CODEWITHSUNDEEP
pythonnumpymatplotlib
user3211991
user3211991

Reputation: 461

Separating arrays with numpy to plot with matplotlib in python

I have an array containing 2 data curves, imported from excel. Below is my array. Column 1 is the x axis, while column 3 is the y axis.

[[  0.00000000e+00   8.57250668e-06   0.00000000e+00]
 [  1.88000000e+03   8.57250668e-06   1.88617039e-01]
 [  8.01000000e+03   8.57250668e-06   3.42702439e-01]
 [  8.16300000e+04   8.57250668e-06   4.43486869e-01]
 [  0.00000000e+00   1.49761692e-05   0.00000000e+00]
 [  2.09000000e+03   1.49761692e-05   1.58760000e-01]
 [  8.22000000e+03   1.49761692e-05   2.54700000e-01]
 [  8.18400000e+04   1.49761692e-05   2.92848750e-01]]

Here is my code

import numpy as np
import matplotlib.pyplot as plt 

A = np.array(
[[0.00000000e+00, 8.57250668e-06, 0.00000000e+00],
 [1.88000000e+03, 8.57250668e-06, 1.88617039e-01],
 [8.01000000e+03, 8.57250668e-06, 3.42702439e-01],
 [8.16300000e+04, 8.57250668e-06, 4.43486869e-01],
 [0.00000000e+00, 1.49761692e-05, 0.00000000e+00],
 [2.09000000e+03, 1.49761692e-05, 1.58760000e-01],
 [8.22000000e+03, 1.49761692e-05, 2.54700000e-01],
 [8.18400000e+04, 1.49761692e-05, 2.92848750e-01]])

print A
x= A[:,0]
c0= A[:,1]
y_meas= A[:,2]

plt.plot(x,y_meas,'-b') 

plt.title('Reaction') 
plt.legend(['Data'], loc='lower right')
plt.show()

Here is my plotted data

Obviously this is not what I want. How do I keep the 2 curves within the array separately, such that I can have 2 discrete curves?

Upvotes: 1

Views: 3831

Answers (2)

HYRY
HYRY

Reputation: 97271

You can insert NANs rows into A, then the line will be split into parts by NANs.

import numpy as np
import matplotlib.pyplot as plt 

A = np.array(
[[0.00000000e+00, 8.57250668e-06, 0.00000000e+00],
 [1.88000000e+03, 8.57250668e-06, 1.88617039e-01],
 [8.01000000e+03, 8.57250668e-06, 3.42702439e-01],
 [8.16300000e+04, 8.57250668e-06, 4.43486869e-01],
 [0.00000000e+00, 1.49761692e-05, 0.00000000e+00],
 [2.09000000e+03, 1.49761692e-05, 1.58760000e-01],
 [8.22000000e+03, 1.49761692e-05, 2.54700000e-01],
 [8.18400000e+04, 1.49761692e-05, 2.92848750e-01]])

idx = np.where(np.diff(A[:, 0]).ravel() < 0)[0] + 1

A2 = np.insert(A, idx, np.nan, axis=0)

x, c0, y_meas = A2.T

plt.plot(x,y_meas,'-b') 

plt.title('Reaction') 
plt.legend(['Data'], loc='lower right')
plt.show()

output:

enter image description here

If you want each line with different color, you can split A:

idx = np.where(np.diff(A[:, 0]).ravel() < 0)[0] + 1
for A2 in np.split(A, idx):
    x, c0, y_meas = A2.T
    plt.plot(x,y_meas)

output:

enter image description here

Upvotes: 1

cosmosis
cosmosis

Reputation: 6257

It's a little hard to tell what you are trying to produce. But looking at the x- and y-axis data points, it's clear that you are dealing with data that begins at zero, increases, then goes back to zero. So, assuming that these are the two curves that you could have to plot, you can separate the array as follow:

x1= A[:,0][:4]
x2= A[:,0][4:]
c0= A[:,1]
y_meas1= A[:,2][:4]       
y_meas2= A[:,2][4:]

plt.plot(x1,y_meas1,'-b') 
plt.plot(x2,y_meas2,'-g') 

plt.title('Reaction') 
plt.legend(['Data1', 'Data2'], loc='lower right')
plt.show()

enter image description here

If you have more data than just these 8 data points within the array, you could create a loop to automatically parse the array by checking for when the x- or y-coordinates (or both) are equivalent to zero and saving the previous x- and y-values (within a range) in order to plot them. In this way you wouldn't have to create all of the arrays by hand. Hope this helps.

Upvotes: 2

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