CODEWITHSUNDEEP
pythonmatplotlib
zaza
zaza

Reputation: 912

How to offset x axis when plotting line graph in matlibplot

I'm trying to plot the number of features vs variance explained for PCA. I'd like to highlight when the variance is > 95% using the line color

I've got the following code so far..

pcaPlotData = {
    'r':var[np.argwhere(var < 95)],
    'g':var[np.argwhere(var >= 95)]
}

fig, ax = plt.subplots()
for k, v in pcaPlotData.items():
    ax.plot(v, color = k)
ax.set_ylabel('% Variance Explained')
ax.set_xlabel('# of Features')
ax.set_title('PCA Analysis')
ax.set_ylim(var.min(),var.max()+1)
plt.show()

which outputs the following plot: enter image description here

However the green line should start when the red line ends, how would i go about offsetting the green line?

Upvotes: 0

Views: 1010

Answers (2)

Sheldore
Sheldore

Reputation: 39042

If your input data is NumPy arrays, an alternative solution could look like the following. Here you create a conditional mask and then use ~mask to access the elements which do not fulfill the condition. This saves you from creating the mask twice.

Following is a complete runnable example:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(40)
var = x**2

# Define the conditional mask
mask = (var<95)

plt.plot(x[mask], var[mask], 'r') # Data fulfilling the condition
plt.plot(x[~mask], var[~mask], 'g') # Data not fulfilling the condition
plt.show()

enter image description here

Upvotes: 1

Julien
Julien

Reputation: 15070

Simply this:

x = np.argwhere(var < 95)
ax.plot(x, var[x], 'r')
x = np.argwhere(var >= 95)
ax.plot(x, var[x], 'g')

Upvotes: 0

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