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:
Related
I have a series of pyplot subplots that I've created using a gridspec. They all have an hspace between them, which is fine, except that I would like to keep three of them without any space. Is there a way to do this? Currently, they look like this:
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure()
grid_spec = gridspec.GridSpec(nrows=10, ncols=10)
grid_spec.update(hspace=1.5)
ax1 = plt.subplot(grid_spec[0:4, :])
ax2 = plt.subplot(grid_spec[4:7, :], sharex=ax1)
# I would like to group the next 3 together
# so that they are stacked top to bottom and side by side
ax3 = plt.subplot(grid_spec[7:8, :5])
ax4 = plt.subplot(grid_spec[8:, :5], sharex=ax3)
ax5 = plt.subplot(grid_spec[8:, 5:6], sharey=ax4)
plt.show()
I would like them to be arranged like this so I can plot the following 2-D KDE diagram and have the relevant 1-D diagrams above and to the right (roughly displaying this sort of data crudely drawn in paint):
I appreciate any help with this one. Can't seem to find documentation on this sort of thing. Thanks!
You can use mpl_toolkits.axes_grid1.make_axes_locatable to subdivide the area of a subplot of a 3 x 2 grid.
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
fig = plt.figure()
gs = fig.add_gridspec(nrows=3, ncols=2, hspace=.5,
height_ratios=[4, 3, 3], width_ratios=[7, 4])
ax1 = fig.add_subplot(gs[0, :])
ax2 = fig.add_subplot(gs[1, :], sharex=ax1)
ax3 = fig.add_subplot(gs[2, 0])
div = make_axes_locatable(ax3)
ax4 = div.append_axes("top", "40%", pad=0.2, sharex=ax3)
ax5 = div.append_axes("right", "25%", pad=0.2, sharey=ax3)
ax4.tick_params(labelbottom=False)
ax5.tick_params(labelleft=False)
plt.show()
Also, you can create a subgridspec, like
import matplotlib.pyplot as plt
from matplotlib import gridspec
fig = plt.figure()
gs = gridspec.GridSpec(nrows=3, ncols=2, hspace=.5,
height_ratios=[4, 3, 3], width_ratios=[7, 4])
ax1 = fig.add_subplot(gs[0, :])
ax2 = fig.add_subplot(gs[1, :], sharex=ax1)
sub_gs = gridspec.GridSpecFromSubplotSpec(2,2, subplot_spec=gs[2,0], hspace=0.3, wspace=0.1,
height_ratios=[1,3], width_ratios=[3,1])
ax3 = fig.add_subplot(sub_gs[1,0])
ax4 = fig.add_subplot(sub_gs[0,0], sharex=ax3)
ax5 = fig.add_subplot(sub_gs[1,1], sharey=ax3)
ax4.tick_params(labelbottom=False)
ax5.tick_params(labelleft=False)
plt.show()
In both cases you will probably want to fine tune the parameters a bit. In general, the matplotlib gridspec tutorial gives a nice overview with many examples on this matter.
I'm trying to remove the white space from the plot that I created:
As it is possible to see, there a big white spot on the right and also on the bottom, how to fix it? Here is my script:
fig = plt.figure(figsize=(7,7))
ax1 = plt.subplot2grid((4,3), (0,0),)
ax2 = plt.subplot2grid((4,3), (1,0),)
ax3 = plt.subplot2grid((4,3), (0,1),)
ax4 = plt.subplot2grid((4,3), (1,1),)
data = self.dframe[i]
tes = print_data(data, self.issues, self.color, self.type_user)
tes.print_top(data=data, top=10, ax=ax1, typegraph="hbar", problem=self.issues[i], tone=self.color[i])
tes.print_top(data=data, top=10, ax=ax2, typegraph="prod_bar", problem=self.issues[i], tone=self.color[i])
tes.print_top(data=data, top=10, ax=ax3, typegraph="reg_hbar", problem=self.issues[i], tone=self.color[i])
tes.print_top(data=data, top=10, ax=ax4, typegraph=self.type_user, problem=self.issues[i], tone=self.color[i])
problem = self.issues[i]
plt.tight_layout()
name = problem + str('.PNG')
plt.close(fig)
fig.savefig(name)
You are creating too many subplots!
If we look at this line:
ax1 = plt.subplot2grid((4,3), (0,0),)
We can see the first argument given to subplot2grid are the dimensions of the subplot grid to be made, in this case 4 rows, and 3 columns. You are then plotting in the subplots in the top left of your figure (the second argument given) which leaves a lot of space that's not used.
So to solve this, reduce the number of subplots by using:
ax1 = plt.subplot2grid((2,2), (0,0),)
Full example:
import numpy as np
import matplotlib.pyplot as plt
data = np.random.randn(25)
fig = plt.figure(figsize=(7,7))
ax1 = plt.subplot2grid((2,2), (0,0),)
ax2 = plt.subplot2grid((2,2), (1,0),)
ax3 = plt.subplot2grid((2,2), (0,1),)
ax4 = plt.subplot2grid((2,2), (1,1),)
ax1.plot(data)
ax2.plot(data)
ax3.plot(data)
ax4.plot(data)
plt.show()
Giving:
you can use
plt.subplots_adjust(left=0.09, bottom=0.07, right=0.98, top=0.97, wspace=0.2 , hspace=0.17 ) to adjust the window.
But the issue is that a lot of the space in your plot is empty
maybe you should change
plt.subplot2grid((4,3)... to plt.subplot2grid((2,2)
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:
The Python/pyplot code below generates four figures and four windows. I need code that opens one window showing fig1. Then when the user presses right arrow button or right arrow key the same window clears fig1 and shows fig2. So basically only one of the four figures will be selected by the user for viewing in a slideshow. I have searched for an answer in the docs and online without success. I have edited the question to show the definition of six axes that appear in the four figures. It appears that one must associate the axes with a single figure and then draw, clear, and redraw axes to simulate a slideshow in the default GUI?
import numpy as np
import matplotlib.pyplot as plt
fig1 = plt.figure()
ax1 = fig1.add_subplot(3, 1, 1)
ax2 = fig1.add_subplot(3, 1, 2, sharex=ax1)
ax3 = fig1.add_subplot(3, 1, 3, sharex=ax1)
fig2 = plt.figure()
ax4 = fig2.add_subplot(1, 1, 1)
fig3 = plt.figure()
ax5 = fig2.add_subplot(1, 1, 1)
fig4 = plt.figure()
ax6 = fig2.add_subplot(1, 1, 1)
plt.show()
Ideally I would like to set the backend to ensure the same code functions on MacOS, Linux, and Windows. However I would be satisfied to get a very basic slideshow working on Windows 7 and develop for other OS later if necessary.
Maybe something like this:
(click on the graph to switch)
import matplotlib.pyplot as plt
import numpy as np
i = 0
def fig1(fig):
ax = fig.add_subplot(111)
ax.plot(x, np.sin(x))
def fig2(fig):
ax = fig.add_subplot(111)
ax.plot(x, np.cos(x))
def fig3(fig):
ax = fig.add_subplot(111)
ax.plot(x, np.tan(x))
def fig4(fig):
ax1 = fig.add_subplot(311)
ax1.plot(x, np.sin(x))
ax2 = fig.add_subplot(312)
ax2.plot(x, np.cos(x))
ax3 = fig.add_subplot(313)
ax3.plot(x, np.tan(x))
switch_figs = {
0: fig1,
1: fig2,
2: fig3,
3: fig4
}
def onclick1(fig):
global i
print(i)
fig.clear()
i += 1
i %= 4
switch_figs[i](fig)
plt.draw()
x = np.linspace(0, 2*np.pi, 1000)
fig = plt.figure()
switch_figs[0](fig)
fig.canvas.mpl_connect('button_press_event', lambda event: onclick1(fig))
plt.show()
I've create the following set of subplots using the following function:
def create31fig(size,xlabel,ylabel,title=None):
fig = plt.figure(figsize=(size,size))
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312)
ax3 = fig.add_subplot(313)
plt.subplots_adjust(hspace=0.001)
plt.subplots_adjust(wspace=0.001)
ax1.set_xticklabels([])
ax2.set_xticklabels([])
xticklabels = ax1.get_xticklabels()+ ax2.get_xticklabels()
plt.setp(xticklabels, visible=False)
ax1.set_title(title)
ax2.set_ylabel(ylabel)
ax3.set_xlabel(xlabel)
return ax1,ax2,ax3
How do I make sure the top and bottom of subplot(312) do not overlap with their neighbours? Thanks.
In the ticker module there is a class called MaxNLocator that can take a prune kwarg.
Using that you can remove the topmost tick of the 2nd and 3rd subplots:
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator # added
def create31fig(size,xlabel,ylabel,title=None):
fig = plt.figure(figsize=(size,size))
ax1 = fig.add_subplot(311)
ax2 = fig.add_subplot(312)
ax3 = fig.add_subplot(313)
plt.subplots_adjust(hspace=0.001)
plt.subplots_adjust(wspace=0.001)
ax1.set_xticklabels([])
ax2.set_xticklabels([])
xticklabels = ax1.get_xticklabels() + ax2.get_xticklabels()
plt.setp(xticklabels, visible=False)
ax1.set_title(title)
nbins = len(ax1.get_xticklabels()) # added
ax2.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper')) # added
ax2.set_ylabel(ylabel)
ax3.yaxis.set_major_locator(MaxNLocator(nbins=nbins,prune='upper')) # added
ax3.set_xlabel(xlabel)
return ax1,ax2,ax3
create31fig(5,'xlabel','ylabel',title='test')
Sample image after making those adjustments:
Aside: If the overlapping x- and y- labels in the lowest subplot are an issue consider "pruning" one of those as well.