dmplot: A Python Package for Dynamic Multiple Plot Generation

dmplot is a Python package designed to facilitate the creation of multiple subplots arranged in a grid-like fashion without having to stress over making the subplots fit in a grid. It provides a simple interface for generating various types of plots from datasets, with customizable layouts, simple preset plotting functions and the ability to use custom plotting functions.

CHECK OUT THE NOTEBOOK FOR A SIMPLE GUIDE AND EXAMPLES!!!!

Features

• Automatically creates a grid layout for multiple subplots.
• Flexible customization of grid shape (square, long, or perfect fit).
• Predefined plotting functions for quick use.
• Support for custom plotting functions.
• Easy legend customization across subplots or for the entire figure.

MultiPlot attributes

• dataset:
  • <list> of array like data or
  • <dict> of {key (will be used as the title of the subplot): array like data} pairs
• shape:
  • <tuple> describing the shape of the grid (rows x columns)
• perfect_shape:
  • <bool>, if True, the resulting gird will have no empty spaces.
• square_shape:
  • <bool>, if True, the grid will try to form a square shape (rows = columns)
• long:
  • <bool>, if True, rows > columns, if False, rows < columns
• figsize:
  • <tuple>, if not specified, will be set to (12, 10) if long=True, or (10, 12) if long=False.

PlotFunctions class

Containts several simple plotting functions to save you from the hassle of creating your own plot functions. Passed inside the dynamic_plot() method of the MultiPlot class.

• plot(ax, data)
• scatterplot(ax, data)
• barplot(ax, data)
• histplot(ax, data)
• imshow(ax, data)
• boxplot(ax, data)
• violinplot(ax, data)

Example Usecase

import numpy as np
import matplotlib.pyplot as plt
from dmplot import MultiPlot, PlotFunctions

n = 6
dataset = [np.random.standard_exponential(10_000) for _ in range(n)]
mp = MultiPlot(dataset, perfect_shape=True, figsize=(8, 6))
fig, axes = mp.dynamic_plot(PlotFunctions.plot)

colors = "rgbykm"
[line.set_color(colors[i]) for i, ax in enumerate(axes) for line in ax.get_lines()]

plt.tight_layout()
plt.show()