Maroof G Maroof G - 1 month ago 28
Python Question

Matplotlib: Gridspec not displaying bar subplot

I have a 4x3 grid. I have 1 broken horizontal bar plot in the first row followed by 9 scatter plots. The height of the bar plot needs to be 2x height of the scatter plots. I am using gridspec to achieve this. However, it doesn't plot the bar plot completely. See picture below:

enter image description here

The complete bar plot looks like this

enter image description here

I am not sure why is this happening. Any suggestions?

Here's my code:

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import gridspec

#####Importing Data from csv file#####

dataset1 = np.genfromtxt('dataSet1.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])
dataset2 = np.genfromtxt('dataSet2.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])
dataset3 = np.genfromtxt('dataSet3.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])

corr1 = np.corrcoef(dataset1['a'],dataset1['x0'])
corr2 = np.corrcoef(dataset1['b'],dataset1['x0'])
corr3 = np.corrcoef(dataset1['c'],dataset1['x0'])
corr4 = np.corrcoef(dataset2['a'],dataset2['x0'])
corr5 = np.corrcoef(dataset2['b'],dataset2['x0'])
corr6 = np.corrcoef(dataset2['c'],dataset2['x0'])
corr7 = np.corrcoef(dataset3['a'],dataset3['x0'])
corr8 = np.corrcoef(dataset3['b'],dataset3['x0'])
corr9 = np.corrcoef(dataset3['c'],dataset3['x0'])

fig = plt.figure(figsize = (8,8))
gs = gridspec.GridSpec(4, 3, height_ratios=[2,1,1,1])

def tornado1():
np.set_printoptions(precision=4)

variables = ['a1','b1','c1','a2','b2','c2','a3','b3','c3']
base = 0
values = np.array([corr1[0,1],corr2[0,1],corr3[0,1],
corr4[0,1],corr5[0,1],corr6[0,1],
corr7[0,1],corr8[0,1],corr9[0,1]])
variables=zip(*sorted(zip(variables, values),reverse = True, key=lambda x: abs(x[1])))[0]
values = sorted(values,key=abs, reverse=True)

# The y position for each variable
ys = range(len(values))[::-1] # top to bottom

# Plot the bars, one by one
for y, value in zip(ys, values):
high_width = base + value

# Each bar is a "broken" horizontal bar chart
ax1= plt.subplot(gs[1]).broken_barh(
[(base, high_width)],
(y - 0.4, 0.8),
facecolors=['red', 'red'], # Try different colors if you like
edgecolors=['black', 'black'],
linewidth=1,
)

# Draw a vertical line down the middle
plt.axvline(base, color='black')

# Position the x-axis on the top/bottom, hide all the other spines (=axis lines)
axes = plt.gca() # (gca = get current axes)
axes.spines['left'].set_visible(False)
axes.spines['right'].set_visible(False)
axes.spines['top'].set_visible(False)
axes.xaxis.set_ticks_position('bottom')

# Make the y-axis display the variables
plt.yticks(ys, variables)

plt.ylim(-2, len(variables))

plt.draw()
return

def correlation1():

corr1 = np.corrcoef(dataset1['a'],dataset1['x0'])
print corr1[0,1]
corr2 = np.corrcoef(dataset1['b'],dataset1['x0'])
print corr2[0,1]
corr3 = np.corrcoef(dataset1['c'],dataset1['x0'])
print corr3[0,1]

ax2=plt.subplot(gs[3])
ax2.scatter(dataset1['a'],dataset1['x0'],marker = '.')
ax2.set_xlabel('a1')
ax2.set_ylabel('x01')
ax3=plt.subplot(gs[4])
ax3.scatter(dataset1['b'],dataset1['x0'],marker = '.')
ax3.set_xlabel('b1')
#ax3.set_ylabel('x01')
ax4=plt.subplot(gs[5])
ax4.scatter(dataset1['c'],dataset1['x0'],marker = '.')
ax4.set_xlabel('c1')
#ax4.set_ylabel('x01')
ax5=fig.add_subplot(gs[6])
ax5.scatter(dataset2['a'],dataset2['x0'],marker = '.')
ax5.set_xlabel('a2')
ax5.set_ylabel('x02')
ax6=fig.add_subplot(gs[7])
ax6.scatter(dataset2['b'],dataset2['x0'],marker = '.')
ax6.set_xlabel('b2')
#ax6.set_ylabel('x02')
ax7=fig.add_subplot(gs[8])
ax7.scatter(dataset2['c'],dataset2['x0'],marker = '.')
ax7.set_xlabel('c2')
#ax7.set_ylabel('x02')
ax8=plt.subplot(gs[9])
ax8.scatter(dataset3['a'],dataset3['x0'],marker = '.')
ax8.set_xlabel('a3')
ax8.set_ylabel('x03')
ax9=plt.subplot(gs[10])
ax9.scatter(dataset3['b'],dataset3['x0'],marker = '.')
ax9.set_xlabel('b3')
#ax9.set_ylabel('x03')
ax10=plt.subplot(gs[11])
ax10.scatter(dataset3['c'],dataset3['x0'],marker = '.')
ax10.set_xlabel('c3')
#ax10.set_ylabel('x03')

plt.show()
return

tornado1()
correlation1()
plt.tight_layout()
plt.show()


Any help would be highly appreciated :-)

Answer

In the block of code:

# Plot the bars, one by one
for y, value in zip(ys, values):
    high_width = base + value

    # Each bar is a "broken" horizontal bar chart
    ax1= plt.subplot(gs[1]).broken_barh(
        [(base, high_width)],
        (y - 0.4, 0.8),
        facecolors=['red', 'red'],  # Try different colors if you like
        edgecolors=['black', 'black'],
        linewidth=1,
    )

You're reinitializing gs[1] on each loop so in the end, your plot only contains the last bar. You should try something like this instead:

# Plot the bars, one by one
ax1 = plt.subplot(gs[1])

for y, value in zip(ys, values):
    high_width = base + value

    # Each bar is a "broken" horizontal bar chart
    ax1.broken_barh(
        [(base, high_width)],
        (y - 0.4, 0.8),
        facecolors=['red', 'red'],  # Try different colors if you like
        edgecolors=['black', 'black'],
        linewidth=1,
    )

Hope that helps.

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