PyDLC - Density Line Charts with Python
Python implementation of the Density Line Chart (Moritz & Fisher, 2018) to visualize time series collections.
Installation
Python Package Index
$ pip install pydlcRequirements
Usage
The following example shows how to import and use the dense_lines plotting function.
import numpy as np
import matplotlib.pyplot as plt
from pydlc import dense_lines
# Generate random synthetic time series
x = np.linspace(0, 90, 25)
ys = []
for _ in range(10000):
ys.append(np.random.randn(1)*np.exp(-x/100))
# Plot here
fig, axs = plt.subplots(1, 2, figsize=(8, 3), sharey=True, sharex=True)
axs[0].plot(x, np.array(ys).T, lw=1) # this is slow and cluttered
axs[0].set_title('Line Chart')
im = dense_lines(ys, x=x, ax=axs[1], cmap='magma') # this is fast and clean
axs[1].set_title('Density Lines Chart')
fig.colorbar(im)
fig.tight_layout()
plt.savefig('./figures/example.png', dpi=144, bbox_inches='tight')
plt.show()Limitations
The vertical grid size can be adjusted with the ny parameter. Higher values of ny yield a smoother density visualization. However, the horizontal grid size is currently limited to the same size as the input sequences and there is no parameter to adjust it (yet).
Algorithm
This graphical abstract explains the algorithm (source).
