Add linear plot to existing symlog plot

Question

I have some 2d data which I plot using this code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt 

def f():
    x=np.linspace(0,100,20000)
    return x, np.sin(x)*np.exp(x)

#this is the plotting function 
def symp(l,label,x_scale,y_scale):
    linthresh=10e-32
    for i in range(len(l)):
        style=[':','dashed','dashdot','dotted']
        dashes=[(5, 1),(3, 5),(3, 5, 1, 5), (1,1)]
        col=['Red','Green','Orange','Blue']
        csfont = {'fontname':'Leelawadee UI'}
        line= plt.plot(l[i][0],l[i][1])
        plt.xscale(x_scale)
        plt.yscale(y_scale,linthreshy=linthresh)
        plt.xticks(fontsize=10, fontweight='bold',**csfont)
        plt.yticks(fontsize=10, fontweight='bold',**csfont)
        plt.xlabel('x',fontsize=26, fontweight='bold',**csfont)
        plt.ylabel(label,fontsize=26, fontweight='bold',**csfont)
        plt.setp(line, linestyle=style[i],color=col[i],dashes=dashes[i])
        plt.locator_params(axis='y')
    plt.tight_layout()
    # plt.savefig(str(label+'.eps'), format='eps')
    plt.show()


symp([f()],r'${v}_{a}(x)$','log','symlog')

My goal is to plot only part of 1 array (for example f()[200:1000]) but linearly on the main plot. (In other words, I'm just zooming on my plot, I need it for my paper): How can I do this properly?

We don't need to see your loading code. We need an MCVE. Generate some suitable random data and show exactly what you want — Mad Physicist, Dec 13 '20 at 15:04
That helps, but it's still not an mcve. Does this answer your question: https://stackoverflow.com/q/21001088/2988730? — Mad Physicist, Dec 13 '20 at 15:45
Searching online for something like this is more likely to yield a result than asking an incomplete question. — Mad Physicist, Dec 13 '20 at 15:46

score 0 · Accepted Answer · answered Dec 13 '20 at 20:39

Inspired by How to add different graphs (as an inset) in another python graph ,

import numpy as np
import matplotlib.pyplot as plt 

def zsymp(l,label,x_scale,y_scale):
    linthresh=10e-32
    zf=np.where(va[0][1] > 0, va[0][1], np.inf).argmin()
    f=200
    fig, ax1 = plt.subplots()
    for i in range(len(l)):
        style=[':','dashed','dashdot','dotted']
        dashes=[(5, 1),(3, 5),(3, 5, 1, 5), (1,1)]
        col=['Red','Green','Orange','Blue']
        csfont = {'fontname':'Leelawadee UI'}
        line= plt.plot(l[i][0],l[i][1])
        plt.xscale(x_scale)
        plt.yscale(y_scale,linthreshy=linthresh)
        plt.xticks(fontsize=10, fontweight='bold',**csfont)
        plt.yticks(fontsize=10, fontweight='bold',**csfont)
        plt.xlabel('x',fontsize=26, fontweight='bold',**csfont)
        plt.ylabel(label,fontsize=26, fontweight='bold',**csfont)
        plt.setp(line, linestyle=style[i],color=col[i],dashes=dashes[i])
        plt.locator_params(axis='y')
    left, bottom, width, height = [0.2, 0.3, 0.28, 0.28]
    ax2 = fig.add_axes([left, bottom, width, height])
    line2=ax2.plot(l[0][0][zf-f:zf+f],l[0][1][zf-f:zf+f])
    plt.setp(line2, linestyle=style[0],color=col[0],dashes=dashes[0])
    # plt.tight_layout()
    plt.show()


def f():
    x=np.linspace(0,100,20000)
    return x, np.sin(x)*np.exp(x)
zsymp([f()],r'${v}_{a}(x)$','log','symlog')

I achieved my desired result:

Add linear plot to existing symlog plot

1 Answers1