Just wandering - how can one obtain the size of a subplot (axes?) in Matplotlib?
If I do Ctrl-F "size" in https://matplotlib.org/3.1.1/api/axes_api.html - there is only one match, in context: "... with varying marker size and/or ...", so it does not really tell me how to find the size of the axes.
Say, I have the same code as in Interactively resize figure and toggle plot visibility in Matplotlib?
#!/usr/bin/env python3
import matplotlib
print("matplotlib.__version__ {}".format(matplotlib.__version__))
import matplotlib.pyplot as plt
import numpy as np
default_size_inch = (9, 6)
showThird = False
def onpress(event):
global fig, ax1, ax2, ax3, showThird
if event.key == 'x':
showThird = not showThird
if showThird:
fig.set_size_inches(default_size_inch[0]+3, default_size_inch[1], forward=True)
plt.subplots_adjust(right=0.85) # leave a bit of space on the right
ax3.set_visible(True)
ax3.set_axis_on()
else:
fig.set_size_inches(default_size_inch[0], default_size_inch[1], forward=True)
plt.subplots_adjust(right=0.9) # default
ax3.set_visible(False)
ax3.set_axis_off()
fig.canvas.draw()
def main():
global fig, ax1, ax2, ax3
xdata = np.arange(0, 101, 1) # 0 to 100, both included
ydata1 = np.sin(0.01*xdata*np.pi/2)
ydata2 = 10*np.sin(0.01*xdata*np.pi/4)
fig = plt.figure(figsize=default_size_inch, dpi=120)
ax1 = plt.subplot2grid((3,3), (0,0), colspan=2, rowspan=2)
ax2 = plt.subplot2grid((3,3), (2,0), colspan=2, sharex=ax1)
ax3 = plt.subplot2grid((3,3), (0,2), rowspan=3)
ax3.set_visible(False)
ax3.set_axis_off()
ax1.plot(xdata, ydata1, color="Red")
ax2.plot(xdata, ydata2, color="Khaki")
fig.canvas.mpl_connect('key_press_event', lambda event: onpress(event))
plt.show()
# ENTRY POINT
if __name__ == '__main__':
main()
How do I find the size of the subplots represented by ax1 and ax2 axes?
For the full explanation of how bbox works refer to here. Each of your axes object fits in a bounding box. All you need to do is to get the height and width of your axis bounding box.
ax_h, ax_w = ax.bbox.height, ax.bbox.width
You can transform to figure coordinates by using bbox.transformed method. For example:
ax_h = ax.bbox.transformed(fig.gca().transAxes).height
Related
I would like to create a plot that consists of three subplots, where the upper left plot has the same width as the lower left plot but 1/3 of the height. Besides, I'd also like to plot the legend in the upper right area from the lower left plot. Is this even possible?
fig, ax = plt.subplots(2, figsize = (16,9))
ax1 = plt.subplot2grid((2,3), (1,0), colspan=2)
ax2 = plt.subplot2grid((2,3), (1,2), colspan=1)
ax3 = plt.subplot2grid((2,3), (0,0), colspan=2)
fig.suptitle('Title')
fig.tight_layout()
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import numpy as np
x = np.linspace(0, 2*np.pi)
y1 = np.cos(x)
y2 = np.sin(x)
fig = plt.figure()
gs = GridSpec(2, 2, width_ratios=[2, 1], height_ratios=[1, 3])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1])
ax3 = fig.add_subplot(gs[2])
ax4 = fig.add_subplot(gs[3])
ax3.plot(x, y1, label="cos")
ax3.plot(x, y2, label="sin")
handles, labels = ax3.get_legend_handles_labels()
# hide axis on the top left subplot
ax2.axis("off")
# adding two legends
legend1 = ax2.legend([handles[0]], [labels[0]], loc="upper left")
legend2 = ax2.legend([handles[1]], [labels[1]], loc="lower right")
ax2.add_artist(legend1)
plt.tight_layout()
I've got a figure that contains three subplots which are arranged vertically. Once I click into the figure, I want the second subplot ax2 to be hidden and the other plots to fill the space. A second click into the figure should restore the original plot and layout.
Hiding the subplot ax2 isn't a problem, but how can I rearrange the positions of the other subplots?
I've tried creating a new GridSpec, using the set_position and set_subplotspec methods, but nothing worked out. I'm sure I'm missing something here, any help would be appreciated.
This is my code:
import matplotlib.pyplot as plt
from matplotlib import gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
You can define two different GridSpecs. One would have 3 subplots, the other 2. Depending on the visibility of the middle axes, you change the position of the other two axes to obey to the first or second GridSpec.
(There is no need for any dummy figure or so, like other answers might suggest.)
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1], hspace=0.3)
gs2 = gridspec.GridSpec(2,1, height_ratios=[5,3])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
ax1.plot([1,2,3], [1,2,3], color="crimson")
ax2.plot([1,2,3], [2,3,1], color="darkorange")
ax3.plot([1,2,3], [3,2,1], color="limegreen")
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
if visible:
ax1.set_position(gs[0].get_position(fig))
ax3.set_position(gs[2].get_position(fig))
else:
ax1.set_position(gs2[0].get_position(fig))
ax3.set_position(gs2[1].get_position(fig))
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
Left: original; right: after clicking
You can create a new gridspec instance, and use that to create some dummy figures in a second figure (you can close this before you plt.show, so you never actually see it, we just want to grab some positions from the axes here).
By storing the two possible positions for ax1 and ax3 from that dummy figure and the original figure, then you can use ax.set_position() in your toggle_ax2 function to change the positions of the remaining two axes.
import matplotlib.pyplot as plt
from matplotlib import gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
# Store the original positions of ax1 and ax3
pos1_1 = ax1.get_position()
pos3_1 = ax3.get_position()
# Create a second gridspec for when ax2 is hidden. Keep 5:1 ratio
gs2 = gridspec.GridSpec(2, 1, height_ratios=[5, 1])
fig2 = plt.figure()
ax1_2 = fig2.add_subplot(gs2[0])
ax3_2 = fig2.add_subplot(gs2[1])
# Store the positions of ax1 and ax3 in the new gridspec
pos1_2 = ax1_2.get_position()
pos3_2 = ax3_2.get_position()
# Close the dummy figure2
plt.close(fig2)
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
# Use the stored positions to switch between
# different arrangements of ax1 and ax3
if visible:
ax1.set_position(pos1_1)
ax3.set_position(pos3_1)
else:
ax1.set_position(pos1_2)
ax3.set_position(pos3_2)
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
Original configuration:
After removing ax2:
I've got a figure that contains three subplots which are arranged vertically. Once I click into the figure, I want the second subplot ax2 to be hidden and the other plots to fill the space. A second click into the figure should restore the original plot and layout.
Hiding the subplot ax2 isn't a problem, but how can I rearrange the positions of the other subplots?
I've tried creating a new GridSpec, using the set_position and set_subplotspec methods, but nothing worked out. I'm sure I'm missing something here, any help would be appreciated.
This is my code:
import matplotlib.pyplot as plt
from matplotlib import gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
You can define two different GridSpecs. One would have 3 subplots, the other 2. Depending on the visibility of the middle axes, you change the position of the other two axes to obey to the first or second GridSpec.
(There is no need for any dummy figure or so, like other answers might suggest.)
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1], hspace=0.3)
gs2 = gridspec.GridSpec(2,1, height_ratios=[5,3])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
ax1.plot([1,2,3], [1,2,3], color="crimson")
ax2.plot([1,2,3], [2,3,1], color="darkorange")
ax3.plot([1,2,3], [3,2,1], color="limegreen")
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
if visible:
ax1.set_position(gs[0].get_position(fig))
ax3.set_position(gs[2].get_position(fig))
else:
ax1.set_position(gs2[0].get_position(fig))
ax3.set_position(gs2[1].get_position(fig))
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
Left: original; right: after clicking
You can create a new gridspec instance, and use that to create some dummy figures in a second figure (you can close this before you plt.show, so you never actually see it, we just want to grab some positions from the axes here).
By storing the two possible positions for ax1 and ax3 from that dummy figure and the original figure, then you can use ax.set_position() in your toggle_ax2 function to change the positions of the remaining two axes.
import matplotlib.pyplot as plt
from matplotlib import gridspec
fig = plt.figure()
gs = gridspec.GridSpec(3, 1, height_ratios=[5, 2, 1])
ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1], sharex=ax1)
ax3 = fig.add_subplot(gs[2], sharex=ax2)
# Store the original positions of ax1 and ax3
pos1_1 = ax1.get_position()
pos3_1 = ax3.get_position()
# Create a second gridspec for when ax2 is hidden. Keep 5:1 ratio
gs2 = gridspec.GridSpec(2, 1, height_ratios=[5, 1])
fig2 = plt.figure()
ax1_2 = fig2.add_subplot(gs2[0])
ax3_2 = fig2.add_subplot(gs2[1])
# Store the positions of ax1 and ax3 in the new gridspec
pos1_2 = ax1_2.get_position()
pos3_2 = ax3_2.get_position()
# Close the dummy figure2
plt.close(fig2)
visible = True
def toggle_ax2(event):
global visible
visible = not visible
ax2.set_visible(visible)
# Use the stored positions to switch between
# different arrangements of ax1 and ax3
if visible:
ax1.set_position(pos1_1)
ax3.set_position(pos3_1)
else:
ax1.set_position(pos1_2)
ax3.set_position(pos3_2)
plt.draw()
fig.canvas.mpl_connect('button_press_event', toggle_ax2)
plt.show()
Original configuration:
After removing ax2:
Having an example code for a scatter plot along with their histograms
x = np.random.rand(5000,1)
y = np.random.rand(5000,1)
fig = plt.figure(figsize=(7,7))
ax = fig.add_subplot(111)
ax.scatter(x, y, facecolors='none')
ax.set_xlim(0,1)
ax.set_ylim(0,1)
fig1 = plt.figure(figsize=(7,7))
ax1 = fig1.add_subplot(111)
ax1.hist(x, bins=25, fill = None, facecolor='none',
edgecolor='black', linewidth = 1)
fig2 = plt.figure(figsize=(7,7))
ax2 = fig2.add_subplot(111)
ax2.hist(y, bins=25 , fill = None, facecolor='none',
edgecolor='black', linewidth = 1)
What I'm wanting to do is to create this graph with the histograms attached to their respected axis almost like this example
I'm familiar with stacking and merging the x-axis
f, (ax1, ax2, ax3) = plt.subplots(3)
ax1.scatter(x, y)
ax2.hist(x, bins=25, fill = None, facecolor='none',
edgecolor='black', linewidth = 1)
ax3.hist(y, bins=25 , fill = None, facecolor='none',
edgecolor='black', linewidth = 1)
f.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in f.axes[:-1]], visible=False)
But I have no idea how to attach the histograms to the y axis and x axis like in the picture I posted above, and on top of that, how to vary the size of the graphs (ie make the scatter plot larger and the histograms smaller in comparison)
Seaborn is the way to go for quick statistical plots. But if you want to avoid another dependency you can use subplot2grid to place the subplots and the keywords sharex and sharey to make sure the axes are synchronized.
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randn(100)
y = np.random.randn(100)
scatter_axes = plt.subplot2grid((3, 3), (1, 0), rowspan=2, colspan=2)
x_hist_axes = plt.subplot2grid((3, 3), (0, 0), colspan=2,
sharex=scatter_axes)
y_hist_axes = plt.subplot2grid((3, 3), (1, 2), rowspan=2,
sharey=scatter_axes)
scatter_axes.plot(x, y, '.')
x_hist_axes.hist(x)
y_hist_axes.hist(y, orientation='horizontal')
You should always look at the matplotlib gallery before asking how to plot something, chances are that it will save you a few keystrokes -- I mean you won't have to ask. There are actually two plots like this in the gallery. Unfortunately the code is old and does not take advantage of subplot2grid, the first one uses rectangles and the second one uses axes_grid, which is a somewhat weird beast. That's why I posted this answer.
I think it's hard to do this solely with matplotlib but you can use seaborn which has jointplot function.
import numpy as np
import pandas as pd
import seaborn as sns
sns.set(color_codes=True)
x = np.random.rand(1000,1)
y = np.random.rand(1000,1)
data = np.column_stack((x,y))
df = pd.DataFrame(data, columns=["x", "y"])
sns.jointplot(x="x", y="y", data=df);
import matplotlib.pyplot as plt
plt.figure()
plt.xlabel('x')
plt.ylabel('y')
plt.plot([0,1],[1,0])
plt.show()
I would like to be able to resize just the plot itself, NOT the entire window, without having to physically resize it. For example, I would like to have the x axis be only 0.75 times as long as it currently is and the y-axis be only 0.5 times long. Remember, I'm just talking about the plotted part itself, not the entire window. But how?
If I understand your question correctly, what you are looking for is the GridSpec function in the matplotlib module.
you can use :
import matplotlib.pyplot as plt
def make_ticklabels_invisible(fig):
for i, ax in enumerate(fig.axes):
ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
for tl in ax.get_xticklabels() + ax.get_yticklabels():
tl.set_visible(False)
plt.figure(0)
ax1 = plt.subplot2grid((3,3), (0,0), colspan=3)
ax2 = plt.subplot2grid((3,3), (1,0), colspan=2)
ax3 = plt.subplot2grid((3,3), (1, 2), rowspan=2)
ax4 = plt.subplot2grid((3,3), (2, 0))
ax5 = plt.subplot2grid((3,3), (2, 1))
plt.suptitle("subplot2grid")
make_ticklabels_invisible(plt.gcf())
plt.show()
which will return us the following example :
for further information you can visit this link