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How to assign a plot to a variable and use the variable in a multiplot in Python

I would like to have a function which create a plot. Once I have the plot, I would like to use that in a multiplot.
For example, I could create the following function:
def fig_1(x):
# create a new figure
fig = plt.figure()
plt.plot([1*x, 2*x, 3*x, 4*x])
return fig
after that I would like something like:
subplot(3,2,1) = fig_1(1)
subplot(3,2,2) = fig_1(2)
subplot(3,2,3) = fig_1(3)
subplot(3,2,4) = fig_1(4)
subplot(3,2,5) = fig_1(5)
subplot(3,2,6) = fig_1(6)
In order to plot the final plot:
from pylab import *
pdf = matplotlib.backends.backend_pdf.PdfPages("Cal8010.pdf")
for fig in xrange(1,figure().number):
In this way, it does not work. Could I do what I have in mind?
Thanks for any kind of help

First: I create subplots and in each one a plot:
import matplotlib.pyplot as plt
import numpy as np
def fig_1(ax, x, y):
ax.plot(x, y)
fig, ax = plt.subplots(3, 2)
for i in range(3):
for j in range(2):
x = np.random.random(10)
y = np.random.random(10)
fig_1(ax[i, j], x, y)
ax[i, j].set_title(f"Subplot #{2*i + j + 1}")
plt.show()
Now, you can also plot an empty array and further update datas to this plot:
import matplotlib.pyplot as plt
import numpy as np
def fig_1(ax):
line, = ax.plot([], [])
return line
fig, ax = plt.subplots(3, 2)
lines = []
for i in range(3):
for j in range(2):
x = np.random.random(10)
y = np.random.random(10)
lines.append((fig_1(ax[i, j]), x, y))
ax[i, j].set_title(f"Subplot #{2*i + j + 1}")
for p in lines:
l, x, y = p
l.set_xdata(x)
l.set_ydata(y)
fig.canvas.draw()
fig.canvas.flush_events()
plt.show()
but this could be tricky because both axis on each plot are not adapted to the datas so plots can be out of bounds (so you possibly need to fix the x and y limits to min and max of datas)

Dear Reviewer,
here the solution that I have work out thanks to another post that I hope to find again in order to give the right credit to it.
fig, axs = plt.subplots(2,2)
def plot_ff(ax=None,data):
ax.plot(data)
return
plot_ff(axs[0, 0],data_1)
plot_ff(axs[0, 1],data_2)
plot_ff(axs[1, 0],data_3)
plot_ff(axs[0, 1],data_3)
In this way, it works and it is easily manage with different type of multiplot
What do you think about this solution?
Should I erase this questions?
Diego

How to make my surface plot appear using Axes3D?

I'm trying to create a surface plot using Python Matplotlib. I've read the documentation in an attempt to figure out where my code was wrong or if I've left anything out, but was having trouble.
The code that I've written is
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
def computeCost(X, y, theta):
m = len(y)
predictions = np.dot(X, theta)
squareErros = (predictions - y) ** 2
J = (1 / (2 * m)) * sum(squareErrors)
return J
data = np.loadtxt("./data1.txt", delimiter=',')
X = data[:, 0].reshape(-1, 1)
y = data[:, 1].reshape(-1, 1)
m = len(y)
X = np.concatenate((np.ones((m, 1)), X), axis=1)
theta0_vals = np.linspace(-10, 10, 100) # size (100,)
theta1_vals = np.linspace(-1, 4, 100) # size (100,)
J_vals = np.zeros((len(theta0_vals), len(theta1_vals)))
for i in range(len(x_values)):
for j in range(len(y_values)):
t = np.array([theta0_vals[i], theta1_vals[j]]).reshape(-1, 1)
J_vals[i][j] = computeCost(X, y, t) # size (100, 100)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
surf = ax.plot_surface(theta0_vals, theta1_vals, J_vals)
plt.show()
When I invoke plt.show() I get no output. The surface plot that I'm expecting to see is similar to this:
Would anybody be kind enough to let me know where my usage of the surface plot library went wrong? Thank you.
EDIT
I've tried to run the demo code provided here and it works fine. Here's the code for that:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np
fig = plt.figure()
ax = fig.gca(projection='3d')
# Make data.
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
linewidth=0, antialiased=False)
# Customize the z axis.
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
# Add a color bar which maps values to colors.
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()

I think I've figured out the issue by changing a couple of the last lines of code from
ax = fig.add_subplot(111, projection='3d')
surf = ax.plot_surface(theta0_vals, theta1_vals, J_vals)
to
ax = plt.axes(projection='3d')
surf = ax.plot_surface(theta0_vals, theta1_vals, J_vals, rstride=1, cstride=1, cmap='viridis', edgecolor='none')
Making this change gives me a surface plot such that:
The link that gave me reference to this was this.

Update interactive plot in Jupyter Notebook [duplicate]

I am trying to animate a pcolormesh in matplotlib. I have seen many of the examples using the package animation, most of them using a 1D plot routine, and some of them with imshow().
First, I wan to use the FuncAnimation routine. My problem is, first, that I do not know if I can initialize the plot
fig,ax = plt.subplots()
quad = ax.pcolormesh(X,Y,Z)
I have tried a few simple lines:
fig,ax = plt.subplots()
quad = ax.pcolormesh([])
def init():
quad.set_array([])
return quad,
def animate(ktime):
quad.set_array(X,Y,np.sin(Z)+ktime)
return quad,
anim = animation.FuncAnimation(fig,animate,init_func=init,frames=Ntime,interval=200,blit=True)
plt.show()
By the way, How do I set labels into and animated plot? Can I animate the title, if it is showing a number that changes in time?
Thanks

The problem was that I was wrongly using set_array() routine. It is very important to note that you must pass a 1D array to this routine. To do so, regarding that color, pcolormesh and so on usually plots multidimensional arrays, you should use .ravel() .
One more important thing: In order to animate different plots at the same time, the blitz option at animate.FuncAnimation must be False (See section "Animating selected plot elements" of this link).
Here I post the code that simple program with various subplots:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.gridspec as gridspec
import matplotlib.animation as animation
y, x = np.meshgrid(np.linspace(-10, 10,100), np.linspace(-10, 10,100))
z = np.sin(x)*np.sin(x)+np.sin(y)*np.sin(y)
v = np.linspace(-10, 10,100)
t = np.sin(v)*np.sin(v)
tt = np.cos(v)*np.cos(v)
###########
fig = plt.figure(figsize=(16, 8),facecolor='white')
gs = gridspec.GridSpec(5, 2)
ax1 = plt.subplot(gs[0,0])
line, = ax1.plot([],[],'b-.',linewidth=2)
ax1.set_xlim(-10,10)
ax1.set_ylim(0,1)
ax1.set_xlabel('time')
ax1.set_ylabel('amplitude')
ax1.set_title('Oscillationsssss')
time_text = ax1.text(0.02, 0.95, '', transform=ax1.transAxes)
#############################
ax2 = plt.subplot(gs[1:3,0])
quad1 = ax2.pcolormesh(x,y,z,shading='gouraud')
ax2.set_xlabel('time')
ax2.set_ylabel('amplitude')
cb2 = fig.colorbar(quad1,ax=ax2)
#########################
ax3 = plt.subplot(gs[3:,0])
quad2 = ax3.pcolormesh(x, y, z,shading='gouraud')
ax3.set_xlabel('time')
ax3.set_ylabel('amplitude')
cb3 = fig.colorbar(quad2,ax=ax3)
############################
ax4 = plt.subplot(gs[:,1])
line2, = ax4.plot(v,tt,'b',linewidth=2)
ax4.set_xlim(-10,10)
ax4.set_ylim(0,1)
def init():
line.set_data([],[])
line2.set_data([],[])
quad1.set_array([])
return line,line2,quad1
def animate(iter):
t = np.sin(2*v-iter/(2*np.pi))*np.sin(2*v-iter/(2*np.pi))
tt = np.cos(2*v-iter/(2*np.pi))*np.cos(2*v-iter/(2*np.pi))
z = np.sin(x-iter/(2*np.pi))*np.sin(x-iter/(2*np.pi))+np.sin(y)*np.sin(y)
line.set_data(v,t)
quad1.set_array(z.ravel())
line2.set_data(v,tt)
return line,line2,quad1
gs.tight_layout(fig)
anim = animation.FuncAnimation(fig,animate,frames=100,interval=50,blit=False,repeat=False)
plt.show()
print 'Finished!!'

There is an ugly detail you need to take care when using QuadMesh.set_array(). If you intantiate your QuadMesh with X, Y and C you can update the values C by using set_array(). But set_array does not support the same input as the constructor. Reading the source reveals that you need to pass a 1d-array and what is even more puzzling is that depending on the shading setting you might need to cut of your array C.
Edit: There is even a very old bug report about the confusing array size for shading='flat'.
That means:
Using QuadMesh.set_array() with shading = 'flat'
'flat' is default value for shading.
# preperation
import numpy as np
import matplotlib.pyplot as plt
plt.ion()
y = np.linspace(-10, 10, num=1000)
x = np.linspace(-10, 10, num=1000)
X, Y = np.meshgrid(x, y)
C = np.ones((1000, 1000)) * float('nan')
# intantiate empty plot (values = nan)
pcmesh = plt.pcolormesh(X, Y, C, vmin=-100, vmax=100, shading='flat')
# generate some new data
C = X * Y
# necessary for shading='flat'
C = C[:-1, :-1]
# ravel() converts C to a 1d-array
pcmesh.set_array(C.ravel())
# redraw to update plot with new data
plt.draw()
Looks like:
Note that if you omit C = C[:-1, :-1] your will get this broken graphic:
Using QuadMesh.set_array() with shading = 'gouraud'
# preperation (same as for 'flat')
import numpy as np
import matplotlib.pyplot as plt
plt.ion()
y = np.linspace(-10, 10, num=1000)
x = np.linspace(-10, 10, num=1000)
X, Y = np.meshgrid(x, y)
C = np.ones((1000, 1000)) * float('nan')
# intantiate empty plot (values = nan)
pcmesh = plt.pcolormesh(X, Y, C, vmin=-100, vmax=100, shading='gouraud')
# generate some new data
C = X * Y
# here no cut of of last row/column!
# ravel() converts C to a 1d-array
pcmesh.set_array(C.ravel())
# redraw to update plot with new data
plt.draw()
If you cut off the last row/column with shade='gouraud' you will get:
ValueError: total size of new array must be unchanged

I am not sure why your quad = ax.pcolormesh(X,Y,Z) function is giving an error. Can you post the error?
Below is what I would do to create a simple animation using pcolormesh:
import matplotlib.pyplot as plt
import numpy as np
y, x = np.meshgrid(np.linspace(-3, 3,100), np.linspace(-3, 3,100))
z = np.sin(x**2+y**2)
z = z[:-1, :-1]
ax = plt.subplot(111)
quad = plt.pcolormesh(x, y, z)
plt.colorbar()
plt.ion()
plt.show()
for phase in np.linspace(0,10*np.pi,200):
z = np.sin(np.sqrt(x**2+y**2) + phase)
z = z[:-1, :-1]
quad.set_array(z.ravel())
plt.title('Phase: %.2f'%phase)
plt.draw()
plt.ioff()
plt.show()
One of the frames:
Does this help? If not, maybe you can clarify the question.

There is another answer presented here that looks simpler thus better (IMHO)
Here is a copy & paste of the alternative solution :
import matplotlib.pylab as plt
from matplotlib import animation
fig = plt.figure()
plt.hold(True)
#We need to prime the pump, so to speak and create a quadmesh for plt to work with
plt.pcolormesh(X[0:1], Y[0:1], C[0:1])
anim = animation.FuncAnimation(fig, animate, frames = range(2,155), blit = False)
plt.show()
plt.hold(False)
def animate( self, i):
plt.title('Ray: %.2f'%i)
#This is where new data is inserted into the plot.
plt.pcolormesh(X[i-2:i], Y[i-2:i], C[i-2:i])

Connector patch between subplots with animation not visible (matplotlib)

I am using an artist animation method with 5 subplots. There is one static plot on the left, with 3 smaller animated imshow plots to the right (the colorbar is the 5th). I have successfully used ConnectionPatch to connect subplots to show where the data is coming from, but only on static plots. No matter what I try, I can't seem to get the patches to show up on the animation. I've tried to include the patch in the image artist list, tried to update the figure with the artist instead of the axis (which I guess doesn't make much sense), among other things. It will be very difficult to extract a working example due to the complexity of the plot, but maybe someone has a tip.
Could setting the facecolor to 'white' with the animation savefig_kwargs be covering up the connector lines? If so, how do I change the z order of the patch/facecolor?

Without a minimal working example, I can only tell you that it is possible to use a ConnectionPatch in an animation. However, as seen below, one has to recreate it for every frame.
import matplotlib.pyplot as plt
import numpy as np; np.random.seed(0)
import matplotlib.gridspec as gridspec
from matplotlib.patches import ConnectionPatch
import matplotlib.animation
plt.rcParams["figure.figsize"] = np.array([6,3.6])*0.7
x = np.linspace(-3,3)
X,Y = np.meshgrid(x,x)
f = lambda x,y: (1 - x / 2. + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)+1.5
Z = f(X,Y)
bins=np.linspace(Z.min(), Z.max(), 16)
cols = plt.cm.PuOr((bins[:-1]-Z.min())/(Z.max()-Z.min()))
gs = gridspec.GridSpec(2, 2, height_ratios=[34,53], width_ratios=[102,53])
fig = plt.figure()
ax=fig.add_subplot(gs[:,0])
ax2=fig.add_subplot(gs[0,1])
ax3=fig.add_subplot(gs[1,1])
ax.imshow(Z, cmap="PuOr")
rec = plt.Rectangle([-.5,-.5], width=9, height=9, edgecolor="crimson", fill=False, lw=2)
conp = ConnectionPatch(xyA=[-0.5,0.5], xyB=[9.5,4], coordsA="data", coordsB="data",
axesA=ax3, axesB=ax, arrowstyle="-|>", zorder=25, shrinkA=0, shrinkB=1,
mutation_scale=20, fc="w", ec="crimson", lw=2)
ax3.add_artist(conp)
ax.add_artist(rec)
im = ax3.imshow(Z[:9,:9], cmap="PuOr", vmin=Z.min(), vmax=Z.max())
ticks = np.array([0,4,8])
ax3.set_yticks(ticks); ax3.set_xticks(ticks)
ax2.hist(Z[:9,:9].flatten(), bins=bins)
def ins(px,py):
global rec, conp, histpatches
ll = [px-.5,py-.5]
rec.set_xy(ll)
conp.remove()
conp = ConnectionPatch(xyA=[-0.5,0.5], xyB=[px+9.5,py+4], coordsA="data", coordsB="data",
axesA=ax3, axesB=ax, arrowstyle="-|>", zorder=25, shrinkA=0, shrinkB=1,
mutation_scale=20, fc="w", ec="crimson", lw=2)
ax3.add_patch(conp)
data = Z[px:px+9,py:py+9]
im.set_data(data)
ax3.set_xticklabels(ticks+px)
ax3.set_yticklabels(ticks+py)
ax2.clear()
ax2.set_ylim(0,60)
h, b_, patches = ax2.hist(data.flatten(), bins=bins, ec="k", fc="#f1a142")
[pat.set_color(cols[i]) for i, pat in enumerate(patches)]
def func(p):
px,py = p
ins(px, py)
phi = np.linspace(0.,2*np.pi)
r = np.sin(2*phi)*20+np.pi/2
xr = (r*np.cos(phi)).astype(np.int8)
yr = (r*np.sin(phi)).astype(np.int8)
plt.subplots_adjust(top=0.93,bottom=0.11,left=0.04,right=0.96,hspace=0.26,wspace=0.15)
frames = np.c_[xr+20, yr+20]
ani = matplotlib.animation.FuncAnimation(fig, func, frames=frames, interval=300, repeat=True)
plt.show()

Contourf animation

I am using a for loop to calculate values at every node of 20x20 matrix and storing data in
MM = []
I want to animate the results and my code looks like this:
ax = plt.subplot(111)
for i in range(60):
x = MM[i]
ax.contourf(X,Y,x, cmap = cm.hot)
plt.draw()
plt.show()
The problem is that it shows only MM[-1].
I have looked over the examples given here, but can't figure out how to make it work.
Thank you.

Your problem is likely due how you are running Matplotlib and what graphical backend you are using. The following example works in IPython. Note that I call ion() to set the interactive mode to on.
from matplotlib import pyplot as plt
import numpy as np
x = y = np.arange(-3.0, 3.01, 0.025)
X, Y = np.meshgrid(x, y)
plt.ion()
ax = plt.subplot(111)
for i in range(1,20):
Z1 = plt.mlab.bivariate_normal(X, Y, 0.5+i*0.1, 0.5, 1, 1)
ax.contourf(x,y,Z1, cmap = plt.cm.hot)
plt.draw()
plt.show()
The information here should help you get your animation running.