Visualizing Errors

Visualizing Errors

• Error bars are included in Matplotlib line plots and graphs. Error is the difference between the calculated value and actual value.

• Without error bars, bar graphs provide the perception that a measurable or determined number is defined to a high level of efficiency. The method matplotlib.pyplot.errorbar() draws y vs. x as planes and/or indicators with error bars associated.

• Adding the error bar in Matplotlib, Python. It's very simple, we just have to write the value of the error. We use the command:

           plt.errorbar(x, y, yerr = 2, capsize=3)

Where:

x = The data of the X axis.

Y = The data of the Y axis.

yerr = The error value of the Y axis. Each point has its own error value.

xerr = The error value of the X axis.

capsize = The size of the lower and upper lines of the error bar

• A simple example, where we only plot one point. The error is the 10% on the Y axis.

importmatplotlib.pyplot as plt

x = 1

y = 20

y_error = 20*0.10  ## El 10% de error

plt.errorbar(x,y, yerr = y_error, capsize=3)

plt.show()

Output:

• We plot using the command "plt.errorbar (...)", giving it the desired characteristics.

importmatplotlib.pyplot as plt

importnumpy as np

x = np.arange(1,8)

y = np.array([20,10,45,32,38,21,27])

y_error = y * 0.10   ##El 10%

plt.errorbar(x, y, yerr = y_error,

linestyle="None", fmt="ob", capsize=3, ecolor="k")

plt.show()

• Parameters of the  errorbar :

a) yerr is the error value in each point.

b) linestyle, here it indicate that we will not plot a line.

c) fmt, is the type of marker, in this case is a point ("o") blue ("b").

d) capsize, is the size of the lower and upper lines of the error bar.

e) ecolor, is the color of the error bar. The default color is the marker color. 

Output:

• Multiple lines in MatplotlibErrorbar in Python : The ability to draw numerous lines in almost the same plot is critical. We'll draw many errorbars in the same graph by using this scheme.

importnumpy as np

importmatplotlib.pyplot as plt

fig = plt.figure()

x = np.arange(20)

y = 4* np.sin(x / 20 * np.pi)

yerr = np.linspace (0.06, 0.3, 20)

plt.errorbar(x, y + 8, yerr = yerr, )

plt.errorbar(x, y + 6, yerr = yerr,

uplims = True, )

plt.errorbar(x, y + 4, yerr = yerr,

uplims = True,

lolims True, )

upperlimits = [True, False] * 6

lowerlimits = [False, True]* 6

plt.errorbar(x, y, yerr = yerr,

uplims =upperlimits,

lolims = lowerlimits, )

plt.legend(loc='upper left')

plt.title('Example')

plt.show()

Output: