Matplotlib's build-in interval plot

Question

I'm trying to plot multi intervals for multiple entries.

I've tried using a loop to enumerate over the entries, plotting one interval at a time.

import matplotlib.pyplot as plt

intervals = [(1, 2), (1.1, 2.5), (1.2, 4), (1.5, 10), (1.7, 12)]

num_intervals = len(intervals)
viridis = plt.cm.get_cmap('viridis', num_intervals)

fig, ax = plt.subplots()
for idx, (min_int, max_int) in enumerate(intervals):
  ax.hlines(y=idx, xmin=min_int, xmax=max_int, colors=viridis(idx / num_intervals), label=idx)
ax.legend()
plt.yticks([], [])
plt.show()

I wish to use matplotlib's build-in method for plotting multiple intervals all at once. Also, I wish to plot the min and max values for each interval in the image.

I wish to add min & max values annotations to the lines as such:

Answer 1

You can tweak your code to be able to use LineCollection whose idea is outlined in this answer. Furthermore, you can add the legends to the LineCollection using this approach.

I modified the first answer to create the lines input data in the desired format using list comprehension.

from matplotlib.lines import Line2D # Imported for legends

num_intervals = len(intervals)
viridis = plt.cm.get_cmap('viridis', num_intervals)
colors = np.array([viridis(idx / num_intervals) for idx in range(len(intervals))])

# Prepare the input data in correct format for LineCollection 
lines = [[(i[0], j), (i[1], j)] for i, j in zip(intervals, range(len(intervals)))]

lc = mc.LineCollection(lines, colors= colors, linewidths=2)
fig, ax = pl.subplots()
ax.add_collection(lc)
ax.margins(0.1)
plt.yticks([], [])

# Adding the legends
def make_proxy(col, scalar_mappable, **kwargs):
    color = col 
    return Line2D([0, 1], [0, 1], color=color, **kwargs)
proxies = [make_proxy(c, lc, linewidth=2) for c in colors]
ax.legend(proxies, range(5))

# Adding annotations
for i, x in enumerate(intervals):
    plt.text(x[0], i+0.1, x[0], color=colors[i])
    plt.text(x[1], i+0.1, x[1], color=colors[i])