# How to scale the voxel-dimensions with Matplotlib?

These chains of operations are easy to set up using Nilearn and Scipy Python libraries, Here we give clear guidelines about these steps, starting with pre-image operations to post-image operations

# cut in x - direction sagittal = -25 # cut in y - direction coronal = -37 # cut in z - direction axial = -6 # coordinates displaying should be prepared as a list cut_coords = [sagittal, coronal, axial]

The following example is a complete program that illustrates some of the basic steps to create grids and write them to disk: , copyToArray has no tolerance argument, because there is no distinction between active and inactive values in the destination array,,Also available if the OpenVDB Python module is compiled with NumPy support (see above) are grid methods to convert polygonal meshes to level sets (see tools::meshToLevelSet for some restrictions) and to convert isosurfaces of scalar-valued grids to meshes

PY_OPENVDB_WRAP_ALL_GRID_TYPES

PY_OPENVDB_WRAP_ALL_GRID_TYPES

.vdb

A 3D ndarray of color names, with each item the color for the corresponding voxel, The size must match the voxels

lowerBound < upperBound

Scaling (zooming) in three dimensions can be represented by a diagonal 3 by 3 matrix, Here’s how to zoom the first dimension by \(p\), the second by \(q\) and the third by \(r\) units:,The voxel coordinate of the center voxel of the anatomical image is:,What is the voxel coordinate in the anatomical corresponding to the voxel center of the EPI image?,This brings the affine-transformed voxel coordinates to the red box on the figure, matching the position on the localizer

```
>>>
import nibabel as nib
>>>
epi_img = nib.load('downloads/someones_epi.nii.gz') >>>
epi_img_data = epi_img.get_fdata() >>>
epi_img_data.shape(53, 61, 33)
```

Want to scale the voxel-dimensions with Matplotlib, How can I do this?, Stack Overflow Public questions & answers , Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers ,Instead the voxel on position (1,0,4)

import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = fig.gca(projection = '3d') # Make grid test2 = np.zeros((6, 6, 6)) # Activate single Voxel test2[1, 0, 4] = True # Custom coordinates for grid x, y, z = np.indices((7, 7, 7)) / 2 # Pass the custom coordinates as extra arguments ax.voxels(x, y, z, test2, edgecolor = "k") ax.set_xlabel('0 - Dim') ax.set_ylabel('1 - Dim') ax.set_zlabel('2 - Dim') plt.show()

Demonstrates using the x, y, z parameters of Axes3D,voxels

```
import matplotlib.pyplot as plt
import matplotlib.colors
import numpy as np
def midpoints(x):
sl = ()
for i in range(x.ndim):
x = (x[sl + np.index_exp[: -1]] + x[sl + np.index_exp[1: ]]) / 2.0
sl += np.index_exp[: ]
return x
# prepare some coordinates, and attach rgb values to each
r, theta, z = np.mgrid[0: 1: 11 j, 0: np.pi * 2: 25 j, -0.5: 0.5: 11 j]
x = r * np.cos(theta)
y = r * np.sin(theta)
rc, thetac, zc = midpoints(r), midpoints(theta), midpoints(z)
# define a wobbly torus about[0.7, *, 0]
sphere = (rc - 0.7) ** 2 + (zc + 0.2 * np.cos(thetac * 2)) ** 2 < 0.2 ** 2
# combine the color components
hsv = np.zeros(sphere.shape + (3, ))
hsv[..., 0] = thetac / (np.pi * 2)
hsv[..., 1] = rc
hsv[..., 2] = zc + 0.5
colors = matplotlib.colors.hsv_to_rgb(hsv)
# and plot everything
ax = plt.figure().add_subplot(projection = '3d')
ax.voxels(x, y, z, sphere,
facecolors = colors,
edgecolors = np.clip(2 * colors - 0.5, 0, 1), # brighter linewidth = 0.5)
plt.show()
```

To place the voxels at different positions, see How to scale the voxel-dimensions with Matplotlib?, ,The upcomming matplotlib version 2

```
from mpl_toolkits.mplot3d
import Axes3D
import numpy as np
import matplotlib.pyplot as plt
N1 = 10
N2 = 10
N3 = 10
ma = np.random.choice([0, 1], size = (N1, N2, N3), p = [0.99, 0.01])
fig = plt.figure()
ax = fig.gca(projection = '3d')
ax.set_aspect('equal')
ax.voxels(ma, edgecolor = "k")
plt.show()
```

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