Maybe this question exists already, but I could not find it.
I am making a scatter plot in Python. For illustrative purposes, I don't want to set my axes range such that all points are included - there may be some really high or really low values, and all I care about in those points is that they exist - that is, they need to be in the plot, but not on their actual value - rather, somewhere on the top of the canvas.
I know that in IDL there is a nice short syntax for this: in plot(x,y<value)
any value in y greater than value
will simply be put at y=value
.
I am looking for something similar in Python. Can somebody help me out?
you can just use np.minimum
on the y
data to set anything above your upper limit to that limit. np.minimum
calculates the minima element-wise, so only those values greater than ymax
will be set to ymax
.
For example:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0., np.pi*2, 30)
y = 10. * np.sin(x)
ymax = 5
fig, ax = plt.subplots(1)
ax.scatter(x, np.minimum(y, ymax))
plt.show()
There is no equivalent syntactic sugar in matplotlib. You will have to preprocess your data, e.g.:
import numpy as np
import matplotlib.pyplot as plt
ymin, ymax = 0, 0.9
x, y = np.random.rand(2,1000)
y[y>ymax] = ymax
fig, ax = plt.subplots(1,1)
ax.plot(x, y, 'o', ms=10)
ax.set_ylim(ymin, ymax)
plt.show()
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