"""this example demonstrates how to make a multiple
subplots of a VisualArray in multiple sides"""
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
arr = np.random.randint(100, size=60).reshape((2, 6, 5))
coords = np.array(list(np.ndindex(arr.shape)))
cells = coords[np.sum(coords, axis=1) % 3 == 0]
fig = plt.figure()
ax = fig.add_subplot(2, 1, 1, projection='3d')
ax.set_title('top')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(cells.T, color='yellow', basecolor='lightblue')
va.vizualize(fixview=True)
ax = fig.add_subplot(2, 1, 2, projection='3d')
ax.set_title('bottom')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(cells.T, color='yellow', basecolor='lightblue')
va.vizualize(fixview=True)
ax.elev = -30
plt.show()
from numpyviz import VisualArray
import matplotlib.gridspec as gridspec
arr = np.random.randint(99, size=(3, 3, 4))
fig = plt.figure(constrained_layout=True)
spec = gridspec.GridSpec(ncols=10,
nrows=3,
hspace=0.05,
wspace=0.05,
figure=fig)
ax = fig.add_subplot(spec[1, 0], projection='3d')
ax.dist = 11 #zoom out a little
ax.set_title(f'arr of shape={arr.shape}')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(np.where(arr > 65), color='lawngreen', basecolor='aqua')
va.vizualize(fixview=True, axis_labels=('axis=0', 'axis=1', 'axis=2'))
idx = np.indices(arr.shape)
for n in range(3):
ax = fig.add_subplot(spec[n, 2], projection='3d')
ax.dist = 11 #zoom out a little
ax.set_title(f'np.indices({arr.shape})[{n}]')
va = VisualArray(idx[n], fig=fig, ax=ax)
va.set_colors(np.where(arr > 65),
color='lightgreen',
basecolor='lightblue')
va.vizualize(fixview=True, axis_labels=('axis=0', 'axis=1', 'axis=2'))
for n in range(3):
ax = fig.add_subplot(spec[n, 4:], projection='3d')
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
v = np.array([[2, 5, 3, 5, 1, 8], [4, 6, 2, 7, 5, 9], [1, 8, 2, 3, 1, 4],
[2, 8, 1, 4, 3, 5], [5, 7, 2, 3, 7, 8], [1, 2, 4, 6, 3, 5],
[3, 5, 2, 8, 1, 4]])
s = np.sort(v, axis=1)
arr1 = v[(s[:, :-1] != s[:, 1:]).all(1)]
arr2 = arr1.reshape(-1, 3, 2)
fig = plt.figure()
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.set_title('Initial array')
va = VisualArray(arr1, fig=fig, ax=ax)
va.set_colors(va.get_indices().T, color='yellow', basecolor='lightblue')
va.vizualize(fixview=True, axis_labels=(None, 'axis=0', 'axis=1'))
ax.dist = 12
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.set_title('Reshaped array')
va = VisualArray(arr2, fig=fig, ax=ax)
va.set_colors(va.get_indices().T, color='yellow', basecolor='lightblue')
va.vizualize(fixview=True)
ax.dist = 12
plt.show()
arr = np.array([[
r'$\times$', r'$x^2$', r'$y^2$', r'$z^2$', r'$-xy$', r'$-yz$', r'$-xz$'
], [r'$x$', r'$x^3$', r'$xy^2$', r'$xz^2$', r'$-x^2y$', r'$-xyz$', r'$-x^2z$'],
[
r'$y$', r'$x^2y$', r'$y^3$', r'$yz^2$', r'$-xy^2$',
r'$-y^2z$', r'$-xyz$'
],
[
r'$z$', r'$x^2z$', r'$y^2z$', r'$z^3$', r'$-xyz$',
r'$-yz^2$', r'$-xz^2$'
]])
va = VisualArray(arr)
blue = [(0, i, 0) for i in range(1, 4)] + [(0, 0, i) for i in range(1, 7)]
lime = [(0, 1, 1), (0, 2, 2), (0, 3, 3), (0, 1, -2), (0, 2, -1), (0, 3, -3)]
va.set_colors(zip(*blue), color='lightblue', basecolor='white')
va.set_colors(zip(*lime), color='lime')
va.set_colors(zip(*[(0, 2, -2), (0, -1, 2)]), color='#ffff00')
va.set_colors(zip(*[(0, 1, 2), (0, 2, 4)]), color='#dddd00')
va.set_colors(zip(*[(0, 1, 3), (0, -1, -1)]), color='#bbbb00')
va.set_colors(zip(*[(0, 1, 4), (0, 2, 1)]), color='#999900')
va.set_colors(zip(*[(0, 1, 6), (0, -1, 1)]), color='#777700')
va.set_colors(zip(*[(0, 2, 3), (0, -1, -2)]), color='#555500')
va.vizualize(fixview=True,
axis_labels=[
None, '$x+y+z$', r'$' + r'\!' * 35 + r' x^2+y^2+z^2-xy-yz-zx$'
],
scale=0.4)
va.ax.set_title(
'Why $(x+y+z)(x^2+y^2+z^2-xy-yz-zx) = x^3+y^3+z^3-3xyz$? \n Simplify monochromatic pairs of yellow cubes!'
)
import matplotlib.pyplot as plt
from numpyviz import VisualArray
fig = plt.figure()
arr = np.array([[[r'$x^3y^2$', r'$x^2y^3$'], [r'$x^2y^3$', r'$xy^4$']],
[[r'$x^2y^3$', r'$xy^4$'], [r'$xy^4$', r'$y^5$']],
[[r'$x^4y$', r'$x^3y^2$'], [r'$x^3y^2$', r'$x^2y^3$']],
[[r'$x^3y^2$', r'$x^2y^3$'], [r'$x^2y^3$', r'$xy^4$']],
[[r'$x^4y$', r'$x^3y^2$'], [r'$x^3y^2$', r'$x^2y^3$']],
[[r'$x^3y^2$', r'$x^2y^3$'], [r'$x^2y^3$', r'$xy^4$']],
[[r'$x^5$', r'$x^4y$'], [r'$x^4y$', r'$x^3y^2$']],
[[r'$x^4y$', r'$x^3y^2$'], [r'$x^3y^2$', r'$x^2y^3$']]])
ax = fig.add_subplot(1, 2, 1, projection='3d')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(np.where(arr == '$x^5$'), color='#6666ff')
va.set_colors(np.where(arr == '$x^4y$'), color='#66ff66')
va.set_colors(np.where(arr == '$x^3y^2$'), color='#ff6666')
va.set_colors(np.where(arr == '$x^2y^3$'), color='#ffff66')
va.set_colors(np.where(arr == '$xy^4$'), color='#ff66ff')
va.set_colors(np.where(arr == '$y^5$'), color='#66ffff')
va.permute(shape=(2, 2, 2, 2, 2))
va.vizualize(
fixview=True,
axis_labels=[
r'$\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!' + 'x(x+y)\!\!+\!\!y(x+y)$',
r'$\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!' + 'x(x+y)\!\!+\!\!y(x+y)$',
r'$\!\!x+y$'
],
scale=0.6)
va.ax.set_title(
import numpy as np import matplotlib.pyplot as plt from numpyviz import VisualArray arr = np.arange(64).reshape((1, 8, 8)) va = VisualArray(arr) cells = va.get_indices_chequerwise(window=(1, 1, 1)) va.set_colors(cells.T, color='white', basecolor='grey') va.vizualize(fixview=True, axis_labels=(None, None, None)) va.ax.dist = 12.5 #zoom out a little plt.show()
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
import matplotlib.gridspec as gridspec
arr = np.random.randint(99, size=24).reshape((3, 4, 2))
fig = plt.figure(constrained_layout=True)
spec = gridspec.GridSpec(ncols=5, nrows=1, figure=fig)
ax = fig.add_subplot(spec[0], projection='3d')
ax.set_title(f'body of shape={arr.shape}')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(va.get_indices().T, color='lawngreen', basecolor='aqua')
va.mix_colors(va.get_indices_chequerwise((1, 1, arr.shape[2])).T, 'black')
va.vizualize(fixview=True, axis_labels=('axis=0', 'axis=1', 'axis=2'))
ax = fig.add_subplot(spec[1:], projection='3d')
ax.set_title(f'body of shape={arr.flatten().shape}')
va2 = VisualArray(va.arr.flatten(), fig=fig, ax=ax)
va2.set_colors(va2.get_indices().T, color='lawngreen', basecolor='aqua')
va2.mix_colors(va2.get_indices_chequerwise((1, 1, arr.shape[2])).T, 'black')
va2.vizualize(fixview=True, axis_labels=(None, None, 'axis=0'))
ax.dist = 8
plt.get_current_fig_manager().window.state('zoomed')
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
arr = np.array([[11, 12, 13, 14, 15, 16], [21, 22, 23, 24, 25, 26],
[31, 32, 33, 34, 35, 36], [41, 42, 43, 44, 45, 46]])
a = arr.copy()
fig = plt.figure()
ax = fig.add_subplot(2, 3, 1, projection='3d')
va = VisualArray(arr, fig=fig, ax=ax)
coords = va.get_indices()
va.set_colors(coords.T, color='yellow', basecolor='lightblue')
va.vizualize(fixview=True, axis_labels=(None, 'axis=0', 'axis=1'))
va.ax.set_title('arr = array of shape (4,6)')
va.ax.dist = 12.5
arr = a.reshape((4, 3, 2))
ax = fig.add_subplot(2, 3, 2, projection='3d')
va = VisualArray(arr, fig=fig, ax=ax)
coords = va.get_indices()
va.set_colors(coords[coords[:, 1] == 1].T,
color='lightgreen',
basecolor='lightblue')
va.set_colors(coords[coords[:, 1] == 2].T,
color='thistle',
basecolor='lightblue')
va.vizualize(fixview=True)
va.ax.set_title('arr1 = array of shape (4, 3, 2)')
va.ax.dist = 12.5
"""this is an example that demonstrates how to multiply three polynomials"""
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
arr = np.array([[[r'$x^2y$', r'$xy^2$'], [r'$xy^2$', r'$y^3$']],
[[r'$x^3$', r'$x^2y$'], [r'$x^2y$', r'$xy^2$']]])
va = VisualArray(arr)
va.set_colors(np.where(arr == '$y^3$'), color='#6666ff')
va.set_colors(np.where(arr == '$x^3$'), color='#ff66ff')
va.set_colors(np.where(arr == '$x^2y$'), color='#66ff66')
va.set_colors(np.where(arr == '$xy^3$'), color='#66ffff')
va.vizualize(fixview=False, axis_labels=['$x+y$', '$x+y$', '$x+y$'], scale=0.7)
va.ax.set_title('Why $(x+y)^3 = x^3+3x^2y+3xy^2+y^3$?')
plt.show()
"""this example demonstrates how to make a multiple
subplots of a VisualArray in multiple sides"""
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
arr = np.array([[[1, 2, 13], [12, 2, 32], [61, 2, 6], [1, 23, 3], [1, 21, 3],
[91, 2, 38]]])
fig = plt.figure()
ax = fig.add_subplot(1, 3, 1, projection='3d')
ax.set_title('a = array of shape (1, 6, 3)')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(np.array(list(np.ndindex(arr.shape))).T,
color='yellow',
basecolor='lightblue')
va.vizualize(fixview=True)
arr = arr[:, :, :2]
ax = fig.add_subplot(1, 3, 2, projection='3d')
ax.set_title('a = a[:,:,:2] \n' 'a is of shape (1, 6, 2) now')
va = VisualArray(arr, fig=fig, ax=ax)
va.set_colors(np.array(list(np.ndindex(arr.shape))).T,
color='yellow',
basecolor='lightblue')
va.vizualize(fixview=True)
arr = arr.squeeze()
ax = fig.add_subplot(1, 3, 3, projection='3d')
ax.set_title('a = a.squeeze() \n' 'a is of shape (6, 2) now')
form[-len(c):] = list(c)
return ''.join(form)
arr = np.asarray(arr, dtype='uint32')
hexarr = np.vectorize(tohexarr)
return hexarr((arr[:, :, 0] << 16) + (arr[:, :, 1] << 8) + arr[:, :, 2])
from PIL import Image
test_image = Image.open('cat.jpg')
test_image = test_image.resize((32, 32), Image.ANTIALIAS)
test_image = np.array(test_image).astype(int)
t = time()
va = VisualArray(test_image)
coords = va.get_indices()
eye = np.eye(3, dtype=int)
#input of set_colors can be another array of len(cellsT)
for i in range(3):
color = np.expand_dims(test_image[:, :, i], axis=2) * eye[i]
cellsT = coords[coords[:, 2] == i].T #list of coords where z = i
va.set_colors(cellsT, color=tohex(color)[cellsT[0], cellsT[1]])
va.vizualize(fixview=True, scale=0.7, axis_labels=(None, None, None))
va.ax.azim = 40 #change to 40 to see another back side
va.ax.elev = 20
va.ax.dist = 8 #zoom in a little
print(time() - t)
plt.get_current_fig_manager().window.state('zoomed')
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
def argmin_axis2(arr):
a3 = np.argmin(arr, axis=2)
print(a3.__repr__())
a1, a2 = np.indices((arr.shape[0], arr.shape[1]))
x, y, z = zip(*np.broadcast(a1, a2, a3))
return x, y, z
arr = np.random.randint(99, size=8 * 8 * 3).reshape((8, 8, 3))
va = VisualArray(arr)
va.set_colors(argmin_axis2(arr), color='yellow', basecolor='lightblue')
va.vizualize(fixview=True)
va.ax.set_title('argmin on axis=-1')
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
arr = np.random.randint(99, size=96).reshape((1, 8, 12))
w = (2, 4)
fig = plt.figure()
ax = fig.add_subplot(1, 3, 1, projection='3d')
ax.set_title('image')
va = VisualArray(arr, fig=fig, ax=ax) #indices of every cell
cells = va.get_indices_chequerwise(window=(1, ) + w)
va.set_colors(cells.T, color='lawngreen', basecolor='aqua')
va.vizualize(fixview=True, axis_labels=(None, 'axis=1', 'axis=0'))
ax = fig.add_subplot(1, 3, 2, projection='3d')
va2 = VisualArray(va.arr, va.colors, fig=fig, ax=ax) #shape: (1, 8, 12)
shape = (va2.arr.shape[1] // w[0], w[0], va2.arr.shape[2] // w[1], w[1])
ax.set_title(f'image.reshape{shape}')
va2.reshape(shape) #shape: (4, 2, 3, 4)
new_arr, new_colors = va2.arr.copy(), va2.colors.copy()
va2.permute(shape)
va2.vizualize(fixview=True, axis_labels=('axis=0', 'axis=1', 'axis=2'))
def argmin(arr):
#bug...
a2 = arr.argmin(axis=1)
a4 = arr.argmin(axis=3)
a1, a3 = np.indices((arr.shape[0], arr.shape[2]))
x, y, z, t = zip(*np.broadcast(a1, a2, a3, a4))
import numpy as np
import matplotlib.pyplot as plt
from numpyviz import VisualArray
a = np.array([[1, 2, 3], [3, 4, 5]])
b = np.array([[[1, 0, 1], [1, 1, 0], [0, 1, 1]],
[[1, 1, 1], [0, 1, 0], [0, 0, 1]]])
c = np.array([1, 2, 3])
fig = plt.figure()
ax = fig.add_subplot(2, 3, 1, projection='3d')
va1 = VisualArray(a[:, None, :], fig=fig, ax=ax)
va1.ax.set_title(f'a[:,None,:] of shape=(2, 1, 3)')
va1.set_colors(va1.get_indices().T, color='lightgreen', basecolor='aqua')
va1.vizualize(fixview=True, usetex=False, scale=1.2)
va1.ax.dist = 12
ax = fig.add_subplot(2, 3, 2, projection='3d')
va2 = VisualArray(b, fig=fig, ax=ax)
va2.ax.set_title(f'b of shape=(2, 3, 3)')
va2.set_colors(va2.get_indices().T, color='lightgreen', basecolor='aqua')
va2.vizualize(fixview=True, usetex=False, scale=1.2)
va2.ax.dist = 12
ax = fig.add_subplot(2, 3, 3, projection='3d')
va3 = VisualArray(c, fig=fig, ax=ax)
va3.ax.set_title(f'c of shape=(3,)')
va3.set_colors(va3.get_indices().T, color='lightgreen', basecolor='aqua')
va3.vizualize(fixview=True,
[0., 0., 0., 4., 0., 0., 0., 4., 0., 0., 0., 4.],
[1., 0., 3., 0., 1., 0., 4., 0., 1., 0., 5., 0.],
[0., 2., 0., 0., 0., 2., 0., 0., 0., 2., 0., 0.],
[0., 0., 3., 0., 0., 0., 3., 0., 0., 0., 3., 0.],
[0., 0., 0., 4., 0., 0., 0., 4., 0., 0., 0., 4.],
[1., 0., 6., 0., 1., 0., 7., 0., 1., 0., 8., 0.],
[0., 2., 0., 0., 0., 2., 0., 0., 0., 2., 0., 0.],
[0., 0., 3., 0., 0., 0., 3., 0., 0., 0., 3., 0.],
[0., 0., 0., 4., 0., 0., 0., 4., 0., 0., 0., 4.]]).reshape(
(1, 12, 12)).astype(int)
fig = plt.figure()
ax = fig.add_subplot(2, 3, 1, projection='3d')
va1 = VisualArray(arr, fig=fig, ax=ax)
va1.ax.set_title(f'input')
va1.set_colors(va1.get_indices().T, color='lightgreen', basecolor='aqua')
va1.vizualize(fixview=True,
axis_labels=(None, 'axis=0', 'axis=1'),
usetex=False,
scale=1.2)
va1.ax.dist = 12
va1.azim, va1.elev = -90, 45
ax = fig.add_subplot(2, 3, 2, projection='3d')
va2 = VisualArray(arr, fig=fig, ax=ax)
va2.ax.set_title(f'input <-> input.reshape((4, 3, 4, 3))')
w = (3, 3)
shape = (arr.shape[1] // w[0], w[0], arr.shape[2] // w[1], w[1])
print(shape)
va2.set_colors(va2.get_indices().T, color='lightgreen', basecolor='aqua')
va2.permute(shape)
arr = np.asarray(arr, dtype='uint32')
hexarr = np.vectorize(tohexarr)
return hexarr((arr[:, :, 0] << 16) + (arr[:, :, 1] << 8) + arr[:, :, 2])
def tolabels(arr):
def tolabelarr(x):
return r'\begin{array}{l}\,\,\sharp ' + x[1:4] + r'\\ \,\,\,\, ' + x[
4:7] + r'\\ ' + r'\\ ' + r'\\ ' + r'\end{array}'
labelarr = np.vectorize(tolabelarr)
return labelarr(arr)
from PIL import Image
test_image = Image.open('cat.jpg')
test_image = test_image.resize((32, 32), Image.ANTIALIAS)
test_image = np.array(test_image).astype(int)
arr = tohex(test_image)
va = VisualArray(arr)
cells = va.get_indices()
x, y, z = cells.T
va.set_colors(cells.T, color=va.arr[x, y, z])
va.arr = tolabels(va.arr)
va.vizualize(fixview=True, scale=0.35, axis_labels=(None, None, None))
va.ax.dist = 11.5 #zoom out a little; change to 3.5 for higher zoom
plt.get_current_fig_manager().window.state('zoomed')
plt.show()