matplotlib-dashboard 0.0.4

This package, with the aim of accelerating and facilitating the use of some design patterns, offers abstract classes.

Matplotlib Dashboard Package

This package creates a simple user interface for creating subfigures when working with matplotlib.

import matplotlib.pyplot as plt
plt.figure(figsize=(10,10))

from matplotlib_dashboard import MatplotlibDashboard
dashboard = MatplotlibDashboard([
    ['top' ,'top' ,'top' ,'top'  ],
    ['left','left', None ,'right'],
    ['left','left','down','right'],
], as3D=['left'], wspace=0.5, hspace=0.5)

import numpy as np
dashboard['top'].plot(np.random.rand(200), color='red')
dashboard['top'].set_ylabel('y')
dashboard['top'].set_xlabel('x')
dashboard['top'].set_title('top plot')

dashboard['right'].bar(['A','B','C'], [10,35,17], color='blue')
dashboard['right'].set_ylabel('freq')
dashboard['right'].set_xlabel('label')
dashboard['right'].set_title('right bar')

from PIL import Image
dashboard['down'].imshow(Image.open('./test1.jpeg'))
dashboard['down'].get_xaxis().set_ticks([])
dashboard['down'].get_yaxis().set_ticks([])
dashboard['down'].set_title('down image')

z = ((5-np.arange(100)%10)**3).reshape(10,10)
x, y = np.meshgrid(np.arange(z.shape[0]), np.arange(z.shape[1]))
dashboard['left'].plot_surface(x, y, z, color='green')
dashboard['left'].set_ylabel('x')
dashboard['left'].set_xlabel('y')
dashboard['left'].set_zlabel('z')
dashboard['left'].set_title('left surface')

plt.show()

Customization

• Pass the map of subfigures you want when getting an instance of the dashboard. Write the map as a list of lists or a 2D array.
• Get the subfigure you want using get-item syntax. The name is what you defined in the map.
• Use the None keyword to access the empty part of the map.
• Use as3D argument to determine which subfigures are 3D.
• Any customization on matplotlib.pyplot also applies to this dashboard. For example, use plt.figure(figsize=(x,y)) to change the size of the dashboard figure.
• This module is based on matplotlib.gridspec. Therefore, you can use the gridspec initialization configurable parameters with the same functionality in this dashboard initialization. For example, set the wspace and hspace parameters to change the horizontal or vertical spacing between subfigures.

Installation

pip install matplotlib-dashboard