CODEWITHSUNDEEP
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Sam Mend
Sam Mend

Reputation: 13

matplotlib graph plotting

I wish to plot a 2D scatter plot with values in the range [-0.5, 0.5] and [-0.5,0.5] for x and y coordinates respectively

fig1 = plt.figure(figsize=[7,7])
axes1 = fig1.add_axes([1,1,1,1])
axes1.set_xlabel("xlabel")
axes1.set_ylabel("ylabel")
axes1.set_title("Emotions Quadrants")
axes1.spines['left'].set_position(('axes', 0.5))
axes1.spines['bottom'].set_position(('axes', 0.5))
axes1.scatter(x_vals, y_vals, label="test")

above code scales and x and y coordinates according to to the data. I wish to show x and y coordinates from -0.5 to 0.5 equally spaced for both the axes and then plot the scatter graph

I wish to keep the axes intersecting at 0,0 and not scale according to the data points

Edit by taking x and y values as xvals = [0.237, 0.415, -0.264, 0.142, -0.037, -0.088, -0.143, -0.332, 0.166, -0.079] y vals= [0.265, 0.325, -0.069, 0.086, -0.136, 0.124, -0.051, -0.052, 0.280, 0.121]

I am getting following plot with @r-beginners answer [enter image description here][2]

I want the origin to be in the center and points not scaled and not shift downward [2]: https://i.sstatic.net/lxGIs.png

Upvotes: 1

Views: 155

Answers (2)

r-beginners
r-beginners

Reputation: 35240

If you set the axis to the desired range and the frame to the center, you will get the graph you want.

import matplotlib.pyplot as plt
import numpy as np

#x_vals = np.linspace(-0.5,0.5,10)
#y_vals = np.linspace(-0.5,0.5,10)

x_vals = [0.237, 0.415, -0.264, 0.142, -0.037, -0.088, -0.143, -0.332, 0.166, -0.079]
y_vals= [0.265, 0.325, -0.069, 0.086, -0.136, 0.124, -0.051, -0.052, 0.280, 0.121]

x_vals_center = (np.max(x_vals) + np.min(x_vals)) / 2
y_vals_center = (np.max(y_vals) + np.min(y_vals)) / 2

fig1 = plt.figure(figsize=[7,7])
axes1 = fig1.add_axes([-0.5,-0.5,0.5,0.5])
axes1.set_xlabel("xlabel", labelpad=0)
axes1.set_ylabel("ylabel", labelpad=110)
axes1.set_title("Emotions Quadrants")
axes1.spines[['top', 'right']].set_visible(False)
#axes1.spines[['left','bottom']].set_position(('data', 0))

axes1.spines['left'].set_position(('data', x_vals_center))
axes1.spines['bottom'].set_position(('data', y_vals_center))

axes1.xaxis.set_ticks_position('bottom')
axes1.yaxis.set_ticks_position('left')

axes1.scatter(x_vals, y_vals, label="test")

plt.show()

enter image description here

Upvotes: 1

Scott Boston
Scott Boston

Reputation: 153510

IIUC,

x_vals = [0.237, 0.415, -0.264, 0.142, -0.037, -0.088, -0.143, -0.332, 0.166, -0.079] 
y_vals= [0.265, 0.325, -0.069, 0.086, -0.136, 0.124, -0.051, -0.052, 0.280, 0.121] 

fig1 = plt.figure(figsize=[7,7])
axes1 = fig1.add_axes([-0.5,-0.5,0.5,0.5])
axes1.set_xlabel("xlabel", labelpad=110)
axes1.set_ylabel("ylabel", labelpad=110)
axes1.set_title("Emotions Quadrants")
axes1.spines['right'].set_visible(False)
axes1.spines['top'].set_visible(False)

axes1.spines['left'].set_position(('axes', 0.5))
axes1.spines['bottom'].set_position(('axes', 0.5))

axes1.xaxis.set_ticks_position('bottom')
axes1.yaxis.set_ticks_position('left')

axes1.scatter(x_vals, y_vals, label="test")
axes1.set_ylabel('Arousal')
axes1.set_xlabel('Valence')

axes1.set_ylim(-.5,.5)
axes1.set_xlim(-.5,.5)

plt.show()

Output: enter image description here

Upvotes: 1

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