# Plotille
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[](https://pypi.python.org/pypi/plotille)
[](https://pepy.tech/project/plotille)
[](https://pypi.python.org/pypi/plotille)
Plots, scatter plots, histograms and heatmaps in the terminal using braille dots, and foreground and background colors - with no dependancies. Make complex figures using the Figure class or make fast and simple plots using graphing function - similar to a very small sibling to matplotlib. Or use the canvas to plot dots, lines and images yourself.
Install:
```sh
pip install plotille
```
Similar to other libraries:
- like [drawille](https://github.com/asciimoo/drawille), but focused on graphing – plus X/Y-axis.
- like [termplot](https://github.com/justnoise/termplot), but with braille (finer dots), left to right histogram and linear interpolation for plotting function.
- like [termgraph](https://github.com/sgeisler/termgraph) (not on pypi), but very different style.
- like [terminalplot](https://github.com/kressi/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`.
Support for heatmaps using background colors for figures and displaying images binary with braille, or in color with background colors using the canvas - provided with release 4.0
If you are still using python 2.7, please use plotille v4 or before. With v5 I am dropping support for python 2.7, as the effort to maintain the discontinued version is too much.
## Documentation
```python
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`:
```python
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:
```python
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:
```python
# create a plot with linear interpolation between points
Figure.plot(self, X, Y, lc=None, interp='linear', label=None, marker=None)
# create a scatter plot with no interpolation between points
Figure.scatter(self, X, Y, lc=None, label=None, marker=None)
# create a histogram over X
Figure.histogram(self, X, bins=160, lc=None)
# print texts at coordinates X, Y
Figure.text(self, X, Y, texts, lc=None)
# The following functions use relative coordinates on the canvas
# i.e. all coordinates are \in [0, 1]
# plot a vertical line at x
Figure.axvline(self, x, ymin=0, ymax=1, lc=None)
# plot a vertical rectangle from (xmin,ymin) to (xmax, ymax).
Figure.axvspan(self, xmin, xmax, ymin=0, ymax=1, lc=None)
# plot a horizontal line at y
Figure.axhline(self, y, xmin=0, xmax=1, lc=None)
# plot a horizontal rectangle from (xmin,ymin) to (xmax, ymax).
Figure.axhspan(self, ymin, ymax, xmin=0, xmax=1, lc=None)
# Display data as an image, i.e. on a 2D regular raster.
Figure.imgshow(self, X, cmap=None)
```
Other interesting functions are:
```python
# remove all plots, texts, spans and images 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)
```
Please have a look at the [`examples/`](./examples) folder.
### Graphing
There are some utility functions for fast graphing of single plots.
#### Plot
```python
In [4]: plotille.plot?
Signature:
plotille.plot(
X,
Y,
width=80,
height=40,
X_label='X',
Y_label='Y',
linesep=os.linesep,
interp='linear',
x_min=None,
x_max=None,
y_min=None,
y_max=None,
lc=None,
bg=None,
color_mode='names',
origin=True,
marker=None,
)
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__
origin: bool Whether to print the origin. default: True
marker: str Instead of braille dots set a marker char for actual values.
Returns:
str: plot over `X`, `Y`.
In [5]: print(plotille.plot(X, np.sin(X), height=30, width=60))
```
#### Scatter
```python
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',
origin=True,
marker=None,
)
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__
origin: bool Whether to print the origin. default: True
marker: str Instead of braille dots set a marker char.
Returns:
str: scatter plot over `X`, `Y`.
In [7]: print(plotille.scatter(X, np.sin(X), height=30, width=60))
```
#### Hist
Inspired by [crappyhist](http://kevinastraight.x10host.com/2013/12/28/python-histograms-from-the-console/) (link is gone, but I made a [gist](https://gist.github.com/tammoippen/4474e838e969bf177155231ebba52386)).
```python
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)))
```
#### Hist (aggregated)
This function allows you to create a histogram when your data is already aggregated (aka you don't have access to raw values, but you have access to bins and counts for each bin).
This comes handy when working with APIs such as [OpenTelemetry Metrics API](https://opentelemetry-python.readthedocs.io/en/latest/api/metrics.html)
where views such as [ExplicitBucketHistogramAggregation](https://opentelemetry-python.readthedocs.io/en/latest/sdk/metrics.view.html#opentelemetry.sdk.metrics.view.ExplicitBucketHistogramAggregation)
only expose access to aggregated values (counts for each bin / bucket).
```python
In [8]: plotille.hist_aggregated?
Signature:
plotille.hist_aggregated(
counts,
bins,
width=80,
log_scale=False,
linesep='\n',
lc=None,
bg=None,
color_mode='names',
)
Docstring:
Create histogram for aggregated data.
Parameters:
counts: List[int] Counts for each bucket.
bins: List[float] Limits for the bins for the provided counts: limits for
bin `i` are `[bins[i], bins[i+1])`.
Hence, `len(bins) == len(counts) + 1`.
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]: counts = [1945, 0, 0, 0, 0, 0, 10555, 798, 0, 28351, 0]
In [10]: bins = [float('-inf'), 10, 50, 100, 200, 300, 500, 800, 1000, 2000, 10000, float('+inf')]
In [11]: print(plotille.hist_aggregated(counts, bins))
```
Keep in mind that there must always be n+1 bins (n is a total number of count values, 11 in the example above).
In this example the first bin is from [-inf, 10) with a count of 1945 and the last bin is from [10000, +inf] with a count of 0.
#### Histogram
There is also another more 'usual' histogram function available:
```python
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:
```python
In [12]: plotille.Canvas?
Init signature:
plotille.Canvas(
width,
height,
xmin=0,
ymin=0,
xmax=1,
ymax=1,
background=None,
**color_kwargs,
)
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_kwargs: More arguments to the color-function. See `plotille.color()`.
Returns:
Canvas object
```
The most interesting functions are:
_point:_
```python
In [11]: plotille.Canvas.point?
Signature: plotille.Canvas.point(self, x, y, set_=True, color=None, marker=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.
marker: str Instead of braille dots set a marker char.
```
_line:_
```python
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:_
```python
In [15]: plotille.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.
```
_text:_
```python
In [16]: plotille.Canvas.text?
Signature: plotille.Canvas.text(self, x, y, text, set_=True, color=None)
Docstring:
Put some text 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 set the text or clear the characters.
text: str The text to add.
color: multiple Color of the point.
```
_braille_image:_
```python
In [17]: plotille.Canvas.braille_image?
Signature:
plotille.Canvas.braille_image(
self,
pixels,
threshold=127,
inverse=False,
set_=True,
)
Docstring:
Print an image using braille dots into the canvas.
The pixels and braille dots in the canvas are a 1-to-1 mapping, hence
a 80 x 80 pixel image will need a 40 x 20 canvas.
Example:
from PIL import Image
import plotille as plt
img = Image.open("/path/to/image")
img = img.convert('L')
img = img.resize((80, 80))
cvs = plt.Canvas(40, 20)
cvs.braille_image(img.getdata(), 125)
print(cvs.plot())
Parameters:
pixels: list[number] All pixels of the image in one list.
threshold: float All pixels above this threshold will be
drawn.
inverse: bool Whether to invert the image.
set_: bool Whether to plot or remove the dots.
```
_image:_
```python
In [18]: plotille.Canvas.image?
Signature: plotille.Canvas.image(self, pixels, set_=True)
Docstring:
Print an image using background colors into the canvas.
The pixels of the image and the characters in the canvas are a
1-to-1 mapping, hence a 80 x 80 image will need a 80 x 80 canvas.
Example:
from PIL import Image
import plotille as plt
img = Image.open("/path/to/image")
img = img.convert('RGB')
img = img.resize((40, 40))
cvs = plt.Canvas(40, 40, mode='rgb')
cvs.image(img.getdata())
print(cvs.plot())
Parameters:
pixels: list[(R,G,B)] All pixels of the image in one list.
set_: bool Whether to plot or remove the background
colors.
```
_plot:_
```python
In [16]: plotille.Canvas.plot?
Signature: plotille.Canvas.plot(self, linesep='\n')
Docstring:
Transform canvas into `print`-able string
Parameters:
linesep: str The requested line seperator. default: os.linesep
Returns:
unicode: The canvas as a string.
```
You can use it for example to plot a house in the terminal:
```python
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())
```
Or you could render images with braille dots:
```python
In [24]: img = Image.open('https://github.com/tammoippen/plotille/raw/master/imgs/ich.jpg')
In [25]: img = img.convert('L')
In [26]: img = img.resize((80, 80))
In [27]: cvs = Canvas(40, 20)
In [28]: cvs.braille_image(img.getdata())
In [29]: print(cvs.plot())
```
Or you could render images with the background color of characters:
```python
In [24]: img = Image.open('https://github.com/tammoippen/plotille/raw/master/imgs/ich.jpg')
In [25]: img = img.convert('RGB')
In [25]: img = img.resize((80, 40))
In [27]: cvs = Canvas(80, 40, mode="rgb")
In [28]: cvs.image(img.getdata())
In [29]: print(cvs.plot())
```
## Stargazers over time
[](https://starchart.cc/tammoippen/plotille)
Raw data
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"home_page": "https://github.com/tammoippen/plotille",
"name": "plotille",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7,<4.0",
"maintainer_email": "",
"keywords": "plot,scatter,histogram,terminal,braille,unicode,timeseries",
"author": "Tammo Ippen",
"author_email": "tammo.ippen@posteo.de",
"download_url": "https://files.pythonhosted.org/packages/8a/73/3f342572f7f916e387e546cc502d6cad35e7162ba0bcde203669e15aa3af/plotille-5.0.0.tar.gz",
"platform": null,
"description": "\n\n# Plotille\n\n[](https://github.com/tammoippen/plotille/actions/workflows/CI.yml)\n[](https://codecov.io/gh/tammoippen/plotille)\n[](https://lgtm.com/projects/g/tammoippen/plotille/context:python)\n[](https://img.shields.io/badge/cpython-3.7%2C%203.8%2C%203.9%2C%203.10%2C%203.11-brightgreen.svg)\n[](https://img.shields.io/badge/pypy-3.8%2C%203.9-brightgreen.svg)\n[](https://pypi.python.org/pypi/plotille)\n[](https://pepy.tech/project/plotille)\n[](https://pypi.python.org/pypi/plotille)\n\nPlots, scatter plots, histograms and heatmaps in the terminal using braille dots, and foreground and background colors - with no dependancies. Make complex figures using the Figure class or make fast and simple plots using graphing function - similar to a very small sibling to matplotlib. Or use the canvas to plot dots, lines and images yourself.\n\nInstall:\n\n```sh\npip install plotille\n```\n\nSimilar to other libraries:\n\n- like [drawille](https://github.com/asciimoo/drawille), but focused on graphing \u2013 plus X/Y-axis.\n- like [termplot](https://github.com/justnoise/termplot), but with braille (finer dots), left to right histogram and linear interpolation for plotting function.\n- like [termgraph](https://github.com/sgeisler/termgraph) (not on pypi), but very different style.\n- like [terminalplot](https://github.com/kressi/terminalplot), but with braille, X/Y-axis, histogram, linear interpolation.\n\nBasic 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`.\n\nSupport for heatmaps using background colors for figures and displaying images binary with braille, or in color with background colors using the canvas - provided with release 4.0\n\nIf you are still using python 2.7, please use plotille v4 or before. With v5 I am dropping support for python 2.7, as the effort to maintain the discontinued version is too much.\n\n## Documentation\n\n```python\nIn [1]: import plotille\nIn [2]: import numpy as np\nIn [3]: X = np.sort(np.random.normal(size=1000))\n```\n\n### Figure\n\nTo construct plots the recomended way is to use a `Figure`:\n\n```python\nIn [12]: plotille.Figure?\nInit signature: plotille.Figure()\nDocstring:\nFigure class to compose multiple plots.\n\nWithin a Figure you can easily compose many plots, assign labels to plots\nand define the properties of the underlying Canvas. Possible properties that\ncan be defined are:\n\n width, height: int Define the number of characters in X / Y direction\n which are used for plotting.\n x_limits: float Define the X limits of the reference coordinate system,\n that will be plottered.\n y_limits: float Define the Y limits of the reference coordinate system,\n that will be plottered.\n color_mode: str Define the used color mode. See `plotille.color()`.\n with_colors: bool Define, whether to use colors at all.\n background: multiple Define the background color.\n x_label, y_label: str Define the X / Y axis label.\n```\n\nBasically, you create a `Figure`, define the properties and add your plots. Using the `show()` function, the `Figure` generates the plot using a new canvas:\n\n```python\nIn [13] fig = plotille.Figure()\nIn [14] fig.width = 60\nIn [15] fig.height = 30\nIn [16] fig.set_x_limits(min_=-3, max_=3)\nIn [17] fig.set_y_limits(min_=-1, max_=1)\nIn [18] fig.color_mode = 'byte'\nIn [19] fig.plot([-0.5, 1], [-1, 1], lc=25, label='First line')\nIn [20] fig.scatter(X, np.sin(X), lc=100, label='sin')\nIn [21] fig.plot(X, (X+2)**2 , lc=200, label='square')\nIn [22] print(fig.show(legend=True))\n```\n\n\n\nThe available plotting functions are:\n\n```python\n# create a plot with linear interpolation between points\nFigure.plot(self, X, Y, lc=None, interp='linear', label=None, marker=None)\n# create a scatter plot with no interpolation between points\nFigure.scatter(self, X, Y, lc=None, label=None, marker=None)\n# create a histogram over X\nFigure.histogram(self, X, bins=160, lc=None)\n# print texts at coordinates X, Y\nFigure.text(self, X, Y, texts, lc=None)\n\n# The following functions use relative coordinates on the canvas\n# i.e. all coordinates are \\in [0, 1]\n# plot a vertical line at x\nFigure.axvline(self, x, ymin=0, ymax=1, lc=None)\n# plot a vertical rectangle from (xmin,ymin) to (xmax, ymax).\nFigure.axvspan(self, xmin, xmax, ymin=0, ymax=1, lc=None)\n# plot a horizontal line at y\nFigure.axhline(self, y, xmin=0, xmax=1, lc=None)\n# plot a horizontal rectangle from (xmin,ymin) to (xmax, ymax).\nFigure.axhspan(self, ymin, ymax, xmin=0, xmax=1, lc=None)\n\n# Display data as an image, i.e. on a 2D regular raster.\nFigure.imgshow(self, X, cmap=None)\n```\n\nOther interesting functions are:\n\n```python\n# remove all plots, texts, spans and images from the figure\nFigure.clear(self)\n# Create a canvas, plot the registered plots and return the string for displaying the plot\nFigure.show(self, legend=False)\n```\n\nPlease have a look at the [`examples/`](./examples) folder.\n\n### Graphing\n\nThere are some utility functions for fast graphing of single plots.\n\n#### Plot\n\n```python\nIn [4]: plotille.plot?\nSignature:\nplotille.plot(\n X,\n Y,\n width=80,\n height=40,\n X_label='X',\n Y_label='Y',\n linesep=os.linesep,\n interp='linear',\n x_min=None,\n x_max=None,\n y_min=None,\n y_max=None,\n lc=None,\n bg=None,\n color_mode='names',\n origin=True,\n marker=None,\n)\nDocstring:\nCreate plot with X , Y values and linear interpolation between points\n\nParameters:\n X: List[float] X values.\n Y: List[float] Y values. X and Y must have the same number of entries.\n width: int The number of characters for the width (columns) of the canvas.\n hight: int The number of characters for the hight (rows) of the canvas.\n X_label: str Label for X-axis.\n Y_label: str Label for Y-axis. max 8 characters.\n linesep: str The requested line seperator. default: os.linesep\n interp: Optional[str] Specify interpolation; values None, 'linear'\n x_min, x_max: float Limits for the displayed X values.\n y_min, y_max: float Limits for the displayed Y values.\n lc: multiple Give the line color.\n bg: multiple Give the background color.\n color_mode: str Specify color input mode; 'names' (default), 'byte' or 'rgb'\n see plotille.color.__docs__\n origin: bool Whether to print the origin. default: True\n marker: str Instead of braille dots set a marker char for actual values.\n\nReturns:\n str: plot over `X`, `Y`.\n\nIn [5]: print(plotille.plot(X, np.sin(X), height=30, width=60))\n```\n\n\n\n#### Scatter\n\n```python\nIn [6]: plotille.scatter?\nSignature:\nplotille.scatter(\n X,\n Y,\n width=80,\n height=40,\n X_label='X',\n Y_label='Y',\n linesep='\\n',\n x_min=None,\n x_max=None,\n y_min=None,\n y_max=None,\n lc=None,\n bg=None,\n color_mode='names',\n origin=True,\n marker=None,\n)\nDocstring:\nCreate scatter plot with X , Y values\n\nBasically plotting without interpolation:\n `plot(X, Y, ... , interp=None)`\n\nParameters:\n X: List[float] X values.\n Y: List[float] Y values. X and Y must have the same number of entries.\n width: int The number of characters for the width (columns) of the canvas.\n hight: int The number of characters for the hight (rows) of the canvas.\n X_label: str Label for X-axis.\n Y_label: str Label for Y-axis. max 8 characters.\n linesep: str The requested line seperator. default: os.linesep\n x_min, x_max: float Limits for the displayed X values.\n y_min, y_max: float Limits for the displayed Y values.\n lc: multiple Give the line color.\n bg: multiple Give the background color.\n color_mode: str Specify color input mode; 'names' (default), 'byte' or 'rgb'\n see plotille.color.__docs__\n origin: bool Whether to print the origin. default: True\n marker: str Instead of braille dots set a marker char.\n\nReturns:\n str: scatter plot over `X`, `Y`.\n\nIn [7]: print(plotille.scatter(X, np.sin(X), height=30, width=60))\n```\n\n\n\n#### Hist\n\nInspired by [crappyhist](http://kevinastraight.x10host.com/2013/12/28/python-histograms-from-the-console/) (link is gone, but I made a [gist](https://gist.github.com/tammoippen/4474e838e969bf177155231ebba52386)).\n\n```python\nIn [8]: plotille.hist?\nSignature:\nplotille.hist(\n X,\n bins=40,\n width=80,\n log_scale=False,\n linesep='\\n',\n lc=None,\n bg=None,\n color_mode='names',\n)\nDocstring:\nCreate histogram over `X` from left to right\n\nThe values on the left are the center of the bucket, i.e. `(bin[i] + bin[i+1]) / 2`.\nThe values on the right are the total counts of this bucket.\n\nParameters:\n X: List[float] The items to count over.\n bins: int The number of bins to put X entries in (rows).\n width: int The number of characters for the width (columns).\n log_scale: bool Scale the histogram with `log` function.\n linesep: str The requested line seperator. default: os.linesep\n lc: multiple Give the line color.\n bg: multiple Give the background color.\n color_mode: str Specify color input mode; 'names' (default), 'byte' or 'rgb'\n see plotille.color.__docs__\n\nReturns:\n str: histogram over `X` from left to right.\n\nIn [9]: print(plotille.hist(np.random.normal(size=10000)))\n```\n\n\n\n#### Hist (aggregated)\n\nThis function allows you to create a histogram when your data is already aggregated (aka you don't have access to raw values, but you have access to bins and counts for each bin).\n\nThis comes handy when working with APIs such as [OpenTelemetry Metrics API](https://opentelemetry-python.readthedocs.io/en/latest/api/metrics.html)\nwhere views such as [ExplicitBucketHistogramAggregation](https://opentelemetry-python.readthedocs.io/en/latest/sdk/metrics.view.html#opentelemetry.sdk.metrics.view.ExplicitBucketHistogramAggregation)\nonly expose access to aggregated values (counts for each bin / bucket).\n\n```python\nIn [8]: plotille.hist_aggregated?\nSignature:\nplotille.hist_aggregated(\n counts,\n bins,\n width=80,\n log_scale=False,\n linesep='\\n',\n lc=None,\n bg=None,\n color_mode='names',\n)\nDocstring:\nCreate histogram for aggregated data.\n\nParameters:\n counts: List[int] Counts for each bucket.\n bins: List[float] Limits for the bins for the provided counts: limits for\n bin `i` are `[bins[i], bins[i+1])`.\n Hence, `len(bins) == len(counts) + 1`.\n width: int The number of characters for the width (columns).\n log_scale: bool Scale the histogram with `log` function.\n linesep: str The requested line seperator. default: os.linesep\n lc: multiple Give the line color.\n bg: multiple Give the background color.\n color_mode: str Specify color input mode; 'names' (default), 'byte' or 'rgb'\n see plotille.color.__docs__\nReturns:\n str: histogram over `X` from left to right.\n\nIn [9]: counts = [1945, 0, 0, 0, 0, 0, 10555, 798, 0, 28351, 0]\nIn [10]: bins = [float('-inf'), 10, 50, 100, 200, 300, 500, 800, 1000, 2000, 10000, float('+inf')]\nIn [11]: print(plotille.hist_aggregated(counts, bins))\n```\n\nKeep in mind that there must always be n+1 bins (n is a total number of count values, 11 in the example above).\n\nIn this example the first bin is from [-inf, 10) with a count of 1945 and the last bin is from [10000, +inf] with a count of 0.\n\n\n\n#### Histogram\n\nThere is also another more 'usual' histogram function available:\n\n```python\nIn [10]: plotille.histogram?\nSignature:\nplotille.histogram(\n X,\n bins=160,\n width=80,\n height=40,\n X_label='X',\n Y_label='Counts',\n linesep='\\n',\n x_min=None,\n x_max=None,\n y_min=None,\n y_max=None,\n lc=None,\n bg=None,\n color_mode='names',\n)\nDocstring:\nCreate histogram over `X`\n\nIn contrast to `hist`, this is the more `usual` histogram from bottom\nto up. The X-axis represents the values in `X` and the Y-axis is the\ncorresponding frequency.\n\nParameters:\n X: List[float] The items to count over.\n bins: int The number of bins to put X entries in (columns).\n height: int The number of characters for the height (rows).\n X_label: str Label for X-axis.\n Y_label: str Label for Y-axis. max 8 characters.\n linesep: str The requested line seperator. default: os.linesep\n x_min, x_max: float Limits for the displayed X values.\n y_min, y_max: float Limits for the displayed Y values.\n lc: multiple Give the line color.\n bg: multiple Give the background color.\n color_mode: str Specify color input mode; 'names' (default), 'byte' or 'rgb'\n see plotille.color.__docs__\n\nReturns:\n str: histogram over `X`.\n\nIn [11]: print(plotille.histogram(np.random.normal(size=10000)))\n```\n\n\n\n### Canvas\n\nThe underlying plotting area is modeled as the `Canvas` class:\n\n```python\nIn [12]: plotille.Canvas?\nInit signature:\nplotille.Canvas(\n width,\n height,\n xmin=0,\n ymin=0,\n xmax=1,\n ymax=1,\n background=None,\n **color_kwargs,\n)\nDocstring:\nA canvas object for plotting braille dots\n\nA Canvas object has a `width` x `height` characters large canvas, in which it\ncan plot indivitual braille point, lines out of braille points, rectangles,...\nSince a full braille character has 2 x 4 dots (\u28ff), the canvas has `width` * 2, `height` * 4\ndots to plot into in total.\n\nIt maintains two coordinate systems: a reference system with the limits (xmin, ymin)\nin the lower left corner to (xmax, ymax) in the upper right corner is transformed\ninto the canvas discrete, i.e. dots, coordinate system (0, 0) to (`width` * 2, `height` * 4).\nIt does so transparently to clients of the Canvas, i.e. all plotting functions\nonly accept coordinates in the reference system. If the coordinates are outside\nthe reference system, they are not plotted.\nInit docstring:\nInitiate a Canvas object\n\nParameters:\n width: int The number of characters for the width (columns) of the canvas.\n hight: int The number of characters for the hight (rows) of the canvas.\n xmin, ymin: float Lower left corner of reference system.\n xmax, ymax: float Upper right corner of reference system.\n background: multiple Background color of the canvas.\n **color_kwargs: More arguments to the color-function. See `plotille.color()`.\n\nReturns:\n Canvas object\n```\n\nThe most interesting functions are:\n\n_point:_\n\n```python\nIn [11]: plotille.Canvas.point?\nSignature: plotille.Canvas.point(self, x, y, set_=True, color=None, marker=None)\nDocstring:\nPut a point into the canvas at (x, y) [reference coordinate system]\n\nParameters:\n x: float x-coordinate on reference system.\n y: float y-coordinate on reference system.\n set_: bool Whether to plot or remove the point.\n color: multiple Color of the point.\n marker: str Instead of braille dots set a marker char.\n```\n\n_line:_\n\n```python\nIn [14]: plotille.Canvas.line?\nSignature: plotille.Canvas.line(self, x0, y0, x1, y1, set_=True, color=None)\nDocstring:\nPlot line between point (x0, y0) and (x1, y1) [reference coordinate system].\n\nParameters:\n x0, y0: float Point 0\n x1, y1: float Point 1\n set_: bool Whether to plot or remove the line.\n color: multiple Color of the line.\n```\n\n_rect:_\n\n```python\nIn [15]: plotille.Canvas.rect?\nSignature: plotille.Canvas.rect(self, xmin, ymin, xmax, ymax, set_=True, color=None)\nDocstring:\nPlot rectangle with bbox (xmin, ymin) and (xmax, ymax) [reference coordinate system].\n\nParameters:\n xmin, ymin: float Lower left corner of rectangle.\n xmax, ymax: float Upper right corner of rectangle.\n set_: bool Whether to plot or remove the rect.\n color: multiple Color of the rect.\n```\n\n_text:_\n\n```python\nIn [16]: plotille.Canvas.text?\nSignature: plotille.Canvas.text(self, x, y, text, set_=True, color=None)\nDocstring:\nPut some text into the canvas at (x, y) [reference coordinate system]\n\nParameters:\n x: float x-coordinate on reference system.\n y: float y-coordinate on reference system.\n set_: bool Whether to set the text or clear the characters.\n text: str The text to add.\n color: multiple Color of the point.\n```\n\n_braille_image:_\n\n```python\nIn [17]: plotille.Canvas.braille_image?\nSignature:\nplotille.Canvas.braille_image(\n self,\n pixels,\n threshold=127,\n inverse=False,\n set_=True,\n)\nDocstring:\nPrint an image using braille dots into the canvas.\n\nThe pixels and braille dots in the canvas are a 1-to-1 mapping, hence\na 80 x 80 pixel image will need a 40 x 20 canvas.\n\nExample:\n from PIL import Image\n import plotille as plt\n\n img = Image.open(\"/path/to/image\")\n img = img.convert('L')\n img = img.resize((80, 80))\n cvs = plt.Canvas(40, 20)\n cvs.braille_image(img.getdata(), 125)\n print(cvs.plot())\n\nParameters:\n pixels: list[number] All pixels of the image in one list.\n threshold: float All pixels above this threshold will be\n drawn.\n inverse: bool Whether to invert the image.\n set_: bool Whether to plot or remove the dots.\n```\n\n_image:_\n\n```python\nIn [18]: plotille.Canvas.image?\nSignature: plotille.Canvas.image(self, pixels, set_=True)\nDocstring:\nPrint an image using background colors into the canvas.\n\nThe pixels of the image and the characters in the canvas are a\n1-to-1 mapping, hence a 80 x 80 image will need a 80 x 80 canvas.\n\nExample:\n from PIL import Image\n import plotille as plt\n\n img = Image.open(\"/path/to/image\")\n img = img.convert('RGB')\n img = img.resize((40, 40))\n cvs = plt.Canvas(40, 40, mode='rgb')\n cvs.image(img.getdata())\n print(cvs.plot())\n\nParameters:\n pixels: list[(R,G,B)] All pixels of the image in one list.\n set_: bool Whether to plot or remove the background\n colors.\n```\n\n_plot:_\n\n```python\nIn [16]: plotille.Canvas.plot?\nSignature: plotille.Canvas.plot(self, linesep='\\n')\nDocstring:\nTransform canvas into `print`-able string\n\nParameters:\n linesep: str The requested line seperator. default: os.linesep\n\nReturns:\n unicode: The canvas as a string.\n```\n\nYou can use it for example to plot a house in the terminal:\n\n```python\nIn [17]: c = Canvas(width=40, height=20)\nIn [18]: c.rect(0.1, 0.1, 0.6, 0.6)\nIn [19]: c.line(0.1, 0.1, 0.6, 0.6)\nIn [20]: c.line(0.1, 0.6, 0.6, 0.1)\nIn [21]: c.line(0.1, 0.6, 0.35, 0.8)\nIn [22]: c.line(0.35, 0.8, 0.6, 0.6)\nIn [23]: print(c.plot())\n```\n\n\n\nOr you could render images with braille dots:\n\n```python\nIn [24]: img = Image.open('https://github.com/tammoippen/plotille/raw/master/imgs/ich.jpg')\nIn [25]: img = img.convert('L')\nIn [26]: img = img.resize((80, 80))\nIn [27]: cvs = Canvas(40, 20)\nIn [28]: cvs.braille_image(img.getdata())\nIn [29]: print(cvs.plot())\n```\n\n\n\nOr you could render images with the background color of characters:\n\n```python\nIn [24]: img = Image.open('https://github.com/tammoippen/plotille/raw/master/imgs/ich.jpg')\nIn [25]: img = img.convert('RGB')\nIn [25]: img = img.resize((80, 40))\nIn [27]: cvs = Canvas(80, 40, mode=\"rgb\")\nIn [28]: cvs.image(img.getdata())\nIn [29]: print(cvs.plot())\n```\n\n\n\n## Stargazers over time\n\n[](https://starchart.cc/tammoippen/plotille)\n",
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