_dict),
                           bins=self.bin_list,
                           weights=weights_multi,
                           label=self.hist_dict.keys(),
                           **kwargs)

def plot_hist(self, ax, overlapping=False, formatted_yaxis=True, **kwargs):
        """Returns a matplotlib style histogram (matplotlib.pyplot.hist)

        Uses the matplotlib object oriented interface to add a Histogram to an matplotlib Axes object.
        All named arguments from pyplot.hist can be used. A new argument called "type" makes it possible to
        make overlapping histogram plots.

        Args:
            ax (:obj:`Axes`): An matplotlib Axes object on which the histogram will be plot
            overlapping (:obj:`bool`, optional): If set to true, this will generate an overlapping plot.
            When set to False it will generate a normal grouped histogram. Defaults to False.
            formatted_yaxis (:obj:`bool`, optional). If set to true, the numbers on the yaxis will be formatted
            for better readability. E.g. 1500000 will become 1.5M. Defaults to True
            **kwargs: The keyword arguments as used in matplotlib.pyplot.hist
        """
        self.build()

        if formatted_yaxis:
            # Round the y-axis value to nearest thousand, million, or billion for readable y-axis
            formatter = plt.FuncFormatter(Histogram._convert_number_bmk)
            ax.yaxis.set_major_formatter(formatter)

        if overlapping:
            for colname in self.hist_dict:
                ax.hist(self._get_bin_centers(),
                        bins=self.bin_list,
                        alpha=0.5,
                        label=self.hist_dict.keys(),
                        weights=self.hist_dict[colname],
                        **kwargs
                        )
        else:
            weights_multi = [self.hist_dict[colname] for colname in self.hist_dict]
            return ax.hist([self._get_bin_centers()] * len(self.hist_dict),
                           bins=self.bin_list,
                           weights=weights_multi,
                           label=self.hist_dict.keys(),
                           **kwargs)