Metadata-Version: 2.1
Name: python2latex
Version: 0.1.7
Summary: A Python to LaTeX converter
Home-page: https://github.com/jsleb333/python2latex
Author: Jean-Samuel Leboeuf
Author-email: jean-samuel.leboeuf.1@ulaval.ca
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy

# Python2LaTeX: The Python to LaTeX converter

Did you ever feel overwhelmed by the cumbersomeness of LaTeX to produce quality tables and figures? Fear no more, Python2LaTeX is here! Produce perfect tables automatically and easily, create figures and plots that integrates seamlessly into your tex file, or even write your complete article directly from Python! All that effortlessly (or almost) with Python2LaTeX.

## Prerequisites

The package makes use of numpy and assumes a distribution of LaTeX that uses ``pdflatex`` is installed on your computer. Some LaTeX packages are used, such as ``booktabs``, ``tikz``, ``pgfplots`` and ``pgfplotstable``. Your LaTeX distribution should inform you if such package needs to be installed.

## Installation

To install the package, simply run in your terminal the command

    pip install python2latex

## Examples

### Create a simple document

The following example shows how to create a document with a single section and some text.
```python
from python2latex import Document

doc = Document(filename='simple_document_example', filepath='./examples/simple document example', doc_type='article', options=('12pt',))
doc.set_margins(top='3cm', bottom='3cm', margins='2cm')
sec = doc.new_section('Spam and Egg', label='spam_egg')
sec.add_text('The Monty Python slays the Spam and eats the Egg.')

tex = doc.build() # Builds to tex and compile to pdf
print(tex) # Prints the tex string that generated the pdf
```

<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/simple%20document%20example/simple_document_example.jpg" alt="Simple document">
</p>
</details>


### Create a table from a numpy array

This example shows how to generate automatically a table from data taken directly from a numpy array. The module allows to add merged cells easily, to add rules where you want and even to highlight the best value automatically inside a specified area! To ease these operations, the the square brackets ('getitem') operator have been repurposed to select an area of the table instead of returning the actual values contained in the table. Once an area is selected, use the 'multicell', 'add_rule' or 'highlight_best' methods. To get the actual values inside the table, one can use the 'data' attribute of the table.
```python
from python2latex import Document, Table, build
import numpy as np

doc = Document(filename='table_from_numpy_array_example', filepath='examples/table from numpy array example', doc_type='article', options=('12pt',))

sec = doc.new_section('Testing tables from numpy array')
sec.add_text("This section tests tables from numpy array.")

col, row = 6, 4
data = np.random.rand(row, col)

table = sec.new(Table(shape=(row+2, col+1), alignment='c', float_format='.2f'))
# Set a caption if desired
table.caption = 'Table from numpy array'
# Set entries with a slice directly from a numpy array!
table[2:,1:] = data

# Set a columns title as a multicell with custom parameters
table[0,1:4].multicell('Title1', h_align='c')
table[0,4:].multicell('Title2', h_align='c')
# Set subtitles as easily
table[1,1:] = [f'Col{i+1}' for i in range(col)]
# Set a subtitle on two lines if it is too long
table[1,-1:].divide_cell(shape=(2,1), alignment='c')[:] = [['Longer'],['Title']]

# Or simply create a new subtable as an entry
subtable = Table(shape=(2,1), as_float_env=False, bottom_rule=False, top_rule=False)
subtable[:,0] = ['From', 'Numpy']

# Chain multiple methods on the same area for easy combinations of operations
table[2:,0].multicell(subtable, v_align='*', v_shift='0pt').highlight('italic')
# Set multicell areas with a slice too
table[3:5,2:4] = 'Array' # The value is stored in the top left cell (here it would be cell (2,2))

# Add rules where you want, as you want
table[1,1:4].add_rule(trim_left=True, trim_right='.3em')
table[1,4:].add_rule(trim_left='.3em', trim_right=True)

# Automatically highlight the best value(s) inside the specified slice, ignoring text
for row in range(2,6):
    table[row,4:].highlight_best('low', 'italic') # Best per row, for the last 3 columns
# Highlights equal or near equal values too!
table[5,1] = 1.0
table[5,2] = 0.996
table[5].highlight_best('high', 'bold') # Whole row 4

tex = doc.build()
print(tex)
```
<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/table%20from%20numpy%20array%20example/table_from_numpy_array_example.jpg" alt="Table from numpy result">
</p>
</details>



### Create a simple plot
You can plot curves as easily as with `matplotlib.pyplot.plot` with the `Plot` environement that compiles it directly into pdf! This is a wrapper around the `pgfplots` and `pgfplotstable` LaTeX packages.
```python
from python2latex import Document, Plot
import numpy as np

# Document type 'standalone' will only show the plot, but does not support all tex environments.
filepath = './examples/simple plot example/'
filename = 'simple_plot_example'
doc = Document(filename, doc_type='standalone', filepath=filepath)

# Create the data
X = np.linspace(0,2*np.pi,100)
Y1 = np.sin(X)
Y2 = np.cos(X)

# Create a plot
plot = doc.new(Plot(X, Y1, X, Y2, plot_path=filepath, as_float_env=False))

tex = doc.build()
```
<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/simple%20plot%20example/simple_plot_example.jpg" alt="Simple plot result">
</p>
</details>


### Create a more complex plot
You can make more complex plots with the options shown in this example.
```python
from python2latex import Document, Plot
import numpy as np

# Create the document
filepath = './examples/more complex plot example/'
filename = 'more_complex_plot_example'
doc = Document(filename, doc_type='article', filepath=filepath)
sec = doc.new_section('More complex plot')
sec.add_text('This section shows how to make a more complex plot integrated directly into a tex file.')

# Create the data
X = np.linspace(0,2*np.pi,100)
Y1 = np.sin(X)
Y2 = np.cos(X)

# Create a plot
plot = sec.new(Plot(plot_name=filename, plot_path=filepath))
plot.caption = 'More complex plot'

plot.add_plot(X, Y1, 'blue', 'dashed', legend='sine') # Add colors and legend to the plot
plot.add_plot(X, Y2, 'orange', line_width='3pt', legend='cosine')
plot.legend_position = 'south east' # Place the legend where you want

# Add a label to each axis
plot.x_label = 'Radians'
plot.y_label = 'Projection'

# Choose the limits of the axis
plot.x_min = 0
plot.y_min = -1

# Choose the positions of the ticks on the axes
plot.x_ticks = np.linspace(0,2*np.pi,5)
plot.y_ticks = np.linspace(-1,1,9)
# Choose the displayed text for the ticks
plot.x_ticks_labels = r'0', r'$\frac{\pi}{2}$', r'$\pi$', r'$\frac{3\pi}{2}$', r'$2\pi$'

# Use the tex environment 'axis' keyword options to use unimplemented features if needed.
plot.axis.kwoptions['y tick label style'] = '{/pgf/number format/fixed zerofill}' # This makes all numbers with the same number of 0 (fills if necessary).

tex = doc.build()
```
<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/more%20complex%20plot%20example/more_complex_plot_example.jpg" alt="More complex plot result">
</p>
</details>

### Create an unsupported environment
If some environment is not currently supported, you can create one from the TexEnvironment base class.
```python
from python2latex import Document, TexEnvironment

doc = Document(filename='unsupported_env_example', doc_type='article', filepath='examples/unsupported env example', options=('12pt',))

sec = doc.new_section('Unsupported env')
sec.add_text("This section shows how to create unsupported env if needed.")

sec.add_package('amsmath') # Add needed packages in any TexEnvironment, at any level
align = sec.new(TexEnvironment('align', label='align_label'))
align.add_text(r"""e^{i\pi} &= \cos \pi + i \sin \pi\\
         &= -1""") # Use raw strings to alleviate tex writing

tex = doc.build()
print(tex)
```
<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/unsupported%20env%20example/unsupported_env_example.jpg" alt="Unsupported environment result">
</p>
</details>


### Binding objects to environments
To alleviate syntax, it is possible to bind TexObject classes to an instance of a TexEnvironment. This creates an alternative class that automatically append any new instance of the class to the environment.
```python
from python2latex import Document, Section, Subsection, TexEnvironment

doc = Document(filename='binding_objects_to_environments_example', filepath='./examples/binding objects to environments example', doc_type='article', options=('12pt',))
section = doc.bind(Section) # section is now a new class that creates Section instances that are automatically appended to 'doc'

sec1 = section('Section 1', label='sec1') # Equivalent to: sec1 = doc.new(Section('Section 1', label='sec1'))
sec1.add_text("All sections created with ``section'' will be automatically appended to the document body!")

subsection, texEnv = sec1.bind(Subsection, TexEnvironment) # 'bind' supports multiple classes in the same call
eq1 = texEnv('equation')
eq1.add_text(r'e^{i\pi} = -1')

eq2 = texEnv('equation')
eq2 += r'\sum_{n=1}^{\infty} n = -\frac{1}{12}' # The += operator calls is the same as 'add_text'

sub1 = subsection('Subsection 1 of section 1')
sub1 += 'Text of subsection 1 of section 1.'

sec2 = section('Section 2', label='sec2')
sec2 += "sec2 is also appended to the document after sec1."

tex = doc.build() # Builds to tex and compile to pdf
print(tex) # Prints the tex string that generated the pdf
```
<details>
<summary>
<i> Click to unfold result </i>
</summary>
<p>
<img src="https://github.com/jsleb333/python2latex/blob/master/examples/binding%20objects%20to%20environments%20example/binding_objects_to_environments_example.jpg" alt="Binding objects to environments result">
</p>
</details>


## How it works

This LaTeX wrapper is based on the TexEnvironment class. Each such environment possesses a body attribute consisting in a list of strings and of other TexEnvironments. The 'build' method then converts every TexEnvironment to a tex string recursively. This step makes sure every environment is properly between a '\begin{env}' and a '\end{env}'. Converting the document to a string only at the end allows to do operation in the order desired, hence providing flexibility. The 'build' method can be called on any TexEnvironment, return the tex string representation of the environment. However, only the Document class 'build' method will also compile it to an actual pdf.


