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Plot in the terminal using braille dots.

Project description

Plotille

CircleCI Coverage Status Language grade: Python Tested CPython Versions Tested PyPy Versions PyPi version PyPi license

Plot, scatter plots and histograms in the terminal using braille dots, with (almost) no dependancies. Plot with color or make complex figures - similar to a very small sibling to matplotlib. Or use the canvas to plot dots and lines yourself.

Install:

pip install plotille

Similar to other libraries:

  • like drawille, but focused on graphing – plus X/Y-axis.
  • like termplot, but with braille (finer dots), left to right histogram and linear interpolation for plotting function.
  • like termgraph (not on pypi), but very different style.
  • like terminalplot, but with braille, X/Y-axis, histogram, linear interpolation.

Basic support for timeseries plotting is provided with release 3.2: for any X or Y values you can also add datetime.datetime, pendulum.datetime or numpy.datetime64 values. Labels are generated respecting the difference of x_limits and y_limits.

Documentation

In [1]: import plotille
In [2]: import numpy as np
In [3]: X = np.sort(np.random.normal(size=1000))

Figure

To construct plots the recomended way is to use a Figure:

In [12]: plotille.Figure?
Init signature: plotille.Figure()
Docstring:
Figure class to compose multiple plots.

Within a Figure you can easily compose many plots, assign labels to plots
and define the properties of the underlying Canvas. Possible properties that
can be defined are:

    width, height: int    Define the number of characters in X / Y direction
                          which are used for plotting.
    x_limits: float       Define the X limits of the reference coordinate system,
                          that will be plottered.
    y_limits: float       Define the Y limits of the reference coordinate system,
                          that will be plottered.
    color_mode: str       Define the used color mode. See `plotille.color()`.
    with_colors: bool     Define, whether to use colors at all.
    background: multiple  Define the background color.
    x_label, y_label: str Define the X / Y axis label.

Basically, you create a Figure, define the properties and add your plots. Using the show() function, the Figure generates the plot using a new canvas:

In [13] fig = plotille.Figure()
In [14] fig.width = 60
In [15] fig.height = 30
In [16] fig.set_x_limits(min_=-3, max_=3)
In [17] fig.set_y_limits(min_=-1, max_=1)
In [18] fig.color_mode = 'byte'
In [19] fig.plot([-0.5, 1], [-1, 1], lc=25, label='First line')
In [20] fig.scatter(X, np.sin(X), lc=100, label='sin')
In [21] fig.plot(X, (X+2)**2 , lc=200, label='square')
In [22] print(fig.show(legend=True))

The available plotting functions are:

# create a plot with linear interpolation between points
Figure.plot(self, X, Y, lc=None, interp='linear', label=None)
# create a scatter plot with no interpolation between points
Figure.scatter(self, X, Y, lc=None, label=None)
# create a histogram over X
Figure.histogram(self, X, bins=160, lc=None)

Other interesting functions are:

# remove all plots from the figure
Figure.clear(self)
# Create a canvas, plot the registered plots and return the string for displaying the plot
Figure.show(self, legend=False)

Graphing:

There are some utility functions for fast graphing of single plots.

Plot:

In [4]: plotille.plot?
Signature: plotille.plot(X, Y, width=80, height=40, X_label='X', Y_label='Y', linesep='\n', interp='linear', x_min=None, x_max=None, y_min=None, y_max=None, lc=None, bg=None, color_mode='names')
Docstring:
Create plot with X , Y values and linear interpolation between points

Parameters:
    X: List[float]         X values.
    Y: List[float]         Y values. X and Y must have the same number of entries.
    width: int             The number of characters for the width (columns) of the canvas.
    hight: int             The number of characters for the hight (rows) of the canvas.
    X_label: str           Label for X-axis.
    Y_label: str           Label for Y-axis. max 8 characters.
    linesep: str           The requested line seperator. default: os.linesep
    interp: Optional[str]  Specify interpolation; values None, 'linear'
    x_min, x_max: float    Limits for the displayed X values.
    y_min, y_max: float    Limits for the displayed Y values.
    lc: multiple           Give the line color.
    bg: multiple           Give the background color.
    color_mode: str        Specify color input mode; 'names' (default), 'byte' or 'rgb'
                           see plotille.color.__docs__

Returns:
    str: plot over `X`, `Y`.

In [5]: print(plotille.plot(X, np.sin(X), height=30, width=60))

Scatter:

In [6]: plotille.scatter?
Signature: plotille.scatter(X, Y, width=80, height=40, X_label='X', Y_label='Y', linesep='\n', x_min=None, x_max=None, y_min=None, y_max=None, lc=None, bg=None, color_mode='names')
Docstring:
Create scatter plot with X , Y values

Basically plotting without interpolation:
    `plot(X, Y, ... , interp=None)`

Parameters:
    X: List[float]       X values.
    Y: List[float]       Y values. X and Y must have the same number of entries.
    width: int           The number of characters for the width (columns) of the canvas.
    hight: int           The number of characters for the hight (rows) of the canvas.
    X_label: str         Label for X-axis.
    Y_label: str         Label for Y-axis. max 8 characters.
    linesep: str         The requested line seperator. default: os.linesep
    x_min, x_max: float  Limits for the displayed X values.
    y_min, y_max: float  Limits for the displayed Y values.
    lc: multiple         Give the line color.
    bg: multiple         Give the background color.
    color_mode: str      Specify color input mode; 'names' (default), 'byte' or 'rgb'
                         see plotille.color.__docs__

Returns:
    str: scatter plot over `X`, `Y`.

In [7]: print(plotille.scatter(X, np.sin(X), height=30, width=60))

Hist:

Inspired by crappyhist.

In [8]: plotille.hist?
Signature: plotille.hist(X, bins=40, width=80, log_scale=False, linesep='\n', lc=None, bg=None, color_mode='names')
Docstring:
Create histogram over `X` from left to right

The values on the left are the center of the bucket, i.e. `(bin[i] + bin[i+1]) / 2`.
The values on the right are the total counts of this bucket.

Parameters:
    X: List[float]  The items to count over.
    bins: int       The number of bins to put X entries in (rows).
    width: int      The number of characters for the width (columns).
    log_scale: bool Scale the histogram with `log` function.
    linesep: str    The requested line seperator. default: os.linesep
    lc: multiple         Give the line color.
    bg: multiple         Give the background color.
    color_mode: str      Specify color input mode; 'names' (default), 'byte' or 'rgb'
                         see plotille.color.__docs__

Returns:
    str: histogram over `X` from left to right.

In [9]: print(plotille.hist(np.random.normal(size=10000)))

Histogram:

There is also another more 'usual' histogram function available:

In [10]: plotille.histogram?
Signature: plotille.histogram(X, bins=160, width=80, height=40, X_label='X', Y_label='Counts', linesep='\n', x_min=None, x_max=None, y_min=None, y_max=None, lc=None, bg=None, color_mode='names')
Docstring:
Create histogram over `X`

In contrast to `hist`, this is the more `usual` histogram from bottom
to up. The X-axis represents the values in `X` and the Y-axis is the
corresponding frequency.

Parameters:
    X: List[float]  The items to count over.
    bins: int       The number of bins to put X entries in (columns).
    height: int     The number of characters for the height (rows).
    X_label: str    Label for X-axis.
    Y_label: str    Label for Y-axis. max 8 characters.
    linesep: str    The requested line seperator. default: os.linesep
    x_min, x_max: float  Limits for the displayed X values.
    y_min, y_max: float  Limits for the displayed Y values.
    lc: multiple         Give the line color.
    bg: multiple         Give the background color.
    color_mode: str      Specify color input mode; 'names' (default), 'byte' or 'rgb'
                         see plotille.color.__docs__

Returns:
    str: histogram over `X`.

In [11]: print(plotille.histogram(np.random.normal(size=10000)))

Canvas:

The underlying plotting area is modeled as the Canvas class:

In [12]: plotille.Canvas?
Init signature: plotille.Canvas(width, height, xmin=0, ymin=0, xmax=1, ymax=1, background=None, color_mode='names')
Docstring:
A canvas object for plotting braille dots

A Canvas object has a `width` x `height` characters large canvas, in which it
can plot indivitual braille point, lines out of braille points, rectangles,...
Since a full braille character has 2 x 4 dots (), the canvas has `width` * 2, `height` * 4
dots to plot into in total.

It maintains two coordinate systems: a reference system with the limits (xmin, ymin)
in the lower left corner to (xmax, ymax) in the upper right corner is transformed
into the canvas discrete, i.e. dots, coordinate system (0, 0) to (`width` * 2, `height` * 4).
It does so transparently to clients of the Canvas, i.e. all plotting functions
only accept coordinates in the reference system. If the coordinates are outside
the reference system, they are not plotted.
Init docstring:
Initiate a Canvas object

Parameters:
    width: int            The number of characters for the width (columns) of the canvas.
    hight: int            The number of characters for the hight (rows) of the canvas.
    xmin, ymin: float     Lower left corner of reference system.
    xmax, ymax: float     Upper right corner of reference system.
    background: multiple  Background color of the canvas.
    color_mode: str       The color-mode for all colors of this canvas; either 'names' (default)
                          'rgb' or 'byte'. See `plotille.color()`.

Returns:
    Canvas object

The most interesting functions are:

point:

Signature: plotille.Canvas.point(self, x, y, set_=True, color=None)
Docstring:
Put a point into the canvas at (x, y) [reference coordinate system]

Parameters:
    x: float         x-coordinate on reference system.
    y: float         y-coordinate on reference system.
    set_: bool       Whether to plot or remove the point.
    color: multiple  Color of the point.

line:

In [14]: plotille.Canvas.line?
Signature: plotille.Canvas.line(self, x0, y0, x1, y1, set_=True, color=None)
Docstring:
Plot line between point (x0, y0) and (x1, y1) [reference coordinate system].

Parameters:
    x0, y0: float    Point 0
    x1, y1: float    Point 1
    set_: bool       Whether to plot or remove the line.
    color: multiple  Color of the line.

rect:

In [15]: Canvas.rect?
Signature: plotille.Canvas.rect(self, xmin, ymin, xmax, ymax, set_=True, color=None)
Docstring:
Plot rectangle with bbox (xmin, ymin) and (xmax, ymax) [reference coordinate system].

Parameters:
    xmin, ymin: float  Lower left corner of rectangle.
    xmax, ymax: float  Upper right corner of rectangle.
    set_: bool         Whether to plot or remove the rect.
    color: multiple    Color of the rect.

plot:

In [16]: Canvas.plot?
Signature: plotille.Canvas.plot(self, x_axis=False, y_axis=False, y_label='Y', x_label='X', linesep='\n')
Docstring:
Transform canvas into `print`-able string

Parameters:
    x_axis: bool  Add a X-axis at the bottom.
    y_axis: bool  Add a Y-axis to the left.
    y_label: str  Label for Y-axis. max 8 characters.
    x_label: str  Label for X-axis.
    linesep: str  The requested line seperator. default: os.linesep

Returns:
    unicode: The cancas as a string.

You can use it for example to plot a house in the terminal:

In [17]: c = Canvas(width=40, height=20)
In [18]: c.rect(0.1, 0.1, 0.6, 0.6)
In [19]: c.line(0.1, 0.1, 0.6, 0.6)
In [20]: c.line(0.1, 0.6, 0.6, 0.1)
In [21]: c.line(0.1, 0.6, 0.35, 0.8)
In [22]: c.line(0.35, 0.8, 0.6, 0.6)
In [23]: print(c.plot())

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