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https://lvwerra.github.io/jupyterplot/
Create real-time plots in Jupyter Notebooks.
https://lvwerra.github.io/jupyterplot/
Last synced: 4 months ago
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Create real-time plots in Jupyter Notebooks.
- Host: GitHub
- URL: https://lvwerra.github.io/jupyterplot/
- Owner: lvwerra
- License: apache-2.0
- Created: 2020-01-16T15:42:56.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-04-11T23:58:54.000Z (almost 2 years ago)
- Last Synced: 2024-10-23T06:07:22.962Z (4 months ago)
- Language: Jupyter Notebook
- Homepage: https://lvwerra.github.io/jupyterplot/
- Size: 9.4 MB
- Stars: 131
- Watchers: 3
- Forks: 10
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# jupyterplot
> Create real-time plots in Jupyter notebooks.## What is it?
It generalises Andreas Madsen's excellent [python-lrcurve](https://github.com/AndreasMadsen/python-lrcurve) library for machine learning to produce visualisations for arbitrary functions in real-time.

## Install
`pip install jupyterplot`
## How to use
### Single plotCreating a simple real-time plot in a Jupyter notebook is as easy as easy as the following snippet:
```
from jupyterplot import ProgressPlot
import numpy as nppp = ProgressPlot()
for i in range(1000):
pp.update(np.sin(i / 100))
pp.finalize()
```
**Note:** The `pp.finalize()` statement is necessary to make the plots persistent between notebook sessions.
### Custom range
By default, the x and y ranges adapt to new data points. If the scale is known beforehand, it can be steadier to set it beforehand:```
pp = ProgressPlot(x_lim=[0, 1000], y_lim=[-1.5, 1.5])
for i in range(1000):
pp.update(np.sin(i / 100))
pp.finalize()
```
### Multiple lines
One can also plot several lines in parallel by specifying the line names in the constructor and passing all values in a list.```
pp = ProgressPlot(line_names=["lin", "log", "cos", "sin"],
x_lim=[0, 1000],
y_lim=[-1, 4])for i in range(1000):
pp.update([[i / 250, np.log10(i + 1), np.cos(i / 100), np.sin(i / 100)]])
pp.finalize()
```
**Note:** The data is fed to `pp.update()` as a list of lists, where each sublist corresponds to the curves that are generated in each subplot.
### Multiple plots
```
pp = ProgressPlot(plot_names=["cos", "sin"],
line_names=["data", "delayed-data"],
x_lim=[0, 1000],
y_lim=[-1, 1])for i in range(1000):
pp.update([[np.cos(i / 100), np.cos((i + 20) / 100)],
[np.sin(i / 100), np.sin((i + 20) / 100)]])
pp.finalize()
```
### Custom x-values
If the x values should not be incremented by 1 at every update one can set the `x_iterator=False`. This requires passing two values to the `update(x, y)`, where `x` is an `int` or `float` and `y` follows the same format as in the previous examples.```
pp = ProgressPlot(x_iterator=False, x_label="custom-x", x_lim=[0, 10000], y_lim=[0, 10])
for i in range(1000):
pp.update(10 * i, i / 100)
pp.finalize()
```
### Decoupled y-limits
If each subplot should have different y-limits then the y-limits can be passed as a list containing the the limits for each subplot.```
pp = ProgressPlot(plot_names=['plot 1', 'plot 2'], x_lim=[0, 1000], y_lim=[[0, 10],[0, 100]])
for i in range(1000):
pp.update([[(i/100)], [(i/100)**2]])
```
### Input format
#### Single plot, single line
If the progress plot consists of a single plot with a single line one can pass the y-updates as `int` or `float`.
#### Multiple plots, multiple lines
If multiple plots or lines are used, the y-updates can either be lists or dicts:
```python
y_update_list = [[y_plot_1_line_1, y_plot_1_line_2],
[y_plot_2_line_1, y_plot_2_line_2]]y_update_dict = {'plot_name_1': {'line_name_1': y_plot_1_line_1,
'line_name_2': y_plot_1_line_2},
'plot_name_2': {'line_name_1': y_plot_2_line_1,
'line_name_2': y_plot_2_line_2}}
```## Limitations
* Only one `ProgressPlot()` object can be used at a time.
* Each subplot must have the same number of lines.
* The same color cycle for each subplot is used.