Printing functions

Advanced printing functions.

display_colums

 display_colums (display_list, num_col=3)

a = [torch.rand((3, 3))]*3
a

[tensor([[0.6266, 0.3672, 0.3988],
         [0.6061, 0.2596, 0.4855],
         [0.3177, 0.8166, 0.3100]]),
 tensor([[0.6266, 0.3672, 0.3988],
         [0.6061, 0.2596, 0.4855],
         [0.3177, 0.8166, 0.3100]]),
 tensor([[0.6266, 0.3672, 0.3988],
         [0.6061, 0.2596, 0.4855],
         [0.3177, 0.8166, 0.3100]])]

v.s.

display_colums(a) # works only in notebook

source

ndarray_to_latex

 ndarray_to_latex (arr)

Returns a LaTeX {pmatrix*}[r] as a string

source

tensor_to_latex

 tensor_to_latex (tensor)

Returns a LaTeX {pmatrix*}[r] as a string

tex = tensor_to_latex(torch.full((3,3), 2))
print(tex)

\begin{pmatrix*}[r]
  2 & 2 & 2\\
  2 & 2 & 2\\
  2 & 2 & 2\\
\end{pmatrix*}

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print_markdown

 print_markdown (text, print_raw=False)

print_markdown("$\sqrt{2}$, *Test text*")

\(\sqrt{2}\), Test text

print_markdown(f"${tex}$")

\(\begin{pmatrix*}[r] 2 & 2 & 2\\ 2 & 2 & 2\\ 2 & 2 & 2\\ \end{pmatrix*}\)

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print_table

 print_table (col_headings:list, data:<built-infunctionarray>,
              row_headings=None, print_raw=False)

Print a table:

h = ["head1", "head2", "head3"]
r = ["sample", "dataset"]
d = np.random.rand(2, 3)
print_table(h, d, r)

	head1	head2	head3
sample	0.32	0.23	0.27
dataset	0.74	0.41	0.00