How to make the circle clear transparent? The desired result is a black edge and None colour to see the plots behind the circle.
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # 3d graph
from mpl_toolkits.mplot3d import proj3d # 3d graph
from matplotlib.patches import FancyArrowPatch
from mpl_toolkits.mplot3d import proj3d, art3d
from matplotlib.patches import Circle
# Plot figure
figsize=[5,5]
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(111, projection='3d')
ax.azim = -57 # y rotation (default=270)
ax.elev = 29 # x rotation (default=0)
# Set limits
ax.set_xlim(-50, 50)
ax.set_ylim(0, 1)
ax.set_zlim(-50, 50)
R = 50
floor_front = Circle((0, 0), R, linewidth=2, edgecolor = 'black', alpha = 0.3) # (x, z), radius
ax.add_patch(floor_front)
art3d.pathpatch_2d_to_3d(floor_front, z=0, zdir="y") # z = corresponds to y
plt.show()
In Circle(), add facecolor="none".
Related
I'm trying to change a colorbar attached to a scatter plot so that the minimum and maximum of the colorbar are the minimum and maximum of the data, but I want the data to be centred at zero as I'm using a colormap with white at zero. Here is my example
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 1, 61)
y = np.linspace(0, 1, 61)
C = np.linspace(-10, 50, 61)
M = np.abs(C).max() # used for vmin and vmax
fig, ax = plt.subplots(1, 1, figsize=(5,3), dpi=150)
sc=ax.scatter(x, y, c=C, marker='o', edgecolor='k', vmin=-M, vmax=M, cmap=plt.cm.RdBu_r)
cbar=fig.colorbar(sc, ax=ax, label='$R - R_0$ (mm)')
ax.set_xlabel('x')
ax.set_ylabel('y')
As you can see from the attached figure, the colorbar goes down to -M, where as I want the bar to just go down to -10, but if I let vmin=-10 then the colorbar won't be zerod at white. Normally, setting vmin to +/- M when using contourf the colorbar automatically sorts to how I want. This sort of behaviour is what I expect when contourf uses levels=np.linspace(-M,M,61) rather than setting it with vmin and vmax with levels=62. An example showing the default contourf colorbar behaviour I want in my scatter example is shown below
plt.figure(figsize=(6,5), dpi=150)
plt.contourf(x, x, np.reshape(np.linspace(-10, 50, 61*61), (61,61)),
levels=62, vmin=-M, vmax=M, cmap=plt.cm.RdBu_r)
plt.colorbar(label='$R - R_0$ (mm)')
Does anyone have any thoughts? I found this link which I thought might solve the problem, but when executing the cbar.outline.set_ydata line I get this error AttributeError: 'Polygon' object has no attribute 'set_ydata' .
EDIT a little annoyed that someone has closed this question without allowing me to clarify any questions they might have, as none of the proposed solutions are what I'm asking for.
As for Normalize.TwoSlopeNorm, I do not want to rescale the smaller negative side to use the entire colormap range, I just want the colorbar attached to the side of my graph to stop at -10.
This link also does not solve my issue, as it's the TwoSlopeNorm solution again.
After changing the ylim of the colorbar, the rectangle formed by the surrounding spines is too large. You can make this outline invisible. And then add a new rectangular border:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 1, 61)
y = np.linspace(0, 1, 61)
C = np.linspace(-10, 50, 61)
M = np.abs(C).max() # used for vmin and vmax
fig, ax = plt.subplots(1, 1, figsize=(5, 3), dpi=150)
sc = ax.scatter(x, y, c=C, marker='o', edgecolor='k', vmin=-M, vmax=M, cmap=plt.cm.RdBu_r)
cbar = fig.colorbar(sc, ax=ax, label='$R - R_0$ (mm)')
cb_ymin = C.min()
cb_ymax = C.max()
cb_xmin, cb_xmax = cbar.ax.get_xlim()
cbar.ax.set_ylim(cb_ymin, cb_ymax)
cbar.outline.set_visible(False) # hide the surrounding spines, which are too large after set_ylim
cbar.ax.add_patch(plt.Rectangle((cb_xmin, cb_ymin), cb_xmax - cb_xmin, cb_ymax - cb_ymin,
fc='none', ec='black', clip_on=False))
plt.show()
Another approach until v3.5 is released is to make a custom colormap that does what you want (see also https://matplotlib.org/stable/tutorials/colors/colormap-manipulation.html#sphx-glr-tutorials-colors-colormap-manipulation-py)
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
from matplotlib.colors import ListedColormap
fig, axs = plt.subplots(2, 1)
X = np.random.randn(32, 32) + 2
pc = axs[0].pcolormesh(X, vmin=-6, vmax=6, cmap='RdBu_r')
fig.colorbar(pc, ax=axs[0])
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
from matplotlib.colors import ListedColormap
fig, axs = plt.subplots(2, 1)
X = np.random.randn(32, 32) + 2
pc = axs[0].pcolormesh(X, vmin=-6, vmax=6, cmap='RdBu_r')
fig.colorbar(pc, ax=axs[0])
def keep_center_colormap(vmin, vmax, center=0):
vmin = vmin - center
vmax = vmax - center
dv = max(-vmin, vmax) * 2
N = int(256 * dv / (vmax-vmin))
RdBu_r = cm.get_cmap('RdBu_r', N)
newcolors = RdBu_r(np.linspace(0, 1, N))
beg = int((dv / 2 + vmin)*N / dv)
end = N - int((dv / 2 - vmax)*N / dv)
newmap = ListedColormap(newcolors[beg:end])
return newmap
newmap = keep_center_colormap(-2, 6, center=0)
pc = axs[1].pcolormesh(X, vmin=-2, vmax=6, cmap=newmap)
fig.colorbar(pc, ax=axs[1])
plt.show()
Why is the first arrow not plotted? There is no error after running the script. There should be three arrows but there are only two arrows. Thank you
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.patches as mpatches
import math
import matplotlib.patches as patches
# Plot figure with size
fig, ax = plt.subplots(sharex=True, sharey=True, figsize=(5,5))
# Axis - lim
plt.xlim(-1.5, 1.5)
plt.ylim(-1.5, 1.5)
shift = 0.011
length = 1.3
coord_45 = math.sqrt(1/2)
# Plot an arrow
style="Simple,tail_width=0.5,head_width=4,head_length=8"
kw = dict(arrowstyle=style)
a3 = patches.FancyArrowPatch((0, 0.366618), (0.211427, 0.211427),connectionstyle="arc3,rad=10", **kw)
ax.scatter(0, 0, marker = 'o', s=30)
arrow = mpatches.FancyArrowPatch((0, 0-shift), (0, length), arrowstyle=style)
plt.gca().add_patch(arrow)
arrow = mpatches.FancyArrowPatch((0, 0), (coord_45, -coord_45), arrowstyle=style)
plt.gca().add_patch(arrow)
plt.savefig('file.pdf')
plt.show()
The issue I would like you to figure out is about the coordinantes appearence on matplotlib graph with a double y axis. First of all a code on Jupyter Notebook which draws a graph with two lines and only one y axis (for some unknown reasons I have to run it two times in order to make it working correctly)
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
from IPython.display import display
from IPython.core.display import display, HTML #display multiple output on a cell
display(HTML("<style>.container { width:100% !important; }</style>")) # improve cells horizontal size
from IPython.core.interactiveshell import InteractiveShell # It saves you having to repeatedly type "Display"
InteractiveShell.ast_node_interactivity = "all"
%matplotlib notebook
x = np.arange(0, 10, 0.01)
y1 = np.sin(np.pi*x)/(np.pi*x)
y2 = abs(np.tan(0.1*np.pi*x))
plt.figure()
plt.plot(x, y1)
plt.plot(x, y2)
plt.ylim(0, 3)
plt.grid()
plt.show()
The present figure provides the two lines with cursor coordinates on the right bottom part of the graph.
The following code
import pandas as pd
import os
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
from IPython.display import display
from IPython.core.display import display, HTML #display multiple output on a cell
display(HTML("<style>.container { width:100% !important; }</style>")) # improve cells horizontal size
from IPython.core.interactiveshell import InteractiveShell # It saves you having to repeatedly type "Display"
InteractiveShell.ast_node_interactivity = "all"
%matplotlib notebook
x = np.arange(0, 10, 0.01)
y1 = np.sin(np.pi*x)/(np.pi*x)
y2 = abs(np.tan(0.1*np.pi*x))
# Create some mock data
fig, ax1 = plt.subplots()
plt.grid()
color = 'tab:red'
ax1.set_xlabel('Time (days from 24 February)')
ax1.set_ylabel('Death cases/Intensive care', color=color)
#ax1.set_xlim(0, 15)
#ax1.set_ylim(0, 900)
ax1.plot(x, y1, '-', color=color, label = 'Left hand scale')
ax1.tick_params(axis='y', labelcolor=color)
ax1.legend(loc = 'upper left')
ax2 = ax1.twinx()
color = 'tab:blue'
ax2.set_ylabel('Total cases/currently positive', color=color) # we already handled the x-label with ax1
ax2.plot(x, y2, '-', color=color, label = 'Right hand scale')
ax2.set_ylim(0, 20)
ax2.tick_params(axis='y', labelcolor=color)
ax2.legend(loc = 'lower right')
fig.tight_layout()
plt.show()
Shows the following graph
Which shows a graph with TWO y scales, one red on the left side and one blue on the right side. The problem here is that in the left bottom side of the picture there are the cursor coordinates related to the right scale and nothing about the left one. Is there a way to show up both the two scales?
Depending on your precise needs, mplcursors seems helpful. Mplcursors allows a lot of ways to customize, for example you can show both y-values together with the current x. Or you could suppress the annotation and only write in the status bar.
Setting hover=True constantly displays the plotted values when the mouse hovers over a curve. Default, the values would only be displayed when clicking.
import matplotlib.pyplot as plt
import numpy as np
import mplcursors
# Create some test data
x = np.arange(0, 10, 0.01)
y1 = np.sin(np.pi * x) / (np.pi * x)
y2 = abs(np.tan(0.1 * np.pi * x))
fig, ax1 = plt.subplots()
plt.grid()
color = 'tab:red'
ax1.set_xlabel('Time (days from 24 February)')
ax1.set_ylabel('Death cases/Intensive care', color=color)
lines1 = ax1.plot(x, y1, '-', color=color, label='Left hand scale')
ax1.tick_params(axis='y', labelcolor=color)
ax1.legend(loc='upper left')
ax2 = ax1.twinx()
color = 'tab:blue'
ax2.set_ylabel('Total cases/currently positive', color=color) # we already handled the x-label with ax1
lines2 = ax2.plot(x, y2, '-', color=color, label='Right hand scale')
ax2.set_ylim(0, 20)
ax2.tick_params(axis='y', labelcolor=color)
ax2.legend(loc='lower right')
cursor1 = mplcursors.cursor(lines1, hover=True)
cursor2 = mplcursors.cursor(lines2, hover=True)
fig.tight_layout()
plt.show()
How to crop the figure to have no white space where nothing is plotted? Why plt.tight_layout(pad=0) does not work? The picture draw 3d coordinate system.
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
fig = plt.figure(figsize=[5,3])
ax = fig.gca(projection = '3d')
ax.set_ylim(-2,3)
ax.set_zlim(-1,2)
vleng = 5
aleng = vleng/3.
p = np.array([vleng+200, 0, 0])
q = np.array([0, vleng-2, 0])
r = np.array([0, 0, vleng-3])
ax.plot(*np.vstack([[0,0,0], p]).T, color='black')
ax.plot(*np.vstack([[0,0,0], q]).T, color='black')
ax.plot(*np.vstack([[0,0,0], r]).T, color='black')
ax.azim = 20 # y rotation (default=270)
ax.elev = 20 # x rotation (default=0)
ax.dist = 10 # zoom (define perspective)
ax.set_axis_off( ) # hide all grid
plt.tight_layout(pad=0)
plt.show()
The output:
figure
So I tried multiple things. The only thing that would reduce these white spaces would require the three lines to be drawn along the meeting lines of the planes. So I did some measurements and here's the code where the white spaces have significantly reduced. You're free to reduce it further by tweaking it some more. Also comment out ax.set_axis_off( ) to see what's happening:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
fig = plt.figure(figsize=[5,3])
ax = fig.gca(projection = '3d')
ax.set_ylim(0,3)
ax.set_zlim(0,2)
# ax.set_xlim(0,2)
vleng = 5
aleng = vleng/3.
p = np.array([vleng+200, 0, 0])
q = np.array([0, vleng-2, 0])
r = np.array([0, 0, vleng-3])
ax.plot(*np.vstack([[0,0,0], p]).T, color='black')
ax.plot(*np.vstack([[0,0,0], q]).T, color='black')
ax.plot(*np.vstack([[0,0,0], r]).T, color='black')
ax.azim = 20 # y rotation (default=270)
ax.elev = 20 # x rotation (default=0)
ax.dist = 10 # zoom (define perspective)
ax.set_axis_off( ) # hide all grid
plt.tight_layout(pad=0)
plt.show()
draw a graph of equation in the form of y=mx+b in python3.x
example y = 5x + 9
This is a very general question. Try to be more specific. It depends how you want to draw it.
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0., 5., 0.2)
y = 5 * x + 9
plt.plot(x, y)
plt.show()
or
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(-1., 5., 0.2)
y = 5 * x + 9
fig, ax = plt.subplots()
ax.plot(x,y)
ax.grid(True, which='both')
ax.axhline(y=0, color='k')
ax.axvline(x=0, color='k')
These are very basic drawing. You can create more sophisticated graphs, but you will have to be more specific in your question.
You can define your y(x) function and then plot it as follows:
import matplotlib.pyplot as plt
def y(x):
return [5*i+9 for i in x]
x = range(0,10)
plt.plot(x,y(x))
plt.show()
This produces follwing graph:
With turtle
You can as well get a graph with turtle with following code for example:
from turtle import Turtle, Screen
def y(x):
return 5*x+9
def plotter(turtle, x_range):
turtle.penup()
for x in x_range:
turtle.goto(x, y(x))
turtle.pendown()
screen = Screen()
screen.setworldcoordinates(0, 0, 9, 60)
turtle = Turtle(visible=False)
x = range(0,10)
plotter(turtle, x)
screen.exitonclick()
Which produces: