How to make a plot of a discontinuous 1d function without line at a function jump. An example is shown on a picture. This was plotted by:

import numpy

from matplotlib import pyplot

x = numpy.linspace(-1.0, 1.0, 100)

y = numpy.sign(x) * numpy.cos(x)

axes = pyplot.gca()

axes.set_ylim(-1.1, 1.1)

pyplot.plot(x, y)

# 1d plot of a discontinuous function

idx = (x>0)

pyplot(x[idx],y[idx])

idx = numpy.logical_not(idx)

pyplot(x[idx],y[idx])

## ···

Le vendredi 30 septembre 2011 à 17:31 +0400, Александров Петр a écrit :

How to make a plot of a discontinuous 1d function without line at a

function jump. An example is shown on a picture. This was plotted by:

import numpy

from matplotlib import pyplot

x = numpy.linspace(-1.0, 1.0, 100)

y = numpy.sign(x) * numpy.cos(x)

axes = pyplot.gca()

axes.set_ylim(-1.1, 1.1)

pyplot.plot(x, y)

--

Fabrice Silva

Hey,

How to make a plot of a discontinuous 1d function without line at a

function jump. An example is shown on a picture. This was plotted by:

import numpy

from matplotlib import pyplot

x = numpy.linspace(-1.0, 1.0, 100)

y = numpy.sign(x) * numpy.cos(x)

axes = pyplot.gca()

axes.set_ylim(-1.1, 1.1)

pyplot.plot(x, y)

You can plot two lines, or use nan (or masked arrays I guess) to break

the line. in this case, this would be something like:

x = np.linspace(-1.0, 1.0, 101) # 101 as then 0 is included

s = np.sign(x)

s[s==0] = np.nan

y = s * np.cos(x)

plt.plot(x, y)

Regards,

Sebastian

## ···

On Fri, 2011-09-30 at 17:31 +0400, Александров Петр wrote:

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2011/9/30 Александров Петр <petr_aleksandrov@…337…>

How to make a plot of a discontinuous 1d function without line at a function jump. An example is shown on a picture. This was plotted by:

import numpy

from matplotlib import pyplot

x = numpy.linspace(-1.0, 1.0, 100)y = numpy.sign(x) * numpy.cos(x)

axes = pyplot.gca()

axes.set_ylim(-1.1, 1.1)

pyplot.plot(x, y)

If you happen to know where the discontinuity is, then you could do two separate plot commands. Automatically, it is harder. Maybe something like this would help:

threshold = 1000.0

# Use gradient instead of diff because it returns an array of the same shape

dydx = numpy.gradient(y) / numpy.gradient(x)

idx = (numpy.abs(dydx) < threshold)

axes.plot(x[idx], y[idx])

Although, that gets rid of valid data points. Another trick would be to rebuild the x and y arrays, but with NaNs placed between datapoints that would form the discontinuity. matplotlib automatically treats NaNs as a indicator to break a line.

Ben Root