What is the best way to specify my colorbar legend location while ensuring the legend title is within the figure? Sometimes the location will be upper right, as shown here; but in other plots it will be variable, upper/lower left/right.
It is okay if the solution doesn't use inset_axes().
Alternative Solution:
It would also be okay if the colorbar legend is to the right of the subplot, if the "My Legend" title is vertical and on the left, and the tick labels are on the right and horizontal (I don't know how to do that).
Using Python 3.8.
## Second Plot
vals2 = ax2.scatter(df.x, df.y, edgecolors = 'none', c = df.z,
norm = mcolors.LogNorm(), cmap=rainbow)
ax2.set_aspect('equal')
ax2.set_title('Subplot Title', style='italic');
ax2.set_xlabel('x');
ax2.set_ylabel('y');
cbaxes = inset_axes(ax2, width="30%", height="10%", location = 'upper right')
clb = plt.colorbar(vals2, cax=cbaxes, format = '%1.2f', orientation='horizontal');
clb.ax.set_title('My Legend')
I would still prefer to have the colorbar (with tick labels and title) inside the subplot; but I did find a way to do the Alternative Solution:
vals2 = ax2.scatter(df.x, df.y, edgecolors = 'none', c = df.z,
norm = mcolors.LogNorm(), cmap=rainbow)
ax2.set_aspect('equal')
ax2.set_title('Subplot Title', style='italic');
ax2.set_xlabel('x');
ax2.set_ylabel('y');
clb = fig.colorbar(slips2, ax=ax2, format = '%1.2g', location='right', aspect=25)
clb.ax.set_ylabel('My Legend')
clb.ax.yaxis.set_label_position('left')
The color bar is taller than the subplot because ax2 is constrained to be equal xy aspect ratio based on the limits in another subplot (ax1, not shown).
Related
When the marker in a legend is a dot, dot and text are not aligned vertically. To solve this I tried following:
l = ax.legend()
for text in l.texts:
text.set_va('center') # Is there some setting for this in matplotlibrc, too??
plt.show()
The vertical alignment of text in a legend seems to be baseline. But no matter whether I choose center, bottom or baseline, etc., things are off:
Zooming in, this is what Matplotlib gives us out of the box:
What I want is also what other software like Inkscape gives me, when aligning two objects vertically:
Can Matplotlib do this for me/us?
This appears to work:
Set it to display only a single scatterpoint per legend entry by setting scatterpoints=1 in the call to legend()
Set the vertical offset of this point to 0 by setting scatteryoffsets=[0] in the call to legend()
After creating the legend, iterate through its text labels and set their vertical alignment to center_baseline, using for t in l.get_texts(): t.set_va('center_baseline')
figure(figsize=(2,2))
scatter([0],[0],marker='s',s=20,label='Thing 1')
scatter([1],[0],marker='s',s=20,label='t')
scatter([2],[0],marker='s',s=20,label='T¹₁')
l = legend(scatterpoints=1,scatteryoffsets=[0],handletextpad=-0.5)
for t in l.get_texts(): t.set_va('center_baseline')
Here is what I do:
import numpy as np
import matplotlib
matplotlib.use('Agg')
matplotlib.rcParams['text.latex.preamble'] = r'\usepackage{amsmath}'
matplotlib.rc('text', usetex = True)
from matplotlib import pyplot as py
## setup figure
figure = py.figure(figsize = (7.5, 5.0))
axs = [py.subplot(1, 1, 1)]
## make plot
xs = np.linspace(0.0, np.pi, 100)
ys = np.sin(xs)
axs[0].plot(xs, ys, color = 'dodgerblue', label = r'$n = 1$')
ys = np.sin(2.0 * xs)
axs[0].plot(xs, ys, color = 'seagreen', label = r'$n = 2$')
axs[0].axhline(0.0, color = 'gray', linestyle = 'dashed')
## vertical alignment
legends = axs[0].legend(frameon = False, fontsize = 25, loc = 'lower left')
shift = np.average([_.get_window_extent(renderer = figure.canvas.get_renderer()).height for _ in legends.get_texts()])
shift /= 3.6
for _ in legends.get_texts():
_.set_va('center') ## va is alias for verticalalignment
_.set_position((0, shift))
## save figure
name = 'test.pdf'
py.tight_layout()
py.savefig(name)
py.close()
It is, however, complicated and requires manual adjustments,
I am still looking for better solutions.
I was making a plot of f(x,y,z) and wanted this to be displayed in a 2D-plane. To avoid cluttering my legend i decided to have different linestyles for y, different colors for z and place the two in two separate legends. I couldn't find out how to do this even after a lot of digging, so I'm posting the solution i came up with here :) If anyone has more elegant solutions I'm all ears :)
Basically the solution was to make three plots, set two of them to have size (0,0) and place those two where i wanted the legends. It feels like an ugly way to do it, but it gave a nice plot and i didn't find any other way :) The resulting plot looks like this:
def plot_alt(style = 'log'):
cmap = cm.get_cmap('inferno')
color_scale = 1.2 #Variable to get colors from a certain part of the colormap
#Making grids for delta T and average concentration
D_T_axis = -np.logspace(np.log10(400), np.log10(1), 7)
C_bar_list = np.linspace(5,10,4)
ST_list = np.logspace(-3,-1,100)
# f(x,y,z)
DC_func = lambda C_bar, ST, DT: 2*C_bar * (1 - np.exp(ST*DT))/(1 + np.exp(ST*DT))
#Some different linestyles
styles = ['-', '--', '-.', ':']
fig, ax = plt.subplots(1,3, figsize = (10,5))
plt.sca(ax[0])
for i, C_bar in enumerate(C_bar_list): #See plot_c_rel_av_DT() for 'enumerate'
for j, DT in enumerate(D_T_axis):
plt.plot(ST_list, DC_func(C_bar, ST_list, DT), color = cmap(np.log10(-DT)/(color_scale*np.log10(-D_T_axis[0]))),
linestyle = styles[i])
# Generating separate legends by plotting lines in the two other subplots
# Basically: to get two separate legends i make two plots, place them where i want the legends
# and set their size to zero, then display their legends.
plt.sca(ax[1]) #Set current axes to ax[1]
for i, C_bar in enumerate(C_bar_list):
# Plotting the different linestyles
plt.plot(C_bar_list, linestyle = styles[i], color = 'black', label = str(round(C_bar, 2)))
plt.sca(ax[2])
for DT in D_T_axis:
#plotting the different colors
plt.plot(D_T_axis, color = cmap(np.log10(-DT)/(color_scale*np.log10(-D_T_axis[0]))), label = str(int(-DT)))
#Placing legend
#This is where i move and scale the three plots to make one plot and two legends
box0 = ax[0].get_position() #box0 is an object that contains the position and dimentions of the ax[0] subplot
box2 = ax[2].get_position()
ax[0].set_position([box0.x0, box0.y0, box2.x0 + 0.4*box2.width, box0.height])
box0 = ax[0].get_position()
ax[1].set_position([box0.x0 + box0.width, box0.y0 + box0.height + 0.015, 0,0])
ax[1].set_axis_off()
ax[2].set_position([box0.x0 + box0.width ,box0.y0 + box0.height - 0.25, 0,0])
ax[2].set_axis_off()
#Displaying plot
plt.sca(ax[0])
plt.xscale('log')
plt.xlim(0.001, 0.1)
plt.ylim(0, 5)
plt.xlabel(r'$S_T$')
plt.ylabel(r'$\Delta C$')
ax[1].legend(title = r'$\langle c \rangle$ [mol/L]',
bbox_to_anchor = (1,1), loc = 'upper left')
ax[2].legend(title = r'$-\Delta T$ [K]', bbox_to_anchor = (1,1), loc = 'upper left')
#Suptitle is the title of the figure. You can also have titles for the individual subplots
plt.suptitle('Steady state concentration gradient as a function of Soret-coefficient\n'
'for different temperature gradients and total concentrations')
I am trying to make some figures for a scientific article, so I want my figures to have a specific size. I also see that Matplotlib by default adds a lot of padding on the border of the figures, which I don't need (since the figures will be on a white background anyway).
To set a specific figure size I simply use plt.figure(figsize = [w, h]), and I add the argument tight_layout = {'pad': 0} to remove the padding. This works perfectly, and even works if I add a title, y/x-labels etc. Example:
fig = plt.figure(
figsize = [3,2],
tight_layout = {'pad': 0}
)
ax = fig.add_subplot(111)
plt.title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
plt.savefig('figure01.pdf')
This creates a pdf file with exact size 3x2 (inches).
The issue I have is that when I for example add a text box outside the axis (typically a legend box), Matplotlib does not make room for the text box like it does when adding titles/axis labels. Typically the text box is cut off, or does not show in the saved figure at all. Example:
plt.close('all')
fig = plt.figure(
figsize = [3,2],
tight_layout = {'pad': 0}
)
ax = fig.add_subplot(111)
plt.title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
t = ax.text(0.7, 1.1, 'my text here', bbox = dict(boxstyle = 'round'))
plt.savefig('figure02.pdf')
A solution I found elsewhere on SO was to add the argument bbox_inches = 'tight' to the savefig command. The text box is now included like I wanted, but the pdf is now the wrong size. It seems like Matplotlib just makes the figure bigger, instead of reducing the size of the axes like it does when adding titles and x/y-labels.
Example:
plt.close('all')
fig = plt.figure(
figsize = [3,2],
tight_layout = {'pad': 0}
)
ax = fig.add_subplot(111)
plt.title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
t = ax.text(0.7, 1.1, 'my text here', bbox = dict(boxstyle = 'round'))
plt.savefig('figure03.pdf', bbox_inches = 'tight')
(This figure is 3.307x2.248)
Is there any solution to this that covers most cases with a legend just outside the axes?
So the requirements are:
Having a fixed, predefined figure size
Adding a text label or legend outside the axes
Axes and text cannot overlap
The axes, together with the title and axis labels, sits tightly agains the figure border.
So tight_layout with pad = 0, solves 1. and 4. but contradicts 2.
One could think on setting pad to a larger value. This would solve 2. However, since it's is symmetric in all directions, it would contradict 4.
Using bbox_inches = 'tight' changes the figure size. Contradicts 1.
So I think there is no generic solution to this problem.
Something I can come up with is the following: It sets the text in figure coordinates and then resizes the axes either in horizontal or in vertical direction such that there is no overlap between the axes and the text.
import matplotlib.pyplot as plt
import matplotlib.transforms
fig = plt.figure(figsize = [3,2])
ax = fig.add_subplot(111)
plt.title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
def text_legend(ax, x0, y0, text, direction = "v", padpoints = 3, margin=1.,**kwargs):
ha = kwargs.pop("ha", "right")
va = kwargs.pop("va", "top")
t = ax.figure.text(x0, y0, text, ha=ha, va=va, **kwargs)
otrans = ax.figure.transFigure
plt.tight_layout(pad=0)
ax.figure.canvas.draw()
plt.tight_layout(pad=0)
offs = t._bbox_patch.get_boxstyle().pad * t.get_size() + margin # adding 1pt
trans = otrans + \
matplotlib.transforms.ScaledTranslation(-offs/72.,-offs/72.,fig.dpi_scale_trans)
t.set_transform(trans)
ax.figure.canvas.draw()
ppar = [0,-padpoints/72.] if direction == "v" else [-padpoints/72.,0]
trans2 = matplotlib.transforms.ScaledTranslation(ppar[0],ppar[1],fig.dpi_scale_trans) + \
ax.figure.transFigure.inverted()
tbox = trans2.transform(t._bbox_patch.get_window_extent())
bbox = ax.get_position()
if direction=="v":
ax.set_position([bbox.x0, bbox.y0,bbox.width, tbox[0][1]-bbox.y0])
else:
ax.set_position([bbox.x0, bbox.y0,tbox[0][0]-bbox.x0, bbox.height])
# case 1: place text label at top right corner of figure (1,1). Adjust axes height.
#text_legend(ax, 1,1, 'my text here', bbox = dict(boxstyle = 'round'), )
# case 2: place text left of axes, (1, y), direction=="v"
text_legend(ax, 1., 0.8, 'my text here', margin=2., direction="h", bbox = dict(boxstyle = 'round') )
plt.savefig(__file__+'.pdf')
plt.show()
case 1 (left) and case 2 (right):
Doin the same with a legend is slightly easier, because we can directly use the bbox_to_anchor argument and don't need to control the fancy box around the legend.
import matplotlib.pyplot as plt
import matplotlib.transforms
fig = plt.figure(figsize = [3.5,2])
ax = fig.add_subplot(111)
ax.set_title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
ax.plot([1,2,3], marker="o", label="quantity 1")
ax.plot([2,1.7,1.2], marker="s", label="quantity 2")
def legend(ax, x0=1,y0=1, direction = "v", padpoints = 3,**kwargs):
otrans = ax.figure.transFigure
t = ax.legend(bbox_to_anchor=(x0,y0), loc=1, bbox_transform=otrans,**kwargs)
plt.tight_layout(pad=0)
ax.figure.canvas.draw()
plt.tight_layout(pad=0)
ppar = [0,-padpoints/72.] if direction == "v" else [-padpoints/72.,0]
trans2=matplotlib.transforms.ScaledTranslation(ppar[0],ppar[1],fig.dpi_scale_trans)+\
ax.figure.transFigure.inverted()
tbox = t.get_window_extent().transformed(trans2 )
bbox = ax.get_position()
if direction=="v":
ax.set_position([bbox.x0, bbox.y0,bbox.width, tbox.y0-bbox.y0])
else:
ax.set_position([bbox.x0, bbox.y0,tbox.x0-bbox.x0, bbox.height])
# case 1: place text label at top right corner of figure (1,1). Adjust axes height.
#legend(ax, borderaxespad=0)
# case 2: place text left of axes, (1, y), direction=="h"
legend(ax,y0=0.8, direction="h", borderaxespad=0.2)
plt.savefig(__file__+'.pdf')
plt.show()
Why 72? The 72 is the number of points per inch (ppi). This is a fixed typographic unit e.g. fontsizes are always given in points (like 12pt). Because matplotlib defines the padding of the text box in units relative to fontsize, which is points, we need to use 72 to transform back to inches (and then to display coordinates). The default dots per inch (dpi) is not touched here, but is accounted for in fig.dpi_scale_trans. If you want to change dpi you need to make sure the figure dpi is set when creating the figure as well as when saving it (use dpi=.. in the call to plt.figure() as well as plt.savefig()).
As of matplotlib==3.1.3, you can use constrained_layout=True to achieve the desired result. This is currently experimental, but see the docs for a very helpful guide (and the section specifically on legends). Note that the legend will steal space from the plot, but this is unavoidable. I've found that as long as the legend does not take up too much space relative to the size of the plot, then the figure gets saved without cropping anything.
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(3, 2), constrained_layout=True)
ax.set_title('title')
ax.set_ylabel('y label')
ax.set_xlabel('x label')
ax.plot([0,1], [0,1], label='my text here')
ax.legend(loc='center left', bbox_to_anchor=(1.1, 0.5))
fig.savefig('figure03.pdf')
My script for plotting creates two legends for each label. I do not know how to make legend() not duplicate. I checked on stackoverflow and found two methods. But I could not implement them here. Any ideas?
Matplotlib: Don't show errorbars in legend
Stop matplotlib repeating labels in legend
symbols = [u'\u2193']
#Plotting our vsini values
for i, symbol in enumerate(symbols):
for x0,y0 in zip(vsini_slit_cl, vsini_slit):
plt.text(x0,y0, symbol, fontname='STIXGeneral', size = 10, va='center', ha='center', clip_on=True,color = '#737373')
for i, symbol in enumerate(symbols):
for x0, y0 in zip(vsini_cl_sl, vsini_sl):
plt.text(x0, y0, symbol, fontname='STIXGeneral', size = 10, va='center', ha='center', clip_on=True)
# PLOTTING VSINI FROM LITERATURE
plt.plot((vmag_lit-jmag_lit), vsini_lit, 'o', color = '#a6a6a6', label='Literature')
# PLOTTING SLOW VSINI FROM LITERATURE
plt.plot(vsini_slit_cl, vsini_slit, 'o', color = '#a6a6a6')
# PLOTTING VSINI FROM OUR WORK
plt.plot(vsini_cl_sl, vsini_sl, 'o', label='This Work' )
plt.errorbar(vsini_color, vsini_chad, yerr=vsini_chad_sig, fmt='bo', capsize=3)
plt.legend()
plt.savefig('vsini_colors.jpg', dpi=200)
Just use
plt.legend(numpoints=1)
The default behavior is to use 2 points, which is what you need to make a legend entry for lines.
See: legend user guide and plt.legend doc and legend doc
I'm trying to use matplotlib to make a scatter plot with very small gray points. Because of the point density, the points need to be small. The problem is that the scatter() function's markers seem to have both a line and a fill. When the markers are small, only the line is visible, not the fill, and the line isn't the right colour (it's always black).
I can get exactly what I want using gnuplot: plot 'nodes' with points pt 0 lc rgb 'gray'
How can I make very small gray points using matplotlib scatterplot()?
scatter([1,2,3], [2,4,5], s=1, facecolor='0.5', lw = 0)
This sets the markersize to 1 (s=1), the facecolor to gray (facecolor='0.5'), and the linewidth to 0 (lw=0).
If the marker has no face (cannot be filled, e.g. '+','x'), then the edgecolor has to be set instead of c, and lw should not be 0:
scatter([1,2,3], [2,4,5], marker='+', edgecolor='r')
The following will no work
scatter([1,2,3], [2,4,5], s=1, marker='+', facecolor='0.5', lw = 0)
because the edge/line will not be displayed, so nothing will be displayed.
The absolute simplest answer to your question is: use the color parameter instead of the c parameter to set the color of the whole marker.
It's easy to see the difference when you compare the results:
from matplotlib import pyplot as plt
plt.scatter([1,2,3], [3,1,2], c='0.8') # marker not all gray
plt.scatter([1,2,3], [3,1,2], color='0.8') # marker all gray
Details:
For your simple use case where you just want to make your whole marker be the same shade of gray color, you really shouldn't have to worry about things like face color vs edge color, and whether your marker is defined as all edges or some edges and some fill. Instead, just use the color parameter and know that your whole marker will be set to the single color that you specify!
In response to zwol's question in comment - my reputation is not high enough to leave comments, so this will have to do: In the event that your colors come from a colormap (i.e., are from a "sequence of values to be mapped") you can use color = as demonstrated in the following:
from matplotlib import pyplot
x = [1,5,8,9,5]
y = [4,2,4,7,9]
numSides = [2,3,1,1,5]
cmap = pyplot.cm.get_cmap("copper_r")
min, max = min(numSides), max(numSides)
for i in range(len(x)):
if numSides[i] >= 2:
cax = pyplot.scatter(x[i], y[i], marker = '+', s = 100, c = numSides[i], cmap = cmap)
cax.set_clim(min, max)
elif numSides[i] == 1:
pyplot.scatter(x[i], y[i], marker = '.', s = 40, color = cmap(numSides[i]))
fig = pyplot.gcf()
fig.set_size_inches(8.4, 6)
fig.savefig('figure_test.png', dpi = 200)
pyplot.show()