Unit Conversions with Python Matplotlib

Introduction

This lab will guide you through a step-by-step tutorial on how to perform unit conversions over masked arrays using Python Matplotlib.

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Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL python(("`Python`")) -.-> python/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/PythonStandardLibraryGroup(["`Python Standard Library`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) python/BasicConceptsGroup -.-> python/comments("`Comments`") matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/PlottingDataGroup -.-> matplotlib/scatter_plots("`Scatter Plots`") python/BasicConceptsGroup -.-> python/variables_data_types("`Variables and Data Types`") python/BasicConceptsGroup -.-> python/numeric_types("`Numeric Types`") python/BasicConceptsGroup -.-> python/booleans("`Booleans`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/ModulesandPackagesGroup -.-> python/using_packages("`Using Packages`") python/PythonStandardLibraryGroup -.-> python/data_collections("`Data Collections`") python/DataScienceandMachineLearningGroup -.-> python/numerical_computing("`Numerical Computing`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") subgraph Lab Skills python/comments -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} matplotlib/importing_matplotlib -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} matplotlib/figures_axes -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} matplotlib/scatter_plots -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/variables_data_types -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/numeric_types -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/booleans -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/tuples -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/importing_modules -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/using_packages -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/data_collections -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/numerical_computing -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} python/data_visualization -.-> lab-49018{{"`Python Matplotlib Unit Conversions`"}} end

Import Libraries

In this step, we will import the necessary libraries to perform the unit conversions and plotting.

import matplotlib.pyplot as plt
import numpy as np
from basic_units import hertz, minutes, secs

Create Masked Array

In this step, we will create a masked array and apply the mask to the data.

## create masked array
data = (1, 2, 3, 4, 5, 6, 7, 8)
mask = (1, 0, 1, 0, 0, 0, 1, 0)
xsecs = secs * np.ma.MaskedArray(data, mask, float)

Create Plots

In this step, we will create three plots using the masked array with different units.

## create subplots
fig, (ax1, ax2, ax3) = plt.subplots(nrows=3, sharex=True)

## plot 1
ax1.scatter(xsecs, xsecs)
ax1.yaxis.set_units(secs)

## plot 2
ax2.scatter(xsecs, xsecs, yunits=hertz)

## plot 3
ax3.scatter(xsecs, xsecs, yunits=minutes)

## set labels
ax1.set_ylabel('Seconds')
ax2.set_ylabel('Hertz')
ax3.set_ylabel('Minutes')
ax3.set_xlabel('Time')

Display Plots

In this step, we will display the plots that were created in the previous step.

## display plot
plt.show()

Summary

In this lab, we have learned how to perform unit conversions over masked arrays using Python Matplotlib. We have created a masked array and applied a mask to the data. We have also created three plots using the masked array with different units and displayed them.

Python Matplotlib Unit Conversions