Plotting a normalized array in Matplotlib
Question:
I am trying to represent the array Pe using lines as shown in the current output but the colors of the lines do not reflect the actual array. For example, line marked 0 has the value 394.20560747663563 and should be blue instead it is yellow.
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from matplotlib.colors import Normalize
from matplotlib import cm
import math
from numpy import nan
fig,aPe = plt.subplots(1)
n=3
N=2*n*(n-1)
J = np.array([[]])
Pe=np.array([[394.20560747663563, 408.7929050665396 , 419.132709901089 ,
398.95097406721044, 403.81198021076113, 430.00914784982064,
424.50127213826016, 453.54817733128607, 441.4651085668709 ,
447.42507960635163, 413.8982415602072 , 390.3025816600353 ]])
C1 = nan
for i in J[0]:
Pe = np.insert(Pe, i, [C1], axis=1)
print("Pe =", [Pe])
for i in range(0,len(Pe)):
Max=max(max(Pe[i]), max(Pe[i]))
Min=min(min(Pe[i]), min(Pe[i]))
a=Min
b=Max
Amax= math.ceil(Max)
Amin= math.floor(Min)
print(Amax, Amin)
color = cm.get_cmap('Dark2')
norm = Normalize(vmin=Amin, vmax=Amax)
color_list = []
for i in range(len(Pe[0])):
color_list.append(color(Pe[0,i]/Amax))
id = 0
for j in range(0, n):
for k in range(n-1):
aPe.hlines(200+200*(n-j-1)+5*n, 200*(k+1)+5*n, 200*(k+2)+5*n, zorder=0, colors=color_list[id])
id += 1
for i in range(0, n):
rect = mpl.patches.Rectangle((200+200*i, 200+200*j), 10*n, 10*n, linewidth=1, edgecolor='black', facecolor='black')
aPe.add_patch(rect)
if j < n-1:
aPe.vlines(200+200*i+5*n, 200*(n-1-j)+5*n, 200*(n-j)+5*n, zorder=0, colors=color_list[id])
id += 1
cb = fig.colorbar(cm.ScalarMappable(cmap=color, norm=norm))
cb.set_label("Entry pressure (N/m$^{2}$)")
aPe.set_xlim(left = 0, right = 220*n)
aPe.set_ylim(bottom = 0, top = 220*n)
plt.axis('off')
plt.show()
The current output is
Answers:
The problem is how you are trying to get your colors from color(). You need to first set the scale so that the value 390 Amin is equivalent to 0 and 454 Amax is equivalent to 1. To do this, subtract the Amin from the values then divide that by the difference of Amax and Amin. So the color_list will be created by:
for i in range(len(Pe[0])):
color_list.append(color(((Pe[0,i])-Amin)/(Amax-Amin)))
The values are:
[394.20560747663563,
408.7929050665396,
419.132709901089,
398.95097406721044,
403.81198021076113,
430.00914784982064,
424.50127213826016,
453.54817733128607,
441.4651085668709,
447.42507960635163,
413.8982415602072,
390.3025816600353]
And the values used for grabbing the colors from color() are:
[0.06571261682243179,
0.2936391416646815,
0.45519859220451586,
0.1398589698001631,
0.21581219079314273,
0.6251429351534474,
0.539082377160315,
0.9929402708013448,
0.8041423213573582,
0.8972668688492442,
0.3734100243782379,
0.004727838438051357]
Which, when put all together, gives you the graph:
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from matplotlib.colors import Normalize
from matplotlib import cm
import math
from numpy import nan
fig,aPe = plt.subplots(1)
n=3
N=2*n*(n-1)
J = np.array([[]])
Pe=np.array([[394.20560747663563, 408.7929050665396 , 419.132709901089 ,
398.95097406721044, 403.81198021076113, 430.00914784982064,
424.50127213826016, 453.54817733128607, 441.4651085668709 ,
447.42507960635163, 413.8982415602072 , 390.3025816600353 ]])
C1 = nan
for i in J[0]:
Pe = np.insert(Pe, i, [C1], axis=1)
print("Pe =", [Pe])
for i in range(0,len(Pe)):
Max=max(max(Pe[i]), max(Pe[i]))
Min=min(min(Pe[i]), min(Pe[i]))
a=Min
b=Max
Amax= math.ceil(Max)
Amin= math.floor(Min)
print(Amax, Amin)
color = cm.get_cmap('Dark2')
norm = Normalize(vmin=Amin, vmax=Amax)
color_list = []
for i in range(len(Pe[0])):
color_list.append(color(((Pe[0,i])-Amin)/(Amax-Amin)))
id = 0
for j in range(0, n):
for k in range(n-1):
aPe.hlines(200+200*(n-j-1)+5*n, 200*(k+1)+5*n, 200*(k+2)+5*n, zorder=0, colors=color_list[id])
id += 1
for i in range(0, n):
rect = mpl.patches.Rectangle((200+200*i, 200+200*j), 10*n, 10*n, linewidth=1, edgecolor='black', facecolor='black')
aPe.add_patch(rect)
if j < n-1:
aPe.vlines(200+200*i+5*n, 200*(n-1-j)+5*n, 200*(n-j)+5*n, zorder=0, colors=color_list[id])
id += 1
cb = fig.colorbar(cm.ScalarMappable(cmap=color, norm=norm), ticks=np.arange(Amin, Amax+len(color.colors), len(color.colors)))
cb.set_label("Entry pressure (N/m$^{2}$)")
aPe.set_xlim(left = 0, right = 220*n)
aPe.set_ylim(bottom = 0, top = 220*n)
plt.axis('off')
plt.show()
I am trying to represent the array Pe using lines as shown in the current output but the colors of the lines do not reflect the actual array. For example, line marked 0 has the value 394.20560747663563 and should be blue instead it is yellow.
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from matplotlib.colors import Normalize
from matplotlib import cm
import math
from numpy import nan
fig,aPe = plt.subplots(1)
n=3
N=2*n*(n-1)
J = np.array([[]])
Pe=np.array([[394.20560747663563, 408.7929050665396 , 419.132709901089 ,
398.95097406721044, 403.81198021076113, 430.00914784982064,
424.50127213826016, 453.54817733128607, 441.4651085668709 ,
447.42507960635163, 413.8982415602072 , 390.3025816600353 ]])
C1 = nan
for i in J[0]:
Pe = np.insert(Pe, i, [C1], axis=1)
print("Pe =", [Pe])
for i in range(0,len(Pe)):
Max=max(max(Pe[i]), max(Pe[i]))
Min=min(min(Pe[i]), min(Pe[i]))
a=Min
b=Max
Amax= math.ceil(Max)
Amin= math.floor(Min)
print(Amax, Amin)
color = cm.get_cmap('Dark2')
norm = Normalize(vmin=Amin, vmax=Amax)
color_list = []
for i in range(len(Pe[0])):
color_list.append(color(Pe[0,i]/Amax))
id = 0
for j in range(0, n):
for k in range(n-1):
aPe.hlines(200+200*(n-j-1)+5*n, 200*(k+1)+5*n, 200*(k+2)+5*n, zorder=0, colors=color_list[id])
id += 1
for i in range(0, n):
rect = mpl.patches.Rectangle((200+200*i, 200+200*j), 10*n, 10*n, linewidth=1, edgecolor='black', facecolor='black')
aPe.add_patch(rect)
if j < n-1:
aPe.vlines(200+200*i+5*n, 200*(n-1-j)+5*n, 200*(n-j)+5*n, zorder=0, colors=color_list[id])
id += 1
cb = fig.colorbar(cm.ScalarMappable(cmap=color, norm=norm))
cb.set_label("Entry pressure (N/m$^{2}$)")
aPe.set_xlim(left = 0, right = 220*n)
aPe.set_ylim(bottom = 0, top = 220*n)
plt.axis('off')
plt.show()
The current output is
The problem is how you are trying to get your colors from color(). You need to first set the scale so that the value 390 Amin is equivalent to 0 and 454 Amax is equivalent to 1. To do this, subtract the Amin from the values then divide that by the difference of Amax and Amin. So the color_list will be created by:
for i in range(len(Pe[0])):
color_list.append(color(((Pe[0,i])-Amin)/(Amax-Amin)))
The values are:
[394.20560747663563,
408.7929050665396,
419.132709901089,
398.95097406721044,
403.81198021076113,
430.00914784982064,
424.50127213826016,
453.54817733128607,
441.4651085668709,
447.42507960635163,
413.8982415602072,
390.3025816600353]
And the values used for grabbing the colors from color() are:
[0.06571261682243179,
0.2936391416646815,
0.45519859220451586,
0.1398589698001631,
0.21581219079314273,
0.6251429351534474,
0.539082377160315,
0.9929402708013448,
0.8041423213573582,
0.8972668688492442,
0.3734100243782379,
0.004727838438051357]
Which, when put all together, gives you the graph:
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
from matplotlib.colors import Normalize
from matplotlib import cm
import math
from numpy import nan
fig,aPe = plt.subplots(1)
n=3
N=2*n*(n-1)
J = np.array([[]])
Pe=np.array([[394.20560747663563, 408.7929050665396 , 419.132709901089 ,
398.95097406721044, 403.81198021076113, 430.00914784982064,
424.50127213826016, 453.54817733128607, 441.4651085668709 ,
447.42507960635163, 413.8982415602072 , 390.3025816600353 ]])
C1 = nan
for i in J[0]:
Pe = np.insert(Pe, i, [C1], axis=1)
print("Pe =", [Pe])
for i in range(0,len(Pe)):
Max=max(max(Pe[i]), max(Pe[i]))
Min=min(min(Pe[i]), min(Pe[i]))
a=Min
b=Max
Amax= math.ceil(Max)
Amin= math.floor(Min)
print(Amax, Amin)
color = cm.get_cmap('Dark2')
norm = Normalize(vmin=Amin, vmax=Amax)
color_list = []
for i in range(len(Pe[0])):
color_list.append(color(((Pe[0,i])-Amin)/(Amax-Amin)))
id = 0
for j in range(0, n):
for k in range(n-1):
aPe.hlines(200+200*(n-j-1)+5*n, 200*(k+1)+5*n, 200*(k+2)+5*n, zorder=0, colors=color_list[id])
id += 1
for i in range(0, n):
rect = mpl.patches.Rectangle((200+200*i, 200+200*j), 10*n, 10*n, linewidth=1, edgecolor='black', facecolor='black')
aPe.add_patch(rect)
if j < n-1:
aPe.vlines(200+200*i+5*n, 200*(n-1-j)+5*n, 200*(n-j)+5*n, zorder=0, colors=color_list[id])
id += 1
cb = fig.colorbar(cm.ScalarMappable(cmap=color, norm=norm), ticks=np.arange(Amin, Amax+len(color.colors), len(color.colors)))
cb.set_label("Entry pressure (N/m$^{2}$)")
aPe.set_xlim(left = 0, right = 220*n)
aPe.set_ylim(bottom = 0, top = 220*n)
plt.axis('off')
plt.show()