### Question :

Matplotlib different size subplots

I need to add two subplots to a figure. One subplot needs to be about three times as wide as the second (same height). I accomplished this using `GridSpec`

and the `colspan`

argument but I would like to do this using `figure`

so I can save to PDF. I can adjust the first figure using the `figsize`

argument in the constructor, but how do I change the size of the second plot?

##
Answer #1:

Another way is to use the `subplots`

function and pass the width ratio with `gridspec_kw`

:

```
import numpy as np
import matplotlib.pyplot as plt
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
f, (a0, a1) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})
a0.plot(x, y)
a1.plot(y, x)
f.tight_layout()
f.savefig('grid_figure.pdf')
```

##
Answer #2:

You can use `gridspec`

and `figure`

:

```
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
fig = plt.figure(figsize=(8, 6))
gs = gridspec.GridSpec(1, 2, width_ratios=[3, 1])
ax0 = plt.subplot(gs[0])
ax0.plot(x, y)
ax1 = plt.subplot(gs[1])
ax1.plot(y, x)
plt.tight_layout()
plt.savefig('grid_figure.pdf')
```

##
Answer #3:

I used `pyplot`

‘s `axes`

object to manually adjust the sizes without using `GridSpec`

:

```
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# definitions for the axes
left, width = 0.07, 0.65
bottom, height = 0.1, .8
bottom_h = left_h = left+width+0.02
rect_cones = [left, bottom, width, height]
rect_box = [left_h, bottom, 0.17, height]
fig = plt.figure()
cones = plt.axes(rect_cones)
box = plt.axes(rect_box)
cones.plot(x, y)
box.plot(y, x)
plt.show()
```

##
Answer #4:

Probably the simplest way is using `subplot2grid`

, described in Customizing Location of Subplot Using GridSpec.

```
ax = plt.subplot2grid((2, 2), (0, 0))
```

is equal to

```
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2)
ax = plt.subplot(gs[0, 0])
```

so bmu’s example becomes:

```
import numpy as np
import matplotlib.pyplot as plt
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
fig = plt.figure(figsize=(8, 6))
ax0 = plt.subplot2grid((1, 3), (0, 0), colspan=2)
ax0.plot(x, y)
ax1 = plt.subplot2grid((1, 3), (0, 2))
ax1.plot(y, x)
plt.tight_layout()
plt.savefig('grid_figure.pdf')
```