matplotlib_viz案例简单探究
# -*- coding: utf-8 -*- """ Created on Sun Jun 11 09:56:39 2017 @author: Raghav Bali """ """ This script visualizes data using matplotlib ``Execute`` $ python matplotlib_viz.py """ import numpy as np import matplotlib.pyplot as plt if __name__=='__main__': # sample plot x = np.linspace(-10, 10, 50) y=np.sin(x) plt.plot(x,y) plt.title('Sine Curve using matplotlib') plt.xlabel('x-axis') plt.ylabel('y-axis') plt.show() # figure plt.figure(1) plt.plot(x,y) plt.title('Fig1: Sine Curve') plt.xlabel('x-axis') plt.ylabel('y-axis') plt.show() plt.figure(2) y=np.cos(x) plt.plot(x,y) plt.title('Fig2: Cosine Curve') plt.xlabel('x-axis') plt.ylabel('y-axis') plt.show() ### subplot # fig.add_subplot y = np.sin(x) figure_obj = plt.figure() ax1 = figure_obj.add_subplot(2,2,1) ax1.plot(x,y) ax2 = figure_obj.add_subplot(2,2,2) ax3 = figure_obj.add_subplot(2,2,3) ax4 = figure_obj.add_subplot(2,2,4) ax4.plot(x+10,y) plt.show() # plt.subplots fig, ax_list = plt.subplots(2,1,sharex=True) y= np.sin(x) ax_list[0].plot(x,y) y= np.cos(x) ax_list[1].plot(x,y) plt.show() # plt.subplot (creates figure and axes objects automatically) plt.subplot(2,2,1) y = np.sin(x) plt.plot(x,y) plt.subplot(2,2,2) y = np.cos(x) plt.plot(x,y) plt.subplot(2,1,2) y = np.tan(x) plt.plot(x,y) plt.show() # subplot2grid y = np.abs(x) z = x**2 plt.subplot2grid((4,3), (0, 0), rowspan=4, colspan=2) plt.plot(x, y,'b',x,z,'r') ax2 = plt.subplot2grid((4,3), (0, 2),rowspan=2) plt.plot(x, y,'b') plt.setp(ax2.get_xticklabels(), visible=False) plt.subplot2grid((4,3), (2, 2), rowspan=2) plt.plot(x, z,'r') plt.show() ### formatting y = x # color ax1 = plt.subplot(611) plt.plot(x,y,color='green') ax1.set_title('Line Color') plt.setp(ax1.get_xticklabels(), visible=False) # linestyle # linestyles -> '-','--','-.', ':', 'steps' ax2 = plt.subplot(612,sharex=ax1) plt.plot(x,y,linestyle='--') ax2.set_title('Line Style') plt.setp(ax2.get_xticklabels(), visible=False) # marker # markers -> '+', 'o', '*', 's', ',', '.', etc ax3 = plt.subplot(613,sharex=ax1) plt.plot(x,y,marker='*') ax3.set_title('Point Marker') plt.setp(ax3.get_xticklabels(), visible=False) # line width ax4 = plt.subplot(614,sharex=ax1) line = plt.plot(x,y) line[0].set_linewidth(3.0) ax4.set_title('Line Width') plt.setp(ax4.get_xticklabels(), visible=False) # alpha ax5 = plt.subplot(615,sharex=ax1) alpha = plt.plot(x,y) alpha[0].set_alpha(0.3) ax5.set_title('Line Alpha') plt.setp(ax5.get_xticklabels(), visible=False) # combine linestyle ax6 = plt.subplot(616,sharex=ax1) plt.plot(x,y,'b^') ax6.set_title('Styling Shorthand') fig = plt.gcf() fig.set_figheight(15) plt.show() # legends y = x**2 z = x plt.plot(x,y,'g',label='y=x^2') plt.plot(x,z,'b:',label='y=x') plt.legend(loc="best") plt.title('Legend Sample') plt.show() # legend with latex formatting plt.plot(x,y,'g',label='$y = x^2$') plt.plot(x,z,'b:',linewidth=3,label='$y = x^2$') plt.legend(loc="best",fontsize='x-large') plt.title('Legend with LaTEX formatting') plt.show() ## axis controls # secondary y-axis fig, ax1 = plt.subplots() ax1.plot(x,y,'g') ax1.set_ylabel(r"primary y-axis", color="green") ax2 = ax1.twinx() ax2.plot(x,z,'b:',linewidth=3) ax2.set_ylabel(r"secondary y-axis", color="blue") plt.title('Secondary Y Axis') plt.show() # ticks y = np.log(x) z = np.log2(x) w = np.log10(x) plt.plot(x,y,'r',x,z,'g',x,w,'b') plt.title('Default Axis Ticks') plt.show() # axis-controls plt.plot(x,y,'r',x,z,'g',x,w,'b') # values: tight, scaled, equal,auto plt.axis('tight') plt.title('Tight Axis') plt.show() # manual plt.plot(x,y,'r',x,z,'g',x,w,'b') plt.axis([0,2,-1,2]) plt.title('Manual Axis Range') plt.show() # Manual ticks plt.plot(x, y) ax = plt.gca() ax.xaxis.set_ticks(np.arange(-2, 2, 1)) plt.grid(True) plt.title("Manual ticks on the x-axis") plt.show() # minor ticks plt.plot(x, z) plt.minorticks_on() ax = plt.gca() ax.yaxis.set_ticks(np.arange(0, 5)) ax.yaxis.set_ticklabels(["min", 2, 4, "max"]) plt.title("Minor ticks on the y-axis") plt.show() # scaling plt.plot(x, y) ax = plt.gca() # values: log, logit, symlog ax.set_yscale("log") plt.grid(True) plt.title("Log Scaled Axis") plt.show() # annotations y = x**2 min_x = 0 min_y = min_x**2 plt.plot(x, y, "b-", min_x, min_y, "ro") plt.axis([-10,10,-25,100]) plt.text(0, 60, "Parabola\n$y = x^2$", fontsize=15, ha="center") plt.text(min_x, min_y+2, "Minima", ha="center") plt.text(min_x, min_y-6, "(%0.1f, %0.1f)"%(min_x, min_y), ha='center',color='gray') plt.title("Annotated Plot") plt.show() # global formatting params params = {'legend.fontsize': 'large', 'figure.figsize': (10, 10), 'axes.labelsize': 'large', 'axes.titlesize':'large', 'xtick.labelsize':'large', 'ytick.labelsize':'large'} plt.rcParams.update(params) # saving #plt.savefig("sample_plot.png", transparent=True)