CODEWITHSUNDEEP
python-3.xmatplotlib
Sra1
Sra1

Reputation: 670

Highlighting arbitrary points in a matplotlib plot

I am new to python and matplotlib.

I am trying to highlight a few points that match a certain criteria in an already existing plot in matplotlib.

The code for the initial plot is as below:

pl.plot(t,y)
pl.title('Damped Sine Wave with %.1f Hz frequency' % f)
pl.xlabel('t (s)')
pl.ylabel('y')
pl.grid()
pl.show()

In the above plot I wanted to highlight some specific points which match the criteria abs(y)>0.5. The code coming up with the points is as below:

markers_on = [x for x in y if abs(x)>0.5]

I tried using the argument 'markevery', but it throws an error saying 

'markevery' is iterable but not a valid form of numpy fancy indexing;

The code that was giving the error is as below:

pl.plot(t,y,'-gD',markevery = markers_on)
pl.title('Damped Sine Wave with %.1f Hz frequency' % f)
pl.xlabel('t (s)')
pl.ylabel('y')
pl.grid()
pl.show()

Upvotes: 4

Views: 13406

Answers (4)

Julian Espinel
Julian Espinel

Reputation: 3492

I was having this issue because I was trying to mark some points that were out of the bounds of the data frame.

For example:

some_df.shape
-> (276, 9)

markers = [1000, 1080, 1120]

some_df.plot(
    x='date',
    y=['speed'],
    figsize=(17, 7), title="Performance",
    legend=True,
    marker='o',
    markersize=10,
    markevery=markers,
)

-> ValueError: markevery=[1000, 1080, 1120] is iterable but not a valid numpy fancy index

Just make sure that the values you are giving as markers are within the bounds of the data frame you want to plot.

Upvotes: 0

9 Guy
9 Guy

Reputation: 309

markevery uses boolean values to mark every point where a boolean is True

so instead of markers_on = [x for x in y if abs(x)>0.5]

you'd do markers_on = [abs(x)>0.5 for x in y] which will return a list of boolean values the same size of y, and every point where |x| > 0.5 you'd get True

Then you'd use your code as is: 

pl.plot(t,y,'-gD',markevery = markers_on)
pl.title('Damped Sine Wave with %.1f Hz frequency' % f)
pl.xlabel('t (s)')
pl.ylabel('y')
pl.grid()
pl.show()

I know this question is old, but I found this solution while trying to do the top answer as I'm not familiar with numpy and it seemed to overcomplicate things

Upvotes: 2

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339120

The markevery argument to the plotting function accepts different types of inputs. Depending on the input type, they are interpreted differently. Find a nice list of possibilities in this matplotlib example.

In the case where you have a condition for the markers to show, there are two options. Assuming t and y are numpy arrays and one has imported numpy as np,

  1. Either specify a boolean array, 

    plt.plot(t,y,'-gD',markevery = np.where(y > 0.5, True, False))

or

  1. an array of indices.

    plt.plot(t,y,'-gD',markevery = np.arange(len(t))[y > 0.5])

Complete example

import matplotlib.pyplot as plt
import numpy as np; np.random.seed(42)

t = np.linspace(0,3,14)
y = np.random.rand(len(t))

plt.plot(t,y,'-gD',markevery = np.where(y > 0.5, True, False))
# or 
#plt.plot(t,y,'-gD',markevery = np.arange(len(t))[y > 0.5])

plt.xlabel('t (s)')
plt.ylabel('y')

plt.show()

resulting in

enter image description here

Upvotes: 5

Sra1
Sra1

Reputation: 670

The markevery argument only takes indices of type None, integer or boolean arrays as input. Since I was passing the values directly it was throwing the error.

I know it is not very pythonic but I used the below code to come up with the indices.

marker_indices = []
for x in range(len(y)):
    if abs(y[x]) > 0.5:
        marker_indices.append(x)

Upvotes: 0

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