watex.view.plot_matshow#

watex.view.plot_matshow(arr, /, labelx=None, labely=None, matshow_kws=None, **baseplot_kws)[source]#

Quick matrix visualization using matplotlib.pyplot.matshow.

Parameters

  • arr (2D ndarray,) – matrix of n rowns and m-columns items

  • matshow_kws (dict) – Additional keywords arguments for matplotlib.axes.matshow()

  • labelx (list of str, optional) – list of labels names that express the name of each category on x-axis. It might be consistent with the matrix number of columns of arr.

  • label (list of str, optional) – list of labels names that express the name of each category on y-axis. It might be consistent with the matrix number of row of arr.

Examples

>>> import numpy as np
>>> from watex.view.mlplot import plot_matshow
>>> matshow_kwargs ={
    'aspect': 'auto',
    'interpolation': None,
   'cmap':'copper_r',
        }
>>> baseplot_kws ={'lw':3,
           'lc':(.9, 0, .8),
           'font_size':15.,
            'cb_format':None,
            #'cb_label':'Rate of prediction',
            'xlabel': 'Predicted flow classes',
            'ylabel': 'Geological rocks',
            'font_weight':None,
            'tp_labelbottom':False,
            'tp_labeltop':True,
            'tp_bottom': False
            }
>>> labelx =['FR0', 'FR1', 'FR2', 'FR3', 'Rates']
>>> labely =['VOLCANO-SEDIM. SCHISTS', 'GEOSYN. GRANITES',
             'GRANITES', '1.0', 'Rates']
>>> array2d = np.array([(1. , .5, 1. ,1., .9286),
                    (.5,  .8, 1., .667, .7692),
                    (.7, .81, .7, .5, .7442),
                    (.667, .75, 1., .75, .82),
                    (.9091, 0.8064, .7, .8667, .7931)])
>>> plot_matshow(array2d, labelx, labely, matshow_kwargs,**baseplot_kws )