I am trying to create a 3D animation scatter plot where each point is plotted as a sphere with radius of r proportional to value M (please see the code below), I guess it should be done by using argument s in ax.scatter, but since this value is unique for each (x,y,z), I don't know how to pass that to graph._offsets3d which accepts (x,y,z) touple. This is the first part of the task, the other part is that the data should appear at their specific time t (please see the code below).
I am currently struggling to change the size of each point according to their corresponding value in M, and color code the point with its corresponding time t, do you know how could I do this?
It would my next task to add a play/pause button to the figure and be able to rotate the the graph?
Does anyone have similar experiences that I could benefit from?
Many thanks!
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as animation
#####Data Generation####
# Space Coordinate
X = np.random.random((100,)) * 255 * 2 - 255
Y = np.random.random((100,)) * 255 * 2 - 255
Z = np.random.random((100,)) * 255 * 2 - 255
# Magnitude of each point
M = np.random.random((100,))*-1+0.5
# Time
t = np.sort(np.random.random((100,))*10)
#ID each point should be color coded. Moreover, each point belongs to a cluster `ID`
ID = np.sort(np.round([np.random.random((100,))*5]))
def update_lines(num):
for i in range (df_IS["EASTING [m]"].size):
dx = X[i]
dy = Y[i]
dz = Z[i]
text.set_text("{:d}: [{:.0f}] Mw[{:.2f}]".format(ID[i], t[i],ID[i])) # for debugging
x.append(dx)
y.append(dy)
z.append(dz)
graph._offsets3d = (x, y, z)
return graph,
fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(111, projection="3d")
graph = ax.scatter(X, Y, Z, color='orange') # s argument here
text = fig.text(0, 1, "TEXT", va='top') # for debugging
ax.set_xlim3d(X.min(), X.max())
ax.set_ylim3d(Y.min(), Y.max())
ax.set_zlim3d(Z.min(),Z.max())
# Creating the Animation object
ani = animation.FuncAnimation(fig, update_lines, frames=200, interval=500, blit=False)
plt.show()
In the animation function was looped by the size of the data frame, but rewrote your code partly because the animation argument is linked to the number of frames. Please correct me if I'm wrong. You can also pass in the size with graph.set_sizes(), which you can specify there. Your size variable had a negative value, so I'm recreating it as an integer. I've used a separate library in part because of my working environment.
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as animation
from IPython.display import HTML # Animation on jupyter lab
from matplotlib.animation import PillowWriter # For GIF animation
#####Data Generation####
# Space Coordinate
X = np.random.random((100,)) * 255 * 2 - 255
Y = np.random.random((100,)) * 255 * 2 - 255
Z = np.random.random((100,)) * 255 * 2 - 255
# Magnitude of each point
# M = np.random.random((100,))*-1+0.5
M = np.random.randint(1,70, size=100)
# Time
t = np.sort(np.random.random((100,))*10)
#ID each point should be color coded. Moreover, each point belongs to a cluster `ID`
ID = np.sort(np.round([np.random.random((100,))*5]))
x = []
y = []
z = []
m = []
def update_lines(i):
# for i in range (df_IS["EASTING [m]"].size):
dx = X[i]
dy = Y[i]
dz = Z[i]
dm = M[i]
# text.set_text("{:d}: [{:.0f}] Mw[{:.2f}]".format(ID[i], t[i],ID[i])) # for debugging
x.append(dx)
y.append(dy)
z.append(dz)
m.append(dm)
graph._offsets3d = (x, y, z)
graph.set_sizes(m)
return graph,
fig = plt.figure(figsize=(5, 5))
ax = fig.add_subplot(111, projection="3d")
graph = ax.scatter(X, Y, Z, s=M, color='orange') # s argument here
text = fig.text(0, 1, "TEXT", va='top') # for debugging
ax.set_xlim3d(X.min(), X.max())
ax.set_ylim3d(Y.min(), Y.max())
ax.set_zlim3d(Z.min(), Z.max())
# Creating the Animation object
ani = animation.FuncAnimation(fig, update_lines, frames=100, interval=500, blit=False, repeat=False)
# plt.show()
ani.save('test3Dscatter.gif', writer='pillow')
plt.close()
HTML(ani.to_html5_video())
Edit:
# Time
t = np.sort(np.random.random((100,))*10)
# datapoint for color
cm_name = 'jet'
cm = plt.get_cmap(cm_name, 100)
C = [cm(n) for n in range(cm.N)]
# list for colors add
x = []
y = []
z = []
m = []
c = []
# animation function update
dm = M[i]
dc = C[i] # update
m.append(dm)
c.append(dc) # update
graph._facecolor3d = c # scatter color defined
return graph,
Related
I have the following code which creates a graph animation. The graph should start from 0, but the 1st interval graph isn't coming.
Below is the code:
import matplotlib.pylab as plt
import matplotlib.animation as animation
import numpy as np
fig, ax = plt.subplots()
left = -1
right = 2*np.pi - 1
def animate(i):
global left, right
left = left + 1
right = right + 1
x = np.linspace(left, right, 50)
y = np.cos(x)
ax.cla()
ax.set_xlim(left, right)
ax.plot(x, y, lw=2)
ani = animation.FuncAnimation(fig, animate, interval = 1000)
plt.show()
For the 1st interval [0, 2π] the graph isn't coming.
What's the mistake?
I changed a little bit your code:
first of all I plot the first frame outside the animate function and I generate a line object from it
then I update the line data within animate function
I suggest to use i counter (which starts from 0 and increases by 1 in each frame) to update your data, in place of calling global variables and change them
Complete Code
import matplotlib.pylab as plt
import matplotlib.animation as animation
import numpy as np
fig, ax = plt.subplots()
left = 0
right = 2*np.pi
x = np.linspace(left, right, 50)
y = np.cos(x)
line, = ax.plot(x, y)
ax.set_xlim(left, right)
def animate(i):
x = np.linspace(left + i, right + i, 50)
y = np.cos(x)
line.set_data(x, y)
ax.set_xlim(left + i, right + i)
return line,
ani = animation.FuncAnimation(fig = fig, func = animate, interval = 1000)
plt.show()
So I am trying to make a game of life using matplotlib's FuncAnimation function to update the grid I am displaying. However, the process is taking longer and longer, probably because I am not pointing out what I am updating. I am not very familiar with the concept of artists either.
For the moment, my code looks like this :
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors
import random as rd
import matplotlib.animation as animation
from time import process_time
Ln = 100 # length
La = 10 # width
data = np.ones((Ln, La)) * np.nan # matrix filled with 0 containing the squares to be colored
pause = False # puts in pause when clicking
Case = [(i, j) for i in range(Ln) for j in range(La)] # squares of the grid
Case = dict(zip([i for i in range(La*Ln)], Case))
def randometre(a):
'''
Colors a square.
'''
while Case:
if not pause:
xx, yy = Case.pop(rd.choice(list(Case.keys()))) # colors the next square in a random order
data[xx, yy] = 1 # square that is being colored
ax.fill_between([xx, xx + 1], [yy], [yy + 1], color=C)
break # to see the coloring process
return
def on_click(event):
global pause
pause ^= True
# random color generation
C = '#%02X%02X%02X' % (rd.randint(0,255), rd.randint(0,255), rd.randint(0,255))
xx = 0
yy = 0
# plotting
fig = plt.figure()
ax = fig.add_subplot(111)
fig.canvas.mpl_connect('button_press_event', on_click)
# drawing grid and squares
for y in range(La + 1):
ax.plot([0, Ln], [y, y], lw=2, color='k')
for x in range(Ln + 1):
ax.plot([x, x], [0, La], lw=2, color='k')
# loop coloring squares
ani = animation.FuncAnimation(fig, randometre, blit=False, interval=10, repeat=False, frames=La*Ln)
ax.axis('off')
plt.show()
So what I need is the fastest way to color the squares as well as being able to see the progress live without slowing down.
A similar issue has been raised here but I can't manage to adapt it to my code unfortunately...
Thank you very much for your time and help !
You should use blit=True, I did two modifications to your code. Now is fast.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors
import random as rd
import matplotlib.animation as animation
from time import process_time
Ln = 100 # length
La = 10 # width
data = np.ones((Ln, La)) * np.nan # matrix filled with 0 containing the squares to be colored
pause = False # puts in pause when clicking
Case = [(i, j) for i in range(Ln) for j in range(La)] # squares of the grid
Case = dict(zip([i for i in range(La*Ln)], Case))
def randometre(a):
'''
Colors a square.
'''
while Case:
if not pause:
xx, yy = Case.pop(rd.choice(list(Case.keys()))) # colors the next square in a random order
data[xx, yy] = 1 # square that is being colored
poly = ax.fill_between([xx, xx + 1], [yy], [yy + 1], color=C)
break # to see the coloring process
return poly, # must return something to make blit=True to work
def on_click(event):
global pause
pause ^= True
# random color generation
C = '#%02X%02X%02X' % (rd.randint(0,255), rd.randint(0,255), rd.randint(0,255))
xx = 0
yy = 0
# plotting
fig = plt.figure()
ax = fig.add_subplot(111)
fig.canvas.mpl_connect('button_press_event', on_click)
# drawing grid and squares
for y in range(La + 1):
ax.plot([0, Ln], [y, y], lw=2, color='k')
for x in range(Ln + 1):
ax.plot([x, x], [0, La], lw=2, color='k')
# loop coloring squares, blit=True
ani = animation.FuncAnimation(fig, randometre, blit=True, interval=10, repeat=False, frames=La*Ln)
ax.axis('off')
I want to have an animation of my plot of my results of the mc method calculating pi; but having the inner circle dots colored differently than the others. How can I do that?
This is my code so far:
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.animation import FuncAnimation
def punkt_im_quadrat(a,N): #a is length of square, N number of dots
"""generates random point in [0,a)x[0,a)"""
x = a * np.random.random_sample((N,2))
return x #[x,y]
def kreis(radius):
return np.sqrt(radius - x**2)
x = np.linspace(0,1,100)
#create array of N=10 dots
punkte = punkt_im_quadrat(1,10) #a=1, so radius of circle is one
treffer = [i for i in punkte if i[1] <= np.sqrt(1 - i[0]**2)] #dots in circle
treffer = np.array(treffer)
außerhalb = [i for i in punkte if i not in treffer] #dots not in circle
außerhalb = np.array(außerhalb)
pi = 4 * len(treffer) / np.shape(punkte)[0]
fig = plt.figure()
fig, ax = plt.subplots()
ax.plot(x,kreis(1))
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.set(title=r"MC Sampling for $\pi$",
ylabel="y-axis",
xlabel="x-axis")
#colors = ["r" if [punkte[i][0],punkte[i][1]] in treffer else "b"]
graph, = ax.plot([],[], "ro")
def animate(i):
graph.set_data((punkte[:i,0],), (punkte[:i,1],))
return graph,
animation = FuncAnimation(fig, func=animate, frames = range(np.shape(punkte)[0]), interval=20, repeat = False)
plt.show()
As you can see, I have tried to change the colors by using the commented color if statement; but it then says
IndexError: arrays used as indices must be of integer (or boolean) type
I then thought I could do an if statement in the animated-function, to determine where the dot is. But when using graph.set_color it changes all dots color.
I'd be really happy if someone can help me.
Thanks in advance!
All the markers in a plot have the same color, so that cannot work. If you want different colors for different points, you need to use scatter()
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.animation import FuncAnimation
def punkt_im_quadrat(a,N): #a is length of square, N number of dots
"""generates random point in [0,a)x[0,a)"""
x = a * np.random.random_sample((N,2))
return x #[x,y]
def kreis(radius):
return np.sqrt(radius - x**2)
x = np.linspace(0,1,100)
#create array of N=10 dots
punkte = punkt_im_quadrat(1,10) #a=1, so radius of circle is one
treffer = [i for i in punkte if i[1] <= np.sqrt(1 - i[0]**2)] #dots in circle
treffer = np.array(treffer)
außerhalb = [i for i in punkte if i not in treffer] #dots not in circle
außerhalb = np.array(außerhalb)
colors = np.array(["r" if i[1] <= np.sqrt(1 - i[0]**2) else "b" for i in punkte])
pi = 4 * len(treffer) / np.shape(punkte)[0]
fig, ax = plt.subplots()
ax.plot(x,kreis(1))
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.set(title=r"MC Sampling for $\pi$",
ylabel="y-axis",
xlabel="x-axis")
graph = ax.scatter([],[], marker='o', s=30)
def animate(i):
graph.set_offsets(punkte[:i,:])
graph.set_facecolor(colors[:i])
return graph,
animation = FuncAnimation(fig, func=animate, frames = range(np.shape(punkte)[0]), interval=20, repeat = False)
Is there a way to align python basemaps like this figure below?
Here's some sample basemap code to produce a map:
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(8, 4.5))
plt.subplots_adjust(left=0.02, right=0.98, top=0.98, bottom=0.00)
m = Basemap(projection='robin',lon_0=0,resolution='c')
m.fillcontinents(color='gray',lake_color='white')
m.drawcoastlines()
plt.savefig('world.png',dpi=75)
I am not an expert with Matplotlib, but I found a way to get a similar result by using the data files included in the source folder of basemap. They can be combined into a meshgrid to plot some data, in the example below we plot the altitude at every point.
One of the tricks I used is to set matplotlib to an orthogonal projection so that there is no distortion in the vertical spacing of the maps.
I have put the parameters at the beginning of the code as you may find it useful to adjust.
One thing I couldn't get my head around is the shadow under the maps.
from mpl_toolkits.mplot3d import proj3d
from mpl_toolkits.basemap import Basemap
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import numpy as np
import matplotlib.pyplot as plt
# Parameters
n_maps = 5 # Number of maps
z_spacing = 4. # Spacing of maps along z
z_reduction = 1E-8 # Reduction factor for Z data, makes the map look flat
view_angles = (14., -100.) # Set view port angles
colbar_bottom = 0.2 # Space at the bottom of colorbar column
colbar_spacing = .132 # Space between colorbars
colbar_height = 0.1 # Height of colorbars
# Set orthogonal projection
def orthogonal_proj(zfront, zback):
a = (zfront+zback)/(zfront-zback)
b = -2*(zfront*zback)/(zfront-zback)
return np.array([[1,0,0,0],
[0,1,0,0],
[0,0,a,b],
[0,0,-0.0001,zback]])
proj3d.persp_transformation = orthogonal_proj
fig = plt.figure(figsize=[30, 10*n_maps])
ax = fig.gca(projection='3d')
etopo = np.loadtxt('etopo20data.gz')
lons = np.loadtxt('etopo20lons.gz')
lats = np.loadtxt('etopo20lats.gz')
# Create Basemap instance for Robinson projection.
m = Basemap(projection='robin', lon_0=0.5*(lons[0]+lons[-1]))
# Compute map projection coordinates for lat/lon grid.
X, Y = m(*np.meshgrid(lons,lats))
# Exclude the oceans
Z = etopo.clip(-1)
# Set the colormap
cmap = plt.cm.get_cmap("terrain")
cmap.set_under("grey")
for i in range(n_maps):
c = ax.contourf(X, Y, z_spacing*i + z_reduction*Z, 30, cmap=cmap, vmin=z_spacing*i, extend='neither')
cax = inset_axes(ax,
width="5%",
height="100%",
loc=3,
bbox_to_anchor=(.85, colbar_spacing*i+colbar_bottom, .2, colbar_height),
bbox_transform=ax.transAxes,
borderpad=0
)
cb = fig.colorbar(c, cax=cax)
cb.set_label("Altitude")
# Reset the ticks of the color bar to match initial data
cb.set_ticks([z_spacing * i + j/10. * z_reduction * Z.max() for j in range(11)])
cb.set_ticklabels([str(int(j/10. * Z.max())) for j in range(11)])
ax.set_axis_off()
ax.view_init(*view_angles)
ax.set_xlim3d(X.min(), X.max())
ax.set_ylim3d(Y.min(), Y.max())
ax.set_zlim3d(-1E-2, (n_maps-1)*z_spacing)
plt.savefig('world.png',dpi=75)
Edit:
If you want shadows and don't mind the extra compute time you can change the beginning of the for loop with something along the lines of:
shadow_Z = np.empty(Z.shape)
for i in range(n_maps):
c = ax.contourf(X, Y, z_spacing*i + z_reduction*Z, 30, cmap=cmaps[i], vmin=z_spacing*i, extend='neither')
for j in range(10):
shadow_Z.fill(z_spacing*i - 1E-2 * j)
s = ax.contourf((X - X.mean()) * (1 + 8E-3 * j) + X.mean() + 2E5,
(Y - Y.mean()) * (1 + 8E-3 * j) + Y.mean() - 2E5,
shadow_Z, colors='black', alpha=0.1 - j * 1E-2)
I want to create an animation showing a diver jumps into water.
By the given parameters of original height of diver from the water, h and his mass, m, I defined a procedure in Python to calculate the moment he touches the water, Tc .
Knowing that he jumps vertically, X axis is fixed, and
Y axis obeys equation (1/2)gt^2 + h (g is gravitational constant)
How do I plot a graph while time t is in range(Tc), X and Y axis shows the projection the diver? (x is fixed and y depends on time t)
In the graphic window we are supposed to see a dot that 'jumps' from certain height vertically downwards, without seeing the line/trace of projection.
Here is part of my work. I don't know where to introduce Tc in the procedure:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], lw=2)
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(i):
x = np.empty(n) ; x.fill(1) # the vertical position is fixed on x-axis
y = 0.5*g*i^2 + h # the equation of diver's displacement on y axis
line.set_data(x, y)
return line,
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=200, interval=20, blit=True)
plt.show()
Edit:
Here is the whole program. I applied and modified the suggestion given by #Mike Muller, but it didn't work. I don’t understand where it goes wrong. Hope you can clarify my doubts.
# -*- coding: utf-8 -*-
from math import *
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
def Plongeon():
h = input("height = ")
h = float(h)
m = input(" mass = ")
m = float(m)
global g
g = 9.8
g = float(g)
global Tc #calculate air time, Tc
Tc = sqrt(2*h/g)
Tc = round(Tc,2)
print Tc
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, h+1)) #ymax : initial height+1
line, = ax.plot([], [], ' o', lw=2)
Tc = int(Tc+1) #make Tc an integer to be used later in def get_y()
xs = [1] # the vertical position is fixed on x-axis
ys = [h, h]
# initialization function: plot the background of each frame
def init():
line.set_data([], [])
return line,
# animation function. This is called sequentially
def animate(y):
ys[-1] = y
line.set_data(xs, ys)
return line,
def get_y():
for step in range(Tc):
t = step / 100.0
y = -0.5*g*t**2 + h # the equation of diver's displacement on y axis
yield y
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, frames=get_y, interval=100)
plt.show()
Plongeon()
Answer based on original question
You need to use a generator to produce your y data. This works:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))
line, = ax.plot([], [], ' o', lw=2)
g = 9.81
h = 2
tc = 200
xs = [1] # the vertical position is fixed on x-axis
ys = [h, h]
# animation function. This is called sequentially
def animate(y):
ys[-1] = y
line.set_data(xs, ys)
return line,
def get_y():
for step in range(tc):
t = step / 100.0
y = -0.5*g*t**2 + h # the equation of diver's displacement on y axis
yield y
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, frames=get_y, interval=100)
plt.show()
Integrated answer
This should work:
# -*- coding: utf-8 -*-
from math import *
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
def Plongeon():
h = float(input("height = "))
g = 9.81
#calculate air time, Tc
Tc = sqrt(2 * h / g)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(-2, h+1)) #ymax : initial height+1
line, = ax.plot([], [], ' o', lw=2)
step = 0.01 # animation step
xs = [1] # the vertical position is fixed on x-axis
ys = [h]
# animation function. This is called sequentially
def animate(y):
ys[-1] = y
line.set_data(xs, ys)
return line,
def get_y():
t = 0
while t <= Tc:
y = -0.5 * g * t**2 + h # the equation of diver's displacement on y axis
yield y
t += step
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, frames=get_y, interval=100)
plt.show()
Plongeon()
I removed unneeded lines. No need for global. Also mass has never been used anywhere in the program.
This is the most important part:
def get_y():
t = 0
while t <= Tc:
y = -0.5 * g * t**2 + h
yield y
t += step
You need to advance your time by an increment.