20

I have two list as below:

latt=[42.0,41.978567980875397,41.96622693388357,41.963791391892457,...,41.972407378075879]
lont=[-66.706920989908909,-66.703116557977069,-66.707351643324543,...-66.718218142021925]

now I want to plot this as a line, separate each 10 of those 'latt' and 'lont' records as a period and give it a unique color. what should I do?

Trenton McKinney
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wuwucat
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5 Answers5

46

There are several different ways to do this. The "best" approach will depend mostly on how many line segments you want to plot.

If you're just going to be plotting a handful (e.g. 10) line segments, then just do something like:

import numpy as np
import matplotlib.pyplot as plt

def uniqueish_color():
    """There're better ways to generate unique colors, but this isn't awful."""
    return plt.cm.gist_ncar(np.random.random())

xy = (np.random.random((10, 2)) - 0.5).cumsum(axis=0)

fig, ax = plt.subplots()
for start, stop in zip(xy[:-1], xy[1:]):
    x, y = zip(start, stop)
    ax.plot(x, y, color=uniqueish_color())
plt.show()

enter image description here

If you're plotting something with a million line segments, though, this will be terribly slow to draw. In that case, use a LineCollection. E.g.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

xy = (np.random.random((1000, 2)) - 0.5).cumsum(axis=0)

# Reshape things so that we have a sequence of:
# [[(x0,y0),(x1,y1)],[(x0,y0),(x1,y1)],...]
xy = xy.reshape(-1, 1, 2)
segments = np.hstack([xy[:-1], xy[1:]])

fig, ax = plt.subplots()
coll = LineCollection(segments, cmap=plt.cm.gist_ncar)
coll.set_array(np.random.random(xy.shape[0]))

ax.add_collection(coll)
ax.autoscale_view()

plt.show()

enter image description here

For both of these cases, we're just drawing random colors from the "gist_ncar" coloramp. Have a look at the colormaps here (gist_ncar is about 2/3 of the way down): http://matplotlib.org/examples/color/colormaps_reference.html

tacaswell
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Joe Kington
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  • Ah, I assumed he wanted lines from the "now I want to plot this as a line", but on re-reading, you're probably right. – Joe Kington Jun 21 '13 at 17:56
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    question. What are you specifying with: `coll.set_array(np.random.random(xy.shape[0]))` documentation is very unclear about this [link](https://matplotlib.org/api/cm_api.html#matplotlib.cm.ScalarMappable.set_array) – J.A.Cado Feb 08 '19 at 08:39
  • @JoeKington this looks awesome, I have a question, How can I make it limited to two lines, if the value is negative, shows red otherwise green – Volatil3 Oct 20 '21 at 05:49
  • @J.A.Cado the set_array is a numeric value to indicate the colors. In this example he sets a random series of number, but for my example i would set the numeric values indicating the color change – MadmanLee Apr 05 '22 at 22:37
5

Copied from this example:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm

x = np.linspace(0, 3 * np.pi, 500)
y = np.sin(x)
z = np.cos(0.5 * (x[:-1] + x[1:]))  # first derivative

# Create a colormap for red, green and blue and a norm to color
# f' < -0.5 red, f' > 0.5 blue, and the rest green
cmap = ListedColormap(['r', 'g', 'b'])
norm = BoundaryNorm([-1, -0.5, 0.5, 1], cmap.N)

# Create a set of line segments so that we can color them individually
# This creates the points as a N x 1 x 2 array so that we can stack points
# together easily to get the segments. The segments array for line collection
# needs to be numlines x points per line x 2 (x and y)
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)

# Create the line collection object, setting the colormapping parameters.
# Have to set the actual values used for colormapping separately.
lc = LineCollection(segments, cmap=cmap, norm=norm)
lc.set_array(z)
lc.set_linewidth(3)

fig1 = plt.figure()
plt.gca().add_collection(lc)
plt.xlim(x.min(), x.max())
plt.ylim(-1.1, 1.1)

plt.show()
ali_m
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2

See the answer here to generate the "periods" and then use the matplotlib scatter function as @tcaswell mentioned. Using the plot.hold function you can plot each period, colors will increment automatically.

Community
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blazetopher
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2

Cribbing the color choice off of @JoeKington, 

import numpy as np
import matplotlib.pyplot as plt

def uniqueish_color(n):
    """There're better ways to generate unique colors, but this isn't awful."""
    return plt.cm.gist_ncar(np.random.random(n))

plt.scatter(latt, lont, c=uniqueish_color(len(latt)))

You can do this with scatter.

tacaswell
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1

I have been searching for a short solution how to use pyplots line plot to show a time series coloured by a label feature without using scatter due to the amount of data points.

I came up with the following workaround:

plt.plot(np.where(df["label"]==1, df["myvalue"], None), color="red", label="1")
plt.plot(np.where(df["label"]==0, df["myvalue"], None), color="blue", label="0")
plt.legend()

The drawback is you are creating two different line plots so the connection between the different classes is not shown. For my purposes it is not a big deal. It may help someone.

Andre S.
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