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

Questo esercizio fa parte del corso

Introduction to Linear Modeling in Python

Visualizza il corso

Istruzioni dell'esercizio

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".

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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()

Modifica ed esegui il codice