CODEWITHSUNDEEP
pythongraphmatplotlibaxis-labels
Sarah Tattersall
Sarah Tattersall

Reputation: 1305

Matplotlib x-labels for logarithmic graph

I'm trying to plot some data in matplotlib to show the results of an experiement as follows:

xvalues = [2, 4, 8, 16, 32, 64, 128, 256]
yvalues = [400139397.517, 339303459.4277, 296846508.2103, 271801897.1163,
           295153640.7553, 323820220.6226, 372099806.9102, 466940449.0719]

I wish to plot this on a logarithmic scale to make it easier to visualise and so have written the following code:

import matplotlib.pyplot as plt

def plot_energy(xvalues, yvalues):
    fig = plt.figure()
    ax = fig.add_subplot(1,1,1)

    ax.scatter(xvalues, yvalues)
    ax.plot(xvalues, yvalues)

    ax.set_xscale('log')

    ax.set_xticklabels(xvalues)

    ax.set_xlabel('RUU size')
    ax.set_title("Energy consumption")
    ax.set_ylabel('Energy per instruction (nJ)')
    plt.show()

However as you can see my xlabels don't appear as I'd like them to as seen below Matplotlib axis graph

If I remove the line ax.set_xticklabels(xvalues) then I get the following result, which isn't what I'd like either: Matplotlib second axis graph

I'd be very grateful for some help in plotting the correct values on the x-axis!

Thanks in advance.

Upvotes: 0

Views: 829

Answers (2)

Rutger Kassies
Rutger Kassies

Reputation: 64443

You are only altering the labels of the ticks, not the ticks position. If you use:

ax.set_xticks(xvalues)

It looks like:

enter image description here

Most of the time you only want to set (override) the labels if you want something completely different like category labels. If you want to stick with the actual units on the axis, its better to set the tick positions with (if needed) a custom formatter.

Upvotes: 3

unutbu
unutbu

Reputation: 879601

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

def plot_energy(xvalues, yvalues):
    fig = plt.figure()
    ax = fig.add_subplot(1,1,1)

    ax.scatter(xvalues, yvalues)
    ax.semilogx(xvalues, yvalues, basex = 2)
    ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
    ax.set_xlabel('RUU size')
    ax.set_title("Energy consumption")
    ax.set_ylabel('Energy per instruction (nJ)')
    plt.show()

xvalues = [2, 4, 8, 16, 32, 64, 128, 256]
yvalues = [400139397.517, 339303459.4277, 296846508.2103, 271801897.1163,
           295153640.7553, 323820220.6226, 372099806.9102, 466940449.0719]
plot_energy(xvalues, yvalues)

yields

enter image description here

Upvotes: 2

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