Plotting the Model on the Data

Continuing with the same measured data from the previous exercise, your goal is to use a predefined model() and measured data times and measured_distances to compute modeled distances, and then plot both measured and modeled data on the same axis.

context figure

Diese Übung ist Teil des Kurses

Introduction to Linear Modeling in Python

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Anleitung zur Übung

Use model_distances = model(times, measured_distances) to compute the modeled values.
Use plt.subplots() to create figure and axis objects.
Use axis.plot() to plot times vs measured_distances with options linestyle=" ", marker="o", color="black".
Use axis.plot() to also plot times vs model_distances with options linestyle="-", color="red".

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Pass times and measured distances into model
model_distances = model(____, ____)

# Create figure and axis objects and call axis.plot() twice to plot data and model distances versus times
fig, axis = plt.subplots()
axis.plot(____, ____, linestyle="____", marker="____", color="____", label="Measured")
axis.plot(____, ____, linestyle="____", marker=None, color="____", label="Modeled")

# Add grid lines and a legend to your plot, and then show to display
axis.grid(True)
axis.legend(loc="best")
plt.show()

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