Set continous color map in matplotlib for line chart [duplicate]

Question

I have been trying to visualize a path saved in an array and to apply a color gradient along the line.

This is what I have so far:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm

arr = np.array([[24.99487317, 55.466666  ,  0.        ],
       [24.99487367, 55.46666917,  1.        ],
       [24.99487217, 55.46667017,  2.        ],
       [24.99487183, 55.4666715 ,  3.        ],
       [24.99487133, 55.466673  ,  4.        ],
       [24.99487267, 55.466674  ,  5.        ]])

fig, ax = plt.subplots()
ax.plot(arr[:, 0], arr[:, 1], c=cm.hot(arr[:, 2]), linestyle='dashed')
plt.show()

I want that more recent points are evaluated higher (or more brighter on the 'hot' colormap). Somehow I always get the error:

ValueError: Invalid RGBA argument: array([[0.0416, 0.    , 0.    , 1.    ],
       [1.    , 1.    , 1.    , 1.    ],
       [1.    , 1.    , 1.    , 1.    ],
       ...,
       [1.    , 1.    , 1.    , 1.    ],
       [1.    , 1.    , 1.    , 1.    ],
       [1.    , 1.    , 1.    , 1.    ]])

I can't find any proper example in the docs and I do not know which shape the return values of cm.hot have to have (I tried various ways, alternatively with plt.scatter and the cmap/norm argument but same error)

How do I need to apply the cmap to get a line that gets continously brighter for later observations?

The example in the docs is multicolored line.

ImportanceOfBeingErnest
– ImportanceOfBeingErnest

2019-05-04 09:29:38 +00:00
Commented May 4, 2019 at 9:29 — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented May 4, 2019 at 9:29

Quang Hoang · Accepted Answer · 2019-05-04 03:49:29Z

0

Try seaborn with scatter:

fig, ax = plt.subplots(1,1, figsize=(12,8))
ax.plot(arr[:,0], arr[:,1])
sns.scatterplot(arr[:, 0], arr[:, 1], 
                ax=ax, hue=arr[:,2], 
                palette=plt.cm.hot,
                legend=None)
plt.show()

Output:

answered May 4, 2019 at 3:49

Quang Hoang

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