Skip to main content

A tool used for plotting and comparing separate EnergyPlus output CSV files.

Project description

CSV Compare

This is a very basic tool used for plotting and comparing csv data from two separate csv files.

Usage

A version of the jupyter notebook is hosted at mybinder.org

How is this used?

  1. Open the binder (https://mybinder.org/v2/gh/mitchute/energyplus-diff-analysis/main). This may take a few minutes to build and load the container images running behind the scenes. Once completed, mybinder.org will launch the jupyter dashboard in your web browser. This looks like a file explorer.
  2. Launch the "Make_Plots.ipynb" jupyter notebook by clicking on it from the jupyter dashboard. This will launch a new tab in your browser with this notebook loaded and running.
  3. Upload your data by clicking "upload" from the jupyter dashboard. For example, you could upload and name your baseline csv file "base.csv", and your modified version csv "mod.csv".
  4. Back over on the "Make_Plots" jupyter notebook, update the names of your baseline and modified csv data files to match what you uploaded.
  5. Select how you want your data plotted. See the examples section below for additional information.
  6. To execute, you can select Cell >> Run All (or other available options). You can also run individual cells with the "shift+return" command."

Examples

Example 1 - Plotting all columns with diffs

As described, this plots all columns

plot(baseline_path, mod_path, output_path)

Example 2 - Plot only one series

If you only want to plot a single column from the csv data, the column name can be passed explicitly to the cols field.

plot(baseline_path, mod_path, output_path, cols="Col Name 1")

Example 3 - Plot a selected set of columns from the csv data

The cols field also accepts a list input for when you want to plot more than one column, but not all of them.

plot(baseline_path, mod_path, output_path, cols=["Col Name 1", "Col Name 2"])

Example 4 - Plot one series for a specified number of rows

You may also specify the range of rows you want to plot.

plot(baseline_path, mod_path, output_path, cols="Col Name 1", low_row_num=10, high_row_num=20)

Example 5 - Only plot files with diffs

To plot all files with including files without diffs, you can add the plot_all_series flag and set it to True.

plot(baseline_path, mod_path, output_path, plot_all_series=True)

Example 6 - Zip plots

You can also zip your plots once plotting is complete for easier downloading.

plot(baseline_path, mod_path, output_path, create_archive=True)

Command Line Interface

There's also a command line interface.

$ energyplus_diffs --help
Usage: eplus-diff [OPTIONS] BASELINE_CSV MODIFIED_CSV OUTPUT_DIR

Options:
  -p, --plot-all-series  Plot all series including series without diffs
  -a, --create-archive   Create archive of plots afterwards
  --help                 Show this message and exit.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

energyplus_diff_analysis-0.2.tar.gz (6.4 kB view hashes)

Uploaded Source

Built Distribution

energyplus_diff_analysis-0.2-py3-none-any.whl (7.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page