Develop Reference

Matplotlib scatter plot of unfilled squares

I would like to make a scatter plot with unfilled squares. markerfacecolor is not an option recognized by scatter. I made a MarkerStyle but the fill style seems to be ignored by the scatter plot. Is there a way to make unfilled markers in the scatterplot?
import matplotlib.markers as markers
import matplotlib.pyplot as plt
import numpy as np
def main():
size = [595, 842] # in pixels
dpi = 72. # dots per inch
figsize = [i / dpi for i in size]
fig = plt.figure(figsize=figsize)
ax = fig.add_axes([0,0,1,1])
x_max = 52
y_max = 90
ax.set_xlim([0, x_max+1])
ax.set_ylim([0, y_max + 1])
x = np.arange(1, x_max+1)
y = [np.arange(1, y_max+1) for i in range(x_max)]
marker = markers.MarkerStyle(marker='s', fillstyle='none')
for temp in zip(*y):
plt.scatter(x, temp, color='green', marker=marker)
plt.show()
main()

It would appear that if you want to use plt.scatter() then you have to use facecolors = 'none' instead of setting fillstyle = 'none' in construction of the MarkerStyle, e.g.
marker = markers.MarkerStyle(marker='s')
for temp in zip(*y):
plt.scatter(x, temp, color='green', marker=marker, facecolors='none')
plt.show()
or, use plt.plot() with fillstyle = 'none' and linestyle = 'none' but since the marker keyword in plt.plot does not support MarkerStyle objects you have to specify the style inline, i.e.
for temp in zip(*y):
plt.plot(x, temp, color='green', marker='s', fillstyle='none')
plt.show()
either of which will give you something that looks like this

Refer to: How to do a scatter plot with empty circles in Python?
Try adding facecolors='none' to your plt.scatter
plt.scatter(x, temp, color='green', marker=marker, facecolors='none')

Matplotlib: how to set a tick label above a plot

This is the sine and cosine plot I draw using matplotlib. But the tick labels are below the plot and can hardly seen.
My python code is:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8,6), dpi=96)
plt.subplot(111)
X = np.linspace(-np.pi, np.pi, 256, endpoint=True)
C,S = np.cos(X), np.sin(X)
plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="consine")
plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine")
plt.xlim(X.min()*1.1, X.max()*1.1)
plt.ylim(C.min()*1.1, C.max()*1.1)
plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$+\frac{\pi}{2}$', r'$+\pi$'])
plt.yticks([-1, 1],
[r'$-1$', r'$+1$'])
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data',0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data',0))
plt.legend(loc='upper left', frameon=False)
for label in ax.get_xticklabels()+ax.get_yticklabels():
label.set_fontsize(16)
label.set_bbox(dict(facecolor='green', edgecolor='None', alpha=0.2))
plt.savefig("figures/exercise10.png", dpi=120)
plt.show()
So, how should I set a tick label above a plot?
Thank you!

Possibly you want to set the labels and the axes spines on top of the lines. This can easily be achieved with the "axes.axisbelow" rcParam.
plt.rcParams["axes.axisbelow"] = False

PyPlot move alternative y axis to background

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)

Change ticks of y-axis in python

I want to change y axis ticks in python. I am using the code
import pylab as plt
y1 = [0,1,2,...10]
y2 = [90,40,65,12,....]
labels = [0.30,0.29,0.28,....]
plt.plot(y1)
plt.plot(y2,'r')
plt.yticks(y1, labels)
plt.yticks(y2, labels)
plt.show()
But all the y axis label appear at one place on top of one another

Borrowing heavily from this example, the code below demonstrates one possible way to have two plots on one figure.
import pylab as plt
fig, ax1 = plt.subplots()
y1 = [0,1,2,3,4,5,6,7,8,9,10]
labels = [0.30,0.29,0.28,0.27,0.26,0.25,0.24,0.23,0.22,0.21,0.20]
ax1.plot(labels, y1, 'b-')
ax1.set_xlabel('labels')
# Make the y-axis label, ticks and tick labels match the line color.
ax1.set_ylabel('y1', color='b', rotation="horizontal")
ax1.tick_params('y', colors='b')
ax2 = ax1.twinx()
y2 = [90,40,65,12,23,43,54,13,42,53,63]
ax2.plot(labels, y2, 'r-')
ax2.set_ylabel('y2', color='r', rotation="horizontal")
ax2.tick_params('y', colors='r')
fig.tight_layout()
plt.show()

Hide radial tick labels matplotlib

I'm trying to plot a polar plot with this code:
import numpy as np
import matplotlib.pylab as plt
def power(angle, l, lam):
return 1/(lam) * ((np.cos(np.pi*l*np.cos(angle)/lam) - np.cos(np.pi*l/lam))/np.sin(angle))**2
fig = plt.figure(1)
ax = fig.add_subplot(111, projection='polar')
theta = np.linspace(0.001, 2*np.pi, 100)
P1 = power(theta, 1, 5)
ax.plot(theta, P1, color='r', linewidth=3)
plt.savefig('1.png')
and I get this plot:
I would like to change 2 things. The first and more important one is to hide the radial tick labels (I just want to show the general form of the plot).
If possible, how can I choose the vertical axis to correspond to 0°?
Thanks for your help.

You can use set_yticklabels() to remove the radial ticks and set_theta_zero_location() to change the zero location:
fig = plt.figure(1)
ax = fig.add_subplot(111, projection='polar')
ax.plot(theta, P1, color='r', linewidth=3)
ax.set_yticklabels([])
ax.set_theta_zero_location('N')
plt.show()
You might also want to change the direction of the azimuthal axis:
ax.set_theta_direction(-1)

You can set the theta zero position with ax.set_theta_zero_location('N').
To modify the r tick labels, you could do something like
for r_label in ax.get_yticklabels():
r_label.set_text('')
If you want to remove them entirely, do ax.set_yticklabels([]).
More methods can be found in the PolarAxes documentation.