I have an issue where adding tick labels interferes with my given padding preference between subplots. What I want, is a tight_layout with no padding at all in between, but with some custom ticks along the x-axis. This snippet and resulting figures shows the issue:
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig_names = ['fig1']
gs = gridspec.GridSpec(1, len(fig_names))
gs.update(hspace=0.0)
figs = dict()
for fig_name in fig_names:
figs[fig_name] = plt.figure(figsize=(3*len(fig_names),6))
for i in range(0,len(fig_names)):
ax = figs[fig_name].add_subplot(gs[i])
ax.plot([0,1],[0,1], 'r-')
if i != 0:
ax.set_yticks(list())
ax.set_yticklabels(list())
ax.set_xticks(list())
ax.set_xticklabels(list())
for name,fig in figs.items():
fig.text(0.5, 0.03, 'Common xlabel', ha='center', va='center')
gs.tight_layout(fig, h_pad=0.0, w_pad=0.0)
ax = fig.add_subplot(gs[len(fig_names)-1])
ax.legend(('Some plot'), loc=2)
plt.show()
By changing the corresponding lines into:
ax.set_xticks([0.5,1.0])
ax.set_xticklabels(['0.5','1.0'])
...unwanted padding is added to the graphs.
How can I customize the tick text so that the graph plots has no padding, regardless of what tick text I enter? The text may "overlap" with the next subplot.
Perhaps you could simply create the axes with plt.subplots:
import numpy as np
import matplotlib.pyplot as plt
fig, axs = plt.subplots(ncols=2, sharey=True)
for ax in axs:
ax.plot([0,1],[0,1], 'r-')
ax.set_xticks([0.5,1.0])
ax.set_xticklabels(['0.5','1.0'])
axs[-1].legend(('Some plot'), loc=2)
for ax in axs[1:]:
ax.yaxis.set_visible(False)
fig.subplots_adjust(wspace=0)
plt.show()
Related
I have a chart with data going below and above 0, and I want to have my x-axis with tick marks at y==0, while tick labels are still below the chart. Note that using axhline is not sufficient as I need tick marks. Also, there are workarounds on SO that use spines to put the top spine at 0, with tick marks, but in my case I would need to keep the spines add the top and bottom.
Is there a way to do this?
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(range(-2, 3))
plt.show()
Maybe this will help:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(range(-2, 3))
ax.spines['left'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position('zero')
ax.spines['top'].set_color('none')
ax.yaxis.tick_left()
ax.xaxis.tick_bottom()
ax.yaxis.set_label_coords(-0.1,0.5)
plt.show()
I am using matplotlib to
#Plot
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure(figsize=(8,8))
gs1 = gridspec.GridSpec(1, 2)
gs1.update(wspace=0.025, hspace=0.05) # set the spacing between axes.
ax1 = plt.subplot(gs1[0])
ax2 = plt.subplot(gs1[1])
ax1.axis('off')
ax1.set_xlabel('(a)')
ax2.axis('off')
ax2.set_xlabel('(b)')
Because I must turn off axis in the figure, hence, I used ax1.axis('off'). Now, I want to insert the figure description such as (a),(b) below each subplot. I used xlabel but it cannot work due to function axis('off'). I can have other options by using .text function, but it requires the known position. In my case, the text must be below and center in each subplot. How can I implement it. Thanks
My expected result is
The problem is if axis("off") is set, the xlabel is removed from the figure (together with all other artists that are part of the axis).
However, you may use some normal text label just below the axes to mimic the xlabel.
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
fig = plt.figure(figsize=(8,8))
gs1 = gridspec.GridSpec(1, 2)
gs1.update(wspace=0.025, hspace=0.05) # set the spacing between axes.
ax1 = plt.subplot(gs1[0])
ax1.imshow([[0,1],[2,1]])
ax2 = plt.subplot(gs1[1])
ax2.imshow([[2,1],[0,1]])
ax1.axis('off')
ax2.axis('off')
ax1.text(0.5,-0.1, "(a) my label", size=12, ha="center",
transform=ax1.transAxes)
ax2.text(0.5,-0.1, "(b) my other label", size=12, ha="center",
transform=ax2.transAxes)
plt.show()
Changing the -0.1 will give you more or less space between the axes and the text.
O am trying to work out how to place another plot, of a cubic shape, on the right of three subplots
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
gs1 = gridspec.GridSpec(3,2)
ax1 = plt.subplot(gs1[0, :])
ax2 = plt.subplot(gs1[1, :],sharex=ax1)
ax3 = plt.subplot(gs1[2, :],sharex=ax1)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.show()
How can I place another plot that spans the three rows next to those one using gridspec?
You've already defined a proper splitting for the gridspec by subdividing it into two columns. Specify that the left axes use the first column (see changes below) and the axes which is supposed to be "cubic" (aspect ratio 1) uses the right column of your gridspec.
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
gs1 = gridspec.GridSpec(3,2)
ax1 = plt.subplot(gs1[0, 0])
ax2 = plt.subplot(gs1[1, 0],sharex=ax1)
ax3 = plt.subplot(gs1[2, 0],sharex=ax1)
ax4 = plt.subplot(gs1[:, 1]) # NEW
ax4.set_aspect('equal', adjustable='box') # NEW
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.show()
Alternatively, you could define a second gridspec and update the (relative) positioning of each gridspec, like so:
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
gs1 = gridspec.GridSpec(3,2)
gs1.update(left=0.05, right=0.48, wspace=0.05)
ax1 = plt.subplot(gs1[0, :])
ax2 = plt.subplot(gs1[1, :],sharex=ax1)
ax3 = plt.subplot(gs1[2, :],sharex=ax1)
gs2 = gridspec.GridSpec(1, 1)
gs2.update(left=0.55, right=0.98, hspace=0.05)
ax4 = plt.subplot(gs2[0,0])
#ax4.set_aspect('equal', adjustable='box')
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.show()
I commented the code to get an equal aspect ratio in ax4, to highlight that by default, it fills the entire available space.
Here is an example that reproduces my problem:
import matplotlib.pyplot as plt
import numpy as np
data1,data2,data3,data4 = np.random.random(100),np.random.random(100),np.random.random(100),np.random.random(100)
fig,ax = plt.subplots()
ax.plot(data1)
ax.plot(data2)
ax.plot(data3)
ax2 = ax.twinx()
ax2.plot(data4)
plt.grid('on')
ax.legend(['1','2','3'], loc='center')
ax2.legend(['4'], loc=1)
How can I get the legend in the center to plot on top of the lines?
To get exactly what you have asked for, try the following. Note I have modified your code to define the labels when you generate the plot and also the colors so you don't get a repeated blue line.
import matplotlib.pyplot as plt
import numpy as np
data1,data2,data3,data4 = (np.random.random(100),
np.random.random(100),
np.random.random(100),
np.random.random(100))
fig,ax = plt.subplots()
ax.plot(data1, label="1", color="k")
ax.plot(data2, label="2", color="r")
ax.plot(data3, label="3", color="g")
ax2 = ax.twinx()
ax2.plot(data4, label="4", color="b")
# First get the handles and labels from the axes
handles1, labels1 = ax.get_legend_handles_labels()
handles2, labels2 = ax2.get_legend_handles_labels()
# Add the first legend to the second axis so it displaysys 'on top'
first_legend = plt.legend(handles1, labels1, loc='center')
ax2.add_artist(first_legend)
# Add the second legend as usual
ax2.legend(handles2, labels2)
plt.show()
Now I will add that it would be clearer if you just use a single legend adding all the lines to that. This is described in this SO post and in the code above can easily be achieved with
ax2.legend(handles1+handles2, labels1+labels2)
But obviously you may have your own reasons for wanting two legends.
The code below produces gaps between the subplots. How do I remove the gaps between the subplots and make the image a tight grid?
import matplotlib.pyplot as plt
for i in range(16):
i = i + 1
ax1 = plt.subplot(4, 4, i)
plt.axis('on')
ax1.set_xticklabels([])
ax1.set_yticklabels([])
ax1.set_aspect('equal')
plt.subplots_adjust(wspace=None, hspace=None)
plt.show()
The problem is the use of aspect='equal', which prevents the subplots from stretching to an arbitrary aspect ratio and filling up all the empty space.
Normally, this would work:
import matplotlib.pyplot as plt
ax = [plt.subplot(2,2,i+1) for i in range(4)]
for a in ax:
a.set_xticklabels([])
a.set_yticklabels([])
plt.subplots_adjust(wspace=0, hspace=0)
The result is this:
However, with aspect='equal', as in the following code:
import matplotlib.pyplot as plt
ax = [plt.subplot(2,2,i+1) for i in range(4)]
for a in ax:
a.set_xticklabels([])
a.set_yticklabels([])
a.set_aspect('equal')
plt.subplots_adjust(wspace=0, hspace=0)
This is what we get:
The difference in this second case is that you've forced the x- and y-axes to have the same number of units/pixel. Since the axes go from 0 to 1 by default (i.e., before you plot anything), using aspect='equal' forces each axis to be a square. Since the figure is not a square, pyplot adds in extra spacing between the axes horizontally.
To get around this problem, you can set your figure to have the correct aspect ratio. We're going to use the object-oriented pyplot interface here, which I consider to be superior in general:
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8,8)) # Notice the equal aspect ratio
ax = [fig.add_subplot(2,2,i+1) for i in range(4)]
for a in ax:
a.set_xticklabels([])
a.set_yticklabels([])
a.set_aspect('equal')
fig.subplots_adjust(wspace=0, hspace=0)
Here's the result:
You can use gridspec to control the spacing between axes. There's more information here.
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
plt.figure(figsize = (4,4))
gs1 = gridspec.GridSpec(4, 4)
gs1.update(wspace=0.025, hspace=0.05) # set the spacing between axes.
for i in range(16):
# i = i + 1 # grid spec indexes from 0
ax1 = plt.subplot(gs1[i])
plt.axis('on')
ax1.set_xticklabels([])
ax1.set_yticklabels([])
ax1.set_aspect('equal')
plt.show()
Without resorting gridspec entirely, the following might also be used to remove the gaps by setting wspace and hspace to zero:
import matplotlib.pyplot as plt
plt.clf()
f, axarr = plt.subplots(4, 4, gridspec_kw = {'wspace':0, 'hspace':0})
for i, ax in enumerate(f.axes):
ax.grid('on', linestyle='--')
ax.set_xticklabels([])
ax.set_yticklabels([])
plt.show()
plt.close()
Resulting in:
With recent matplotlib versions you might want to try Constrained Layout. This does (or at least did) not work with plt.subplot() however, so you need to use plt.subplots() instead:
fig, axs = plt.subplots(4, 4, constrained_layout=True)
Have you tried plt.tight_layout()?
with plt.tight_layout()
without it:
Or: something like this (use add_axes)
left=[0.1,0.3,0.5,0.7]
width=[0.2,0.2, 0.2, 0.2]
rectLS=[]
for x in left:
for y in left:
rectLS.append([x, y, 0.2, 0.2])
axLS=[]
fig=plt.figure()
axLS.append(fig.add_axes(rectLS[0]))
for i in [1,2,3]:
axLS.append(fig.add_axes(rectLS[i],sharey=axLS[-1]))
axLS.append(fig.add_axes(rectLS[4]))
for i in [1,2,3]:
axLS.append(fig.add_axes(rectLS[i+4],sharex=axLS[i],sharey=axLS[-1]))
axLS.append(fig.add_axes(rectLS[8]))
for i in [5,6,7]:
axLS.append(fig.add_axes(rectLS[i+4],sharex=axLS[i],sharey=axLS[-1]))
axLS.append(fig.add_axes(rectLS[12]))
for i in [9,10,11]:
axLS.append(fig.add_axes(rectLS[i+4],sharex=axLS[i],sharey=axLS[-1]))
If you don't need to share axes, then simply axLS=map(fig.add_axes, rectLS)
Another method is to use the pad keyword from plt.subplots_adjust(), which also accepts negative values:
import matplotlib.pyplot as plt
ax = [plt.subplot(2,2,i+1) for i in range(4)]
for a in ax:
a.set_xticklabels([])
a.set_yticklabels([])
plt.subplots_adjust(pad=-5.0)
Additionally, to remove the white at the outer fringe of all subplots (i.e. the canvas), always save with plt.savefig(fname, bbox_inches="tight").