<jupyter_start><jupyter_text>Some text Some more test with mathematics $a = b$ and more:$$b = cc = \vec{v}$$Yet more text<jupyter_code>import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
a = 2
b = a
b * a
for i in range(3):
    c = a * i
c
plt.plot(range(10))
plt.plot(range(10))
plt.imshow(np.arange(12).reshape((3, 4)))
# Code that prints stuff with end result
print('one')
print('two')
3
# Code that prints stuff without end result
print('hello, again')
def xyz_trans_vol(vol, x_y_z_trans):
    """ Make a new copy of `vol` translated by `x_y_z_trans` voxels

    x_y_z_trans is a sequence or array length 3, containing the (x, y, z) translations in voxels.
       
    Values in `x_y_z_trans` can be positive or negative, and can be floats.
    """
    x_y_z_trans = np.array(x_y_z_trans)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11666666666666667, 'fraction_numerical': 0.014285714285714285, 'mean_word_length': 4.25625, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '379440', 'license': 'BSD-2-Clause', 'n_tokens_mistral': 332, 'n_tokens_neox': 312, 'n_words': 104, 'path': 'nb2plots/tests/data/small.ipynb', 'repo_name': 'jonathan-taylor/nb2plots', 'size': '840'}