When using axhline right after twinx(), the horizontal line drawn still follows the coordinates of the first y-axis.
Any tip on how to make it scale to the second y-axis ?
You could call the axhline method from the Axes objects, as in the example below, or set te current Axes with sca.
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 10, 0.1)
y1 = np.sin(x)
y2 = 2.0 * np.cos(x)
fig = plt.figure()
ax1 = plt.subplot(111)
ax2 = ax1.twinx()
ax1.axhline( 0.5, 0.1, 0.5, color='r', lw=3)
ax2.axhline(-0.5, 0.5, 0.9, color='b', lw=3)
ax1.plot(x, y1, 'r', lw=2)
ax2.plot(x, y2, 'b', lw=2)
plt.show()
In case you don't have access to the return value of twinx() (for example when it was called for you by Pandas) you can access the left and right axes using the Axes object's left_ax and right_ax attributes.
Only one of these will be present, as each links to the other axis.
If you have a handle to the left axis, its right_ax attribute will point to the linked right axis.
If you have a handle to the right axis, its left_ax attribute will point to the linked left axis.
For example:
df = pandas.DataFrame({'d1': numpy.random.rand(10),
'd2': numpy.random.rand(10) * 10})
ax = df.plot(secondary_y=['d2']) # returns the left axis
ax.axhline(y=0.5, alpha=0.5) # draw a line from it
ax.right_ax.axhline(y=10, color="red", alpha=0.5) # draw a line from the right axis
Related
I'm plotting 3 things at once: a multicolored line via a LineCollection (following this) and a scatter (for the markers to "cover" where the lines are joining) for an average value, and a fill_between for min/max. I get all the legend returns to plot a single legend handle. The graph looks like this:
As one can note, the circle marker is not aligned with the line. How can I adjust this?
The piece of the code that is plotting them and the legend looks like:
lc = LineCollection(segments, cmap='turbo',zorder=3)
p1 = ax.add_collection(lc)
p2 = ax.fill_between(x, errmin,errmax, color=colors[1],zorder=2)
ps = ax.scatter(x,y,marker='o',s=1,c=y,cmap='turbo',zorder=4)
ax.legend([(p2, p1, ps)], ["(min/avg/max)"],fontsize=tinyfont, facecolor='white', loc='lower right')
The legend has a parameter scatteryoffsets= which defaults to [0.375, 0.5, 0.3125]. As only one point is shown, setting it to [0.5] should show the dot in the center of the legend marker.
To change the color of the line in the legend, one could create a copy of the existing line, change its color and create the legend with that copy.
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np
from copy import copy
x = np.arange(150)
y = np.random.randn(150).cumsum()
y -= y.min()
y /= y.max()
errmin = 0
errmax = 1
segments = np.array([x[:-1], y[:-1], x[1:], y[1:]]).T.reshape(-1, 2, 2)
fig, ax = plt.subplots(figsize=(12, 3))
lc = LineCollection(segments, cmap='turbo', zorder=3)
lc.set_array(y[:-1])
p1 = ax.add_collection(lc)
p2 = ax.fill_between(x, errmin, errmax, color='lightblue', zorder=2, alpha=0.4)
ps = ax.scatter(x, y, marker='o', s=5, color='black', zorder=4)
p1copy = copy(p1)
p1copy.set_color('crimson')
leg = ax.legend([(p2, p1copy, ps)], ["(min/avg/max)"], fontsize=10, facecolor='white', loc='lower right',
scatteryoffsets=[0.5])
ax.margins(x=0.02)
plt.show()
I was trying to make a graph with two secondary vertical axis (y-axis), with python matplotlib.
I was using twinx() method, where one of the two new axis is with the default behavior (labels on the right)
and the other with labels on the left, like the example of tan(x) on the figure bellow (created in an specific software).
Is there an easy way to do that? I'm not restricted to use the twinx() method, if there is another way
Here is a way to add two secondary y-axis, one towards the inside:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(.5, 10, 1000)
y1 = np.cos(x)
y2 = np.sin(2 * x)
y3 = np.clip(np.tan(x * .6), -75, 75)
fig, ax1 = plt.subplots()
color = 'dodgerblue'
ax1.set_ylabel('$cos(x)$', color=color)
ax1.plot(x, y1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx()
color = 'limegreen'
ax2.set_ylabel('$sin(2 x)$', color=color)
ax2.plot(x, y2, color=color)
ax2.tick_params(axis="y", labelcolor=color)
ax3 = ax1.twinx()
color = 'crimson'
ax3.set_ylabel('$tan(.6 x)$', color=color, labelpad=-40)
ax3.plot(x, y3, color=color)
ax3.tick_params(axis="y", labelcolor=color, direction="in", pad=-5)
plt.setp(ax3.get_yticklabels(), ha="right")
ax1.set_xlim(0, 12)
fig.tight_layout()
plt.show()
Usually two y-axes are kept apart with different colors, as shown in the example below.
For publications it's often necessary to keep it distinguishable, even when it's printed in black and white.
This is usually done by plotting circles around a line, which have an arrow in the direction of the corresponding axis attached.
How can this be achieved with matplotlib? Or is there a better way to accomplish black and white readability without those circles?
Code from matplotlib.org:
import numpy as np
import matplotlib.pyplot as plt
# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('time (s)')
ax1.set_ylabel('exp', color=color)
ax1.plot(t, data1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('sin', color=color) # we already handled the x-label with ax1
ax2.plot(t, data2, color=color)
ax2.tick_params(axis='y', labelcolor=color)
fig.tight_layout() # otherwise the right y-label is slightly clipped
plt.show()
This approach is based on this answer. It uses arc, which can be configured as follows:
import matplotlib.pyplot as plt
from matplotlib.patches import Arc
# Generate example graph
fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(1, 1, 1)
ax.plot([1,2,3,4,5,6], [2,4,6,8,10,12])
# Configure arc
center_x = 2 # x coordinate
center_y = 3.8 # y coordinate
radius_1 = 0.25 # radius 1
radius_2 = 1 # radius 2 >> for cicle: radius_2 = 2 x radius_1
angle = 180 # orientation
theta_1 = 70 # arc starts at this angle
theta_2 = 290 # arc finishes at this angle
arc = Arc([center_x, center_y],
radius_1,
radius_2,
angle = angle,
theta1 = theta_1,
theta2=theta_2,
capstyle = 'round',
linestyle='-',
lw=1,
color = 'black')
# Add arc
ax.add_patch(arc)
# Add arrow
x1 = 1.9 # x coordinate
y1 = 4 # y coordinate
length_x = -0.5 # length on the x axis (negative so the arrow points to the left)
length_y = 0 # length on the y axis
ax.arrow(x1,
y1,
length_x,
length_y,
head_width=0.1,
head_length=0.05,
fc='k',
ec='k',
linewidth = 0.6)
The result is shown below:
You can use matplotlib's axes annotate to draw arrows to the y-axes. You will need to find the points in the plot where the arrows should start. However, this does not plot circles around lines. If you really want to plot a circle, you could use plt.scatter or plt.Circle to plot an appropriate circle covering the relevant area.
import numpy as np
import matplotlib.pyplot as plt
# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('time (s)')
ax1.set_ylabel('exp', color=color)
ax1.plot(t, data1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax1.annotate('', xy=(7, 1096), xytext=(-0.5, 1096), # start the arrow from x=7 and draw towards primary y-axis
arrowprops=dict(arrowstyle="<-", color=color))
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('sin', color=color) # we already handled the x-label with ax1
ax2.plot(t, data2, color=color)
ax2.tick_params(axis='y', labelcolor=color)
# plt.arrow()
ax2.annotate('', xy=(6,0), xytext=(10.4, 0), # start the arrow from x=6 and draw towards secondary y-axis
arrowprops=dict(arrowstyle="<-", color=color))
fig.tight_layout() # otherwise the right y-label is slightly clipped
plt.show()
Following is the sample output figure.
EDIT: Following is the snippet with the circles you've requested. I have used plt.scatter.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
data1 = np.exp(t)
data2 = np.sin(2 * np.pi * t)
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('time (s)')
ax1.set_ylabel('exp', color=color)
ax1.plot(t, data1, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax1.annotate('', xy=(7, 1096), xytext=(-0.5, 1096), # start the arrow from x=7 and draw towards primary y-axis
arrowprops=dict(arrowstyle="<-", color=color))
# circle1 = Circle((5, 3000), color='r')
# ax1.add_artist(circle1)
plt.scatter(7, 1096, s=100, facecolors='none', edgecolors='r')
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('sin', color=color) # we already handled the x-label with ax1
ax2.plot(t, data2, color=color)
ax2.tick_params(axis='y', labelcolor=color)
# plt.arrow()
ax2.annotate('', xy=(6.7,0), xytext=(10.5, 0), # start the arrow from x=6.7 and draw towards secondary y-axis
arrowprops=dict(arrowstyle="<-", color=color))
plt.scatter(6,0, s=2000, facecolors='none', edgecolors=color)
fig.tight_layout() # otherwise the right y-label is slightly clipped
plt.savefig('fig')
plt.show()
Here is the sample output.
In pyplot, you can change the order of different graphs using the zorder option or by changing the order of the plot() commands. However, when you add an alternative axis via ax2 = twinx(), the new axis will always overlay the old axis (as described in the documentation).
Is it possible to change the order of the axis to move the alternative (twinned) y-axis to background?
In the example below, I would like to display the blue line on top of the histogram:
import numpy as np
import matplotlib.pyplot as plt
import random
# Data
x = np.arange(-3.0, 3.01, 0.1)
y = np.power(x,2)
y2 = 1/np.sqrt(2*np.pi) * np.exp(-y/2)
data = [random.gauss(0.0, 1.0) for i in range(1000)]
# Plot figure
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()
ax2.hist(data, bins=40, normed=True, color='g',zorder=0)
ax2.plot(x, y2, color='r', linewidth=2, zorder=2)
ax1.plot(x, y, color='b', linewidth=2, zorder=5)
ax1.set_ylabel("Parabola")
ax2.set_ylabel("Normal distribution")
ax1.yaxis.label.set_color('b')
ax2.yaxis.label.set_color('r')
plt.show()
Edit: For some reason, I am unable to upload the image generated by this code. I will try again later.
You can set the zorder of an axes, ax.set_zorder(). One would then need to remove the background of that axes, such that the axes below is still visible.
ax2 = ax1.twinx()
ax1.set_zorder(10)
ax1.patch.set_visible(False)
I'm facing a problem in showing the legend in the correct format using matplotlib.
EDIT: I have 4 subplots in a figure in 2 by 2 format and I want legend only on the first subplot which has two lines plotted on it. The legend that I got using the code attached below contained endless entries and extended vertically throughout the figure. When I use the same code using linspace to generate fake data the legend works absolutely fine.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import os
#------------------set default directory, import data and create column output vectors---------------------------#
path="C:/Users/Pacman/Data files"
os.chdir(path)
data =np.genfromtxt('vrp.txt')
x=np.array([data[:,][:,0]])
y1=np.array([data[:,][:,6]])
y2=np.array([data[:,][:,7]])
y3=np.array([data[:,][:,9]])
y4=np.array([data[:,][:,11]])
y5=np.array([data[:,][:,10]])
nrows=2
ncols=2
tick_l=6 #length of ticks
fs_axis=16 #font size of axis labels
plt.rcParams['axes.linewidth'] = 2 #Sets global line width of all the axis
plt.rcParams['xtick.labelsize']=14 #Sets global font size for x-axis labels
plt.rcParams['ytick.labelsize']=14 #Sets global font size for y-axis labels
plt.subplot(nrows, ncols, 1)
ax=plt.subplot(nrows, ncols, 1)
l1=plt.plot(x, y2, 'yo',label='Flow rate-fan')
l2=plt.plot(x,y3,'ro',label='Flow rate-discharge')
plt.title('(a)')
plt.ylabel('Flow rate ($m^3 s^{-1}$)',fontsize=fs_axis)
plt.xlabel('Rupture Position (ft)',fontsize=fs_axis)
# This part is not working
plt.legend(loc='upper right', fontsize='x-large')
#Same code for rest of the subplots
I tried to implement a fix suggested in the following link, however, could not make it work:
how do I make a single legend for many subplots with matplotlib?
Any help in this regard will be highly appreciated.
If I understand correctly, you need to tell plt.legend what to put as legends... at this point it is being loaded empty. What you get must be from another source. I have quickly the following, and of course when I run fig.legend as you do I get nothing.
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.4, 0.7])
ax2 = fig.add_axes([0.55, 0.1, 0.4, 0.7])
x = np.arange(0.0, 2.0, 0.02)
y1 = np.sin(2*np.pi*x)
y2 = np.exp(-x)
l1, l2 = ax1.plot(x, y1, 'rs-', x, y2, 'go')
y3 = np.sin(4*np.pi*x)
y4 = np.exp(-2*x)
l3, l4 = ax2.plot(x, y3, 'yd-', x, y4, 'k^')
fig.legend(loc='upper right', fontsize='x-large')
#fig.legend((l1, l2), ('Line 1', 'Line 2'), 'upper left')
#fig.legend((l3, l4), ('Line 3', 'Line 4'), 'upper right')
plt.show()
I'd suggest doing one by one, and then applying for all.
It is useful to work with the axes directly (ax in your case) when when working with subplots. So if you set up two plots in a figure and only wish to have a legend in your second plot:
t = np.linspace(0, 10, 100)
plt.figure()
ax1 = plt.subplot(2, 1, 1)
ax1.plot(t, t * t)
ax2 = plt.subplot(2, 1, 2)
ax2.plot(t, t * t * t)
ax2.legend('Cubic Function')
Note that when creating the legend, I am doing so on ax2 as opposed to plt. If you wish to create a second legend for the first subplot, you can do so in the same way but on ax1.