Numpy arange function produces variable of a different length than the variable it depends on

Question

I am trying to make a pyplot graph, but my x and y values are of different length.

I am using numpy's arange function to create the range of x values based on the length of my list of y values.

def event_editor(EventDatabase, ConcatenatedEvents, ConcatenatedFits):

    for i in list(EventDatabase):

        # Check for events with absurd blockage current

        if abs(EventDatabase[i]['AllLevelFits'][0]) > 5:
            del EventDatabase[i]
            continue
        event = ConcatenatedEvents[i][0]
        fit = ConcatenatedFits[i]
        x_values = np.arange(0, len(event) / 100, .01)
        x_values2 = np.arange(0, len(fit) / 100, .01)

        fig = plt.figure()
        plt.plot(x_values, event, figure=fig)
        plt.plot(x_values2, fit, figure=fig)
        plt.xlabel('Time (ms)', figure=fig)
        plt.ylabel('Current (I)', figure=fig)
        plt.title('Event #' + str(i), figure=fig)
        plt.show()

I'd expect the x_values and the event/fit lists to have the same length, and most of the time they do have the same length. However, when the length of event/fit is 111, the length of the x_values is 112. What causes this?

Possible duplicate of Numpy arange floating point inconsistency — StefOverflow
– StefOverflow, Commented Jul 16, 2019 at 18:44

StefOverflow · Accepted Answer · 2019-07-16 18:44:32Z

2

This is due to float approximation in Python / NumPy. The inconsistent behavior is documented also in its official docs.

A more robust approach is to use: np.linspace() e.g.:

step = 0.01
np.arange(0, len(event) / 100, step)
np.arange(0, len(fit) / 100, step)

becomes, for example:

step = 0.01
N = int(max(len(event) / 100 / step, len(fit) / 100 / step))

np.linspace(0, len(event) / 100, N)
np.linspace(0, len(fit) / 100, N)

note that with np.linspace() you specify the number of points rather than the step as last parameter.

answered Jul 16, 2019 at 18:44

StefOverflow

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