METplotpy

jpresto Wed, 04/06/2022 - 11:53

Histogram

Histogram Overview:

The histogram source code is located in the https://github.com/dtcenter/METplotpy repository, under the METplotpy/metplotpy/plots/histogram directory. Custom configuration files and sample data are located under the METplotpy/test/histogram directory.

There are three specialized histogram plots available:

Rank Histogram
Relative Frequency Histogram
Probability Histogram

Detailed information about these plots is available from Read the Docs:

https://metplotpy.readthedocs.io/en/latest/Users_Guide/histogram.html

These instructions are relevant for generating the rank histogram from the command line. For METplotpy version 2.0, development was performed with Python 3.8 and related third-party packages (i.e. Python packages outside the Python standard library).

Each histogram plot requires two configuration files, a default and custom configuration file in YAML (https://yaml.org/). One default configuration file is used for all three histogram plots: histogram_defaults.yaml. This default configuration file is automatically loaded by the source code. The custom configuration file is useful for overriding the default settings in the histogram_defaults.yaml configuration file. If the user chooses to use all the settings in the default configuration file, an empty custom configuration file can be provided (however, the user will have the sample data and output plot located in the specified directories set in the default configuration file- some users may not have permission to do this) . The custom configuration files and sample data are located in the METplotpy/test/histogram directory of the downloaded/cloned source code.

Set up pre-requisites:

The Python requirements for METplotpy are found in the User's Guide, under the Installation section

METcalcpy is a requirement for METplotpy. The following description is one of numerous methods to set up the working environment to utilize METcalcpy from the METplotpy source code. These instructions are suitable for users that are not working within a conda environment:

Clone the METcalcpy repository to a directory where you have read/write permissions (replace /path/to/code with the full path to where you are saving the METcalcpy source code):

mkdir /path/to/code

cd /path/to/code

git clone https://github.com/dtcenter/METcalcpy

The following instructions are for users who have permission to create, modify, and use conda environments (skip if you already set the PYTHONPATH above). Select either Method 1 or Method 2:

Method 1: Follow instructions in Section 1.1.2 of the Installation section of the METplotpy User's Guide
Method 2: Using using PyPI (Python Package Index) enter the following:

pip install metcalcpy==2.0.1

Clone the METplotpy repository to a directory where you have read/write permissions (replace /path/to/code with the full path to where you are saving the METplotpy source code):

cd /path/to/code

git clone https://github.com/dtcenter/METplotpy

Create the Rank Histogram plot:

Overview of steps:

create a WORKING_DIR where you have read/write permissions
set the PYTHONPATH, WORKING_DIR, and METPLOTPY_BASE environments
copy the histogram data to the WORKING_DIR
copy the custom configuration for the rank histogram to the WORKING_DIR
modify the location of the input data and output plot in the custom configuration file
run the Python script to generate the rank histogram plot

Create the working directory where you have read/write permissions:

mkdir -p /path/to/working_dir/histogram

replace /path/to/working_dir with the path leading to the working directory.

Set the PYTHONPATH, METPLOTPY_BASE, and WORKING_DIR environment variables. If you used Method 1 above:

csh:

setenv PYTHONPATH /path/to/METcalcpy:/path/to/METcalcpy/metcalcpy:/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

setenv METPLOTPY_BASE /path/to/METplotpy

setenv WORKING_DIR /path/to/working_dir/histogram

bash:

export PYTHONPATH=/path/to/METcalcpy:/path/to/METcalcpy/metcalcpy:/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

export METPLOTPY_BASE=/path/to/METplotpy

export WORKING_DIR=/path/to/working_dir/histogram

If you installed METcalcpy using Method 2 above (i.e. PyPI and pip), then set the PYTHONPATH without the METcalcpy paths:

csh:

setenv /path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

setenv METPLOTPY_BASE /path/to/METplotpy

setenv WORKING_DIR /path/to/working_dir/histogram

bash:

export PYTHONPATH=/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

export METPLOTPY_BASE=/path/to/METplotpy

export WORKING_DIR=/path/to/working_dir/histogram

Copy data and custom config file to WORKING_DIR:

cp $METPLOTPY_BASE/test/histogram/rank_hist.data $WORKING_DIR

cp $METPLOTPY_BASE/test/histogram/rank_hist.yaml $WORKING_DIR

cd $WORKING_DIR

Modify custom configuration file:

Open the rank_hist.yaml file in a text editor of your choice. Modify the stat_input and plot_filename to point explicitly to the location of the input data you copied and the name and location of the output plot:

stat_input: /path/to/working_dir/histogram/rank_hist.data

plot_filename: /path/to/working_dir/histogram/rank_hist.png

Save and close the rank_hist.yaml file.

Generate the rank histogram plot:

python $METPLOTPY_BASE/metplotpy/plots/histogram/rank_hist.py $WORKING_DIR/rank_hist.yaml

In your WORKING_DIR, you will now see a rank_hist.png file. You can view the png file using an appropriate viewer, such as 'display' if on a Linux/Unix host:

cd $WORKING_DIR

display rank_hist.png

Your histogram will look like the following:

Create the Relative Frequency Histogram and Probability Histogram

Repeat the steps for the rank histogram, except copy the following to the WORKING_DIR:

Relative frequency histogram:

cp $METPLOTPY_BASE/test/histogram/rel_hist.data $WORKING_DIR

cp $METPLOTPY_BASE/test/histogram/rel_hist.yaml $WORKING_DIR

Probability histogram:

cp $METPLOTPY_BASE/test/histogram/prob_hist.data $WORKING_DIR

cp $METPLOTPY_BASE/test/histogram/prob_hist.yaml $WORKING_DIR

Make the same modifications in the rel_hist.yaml and prob_hist.yaml files to the stat_input and plot_filename settings.

Relative frequency histogram:

stat_input: /path/to/working_dir/histogram/rel_hist.data

plot_filename: /path/to/working_dir/histogram/rel_hist.png

Probability histogram:

stat_input: /path/to/working_dir/histogram/prob_hist.data

plot_filename: /path/to/working_dir/histogram/prob_hist.png

Generate the Relative Frequency and Probability Histogram plots using these Python scripts:

Relative frequency histogram:

python $METPLOTPY_BASE/metplotpy/plots/histogram/rel_hist.py $WORKING_DIR/rel_hist.yaml

Probability histogram:

python $METPLOTPY_BASE/metplotpy/plots/histogram/prob_hist.py $WORKING_DIR/prob_hist.yaml

You will see the rel_hist.png and prob_hist.png files in your WORKING_DIR. Your plots will look like the following:

Relative Frequency Histogram:

Probability Histogram:

jpresto Wed, 04/06/2022 - 11:54

Wind Rose

Wind Rose Overview

The wind rose diagram source code is located in the https://github.com/dtcenter/METplotpy repository, under the METplotpy/metplotpy/plots/wind_rose directory. Custom configuration files and sample data are located under the METplotpy/test/wind_rose directory.

Detailed information about the wind rose diagram is available from Read the Docs:

https://metplotpy.readthedocs.io/en/latest/Users_Guide/wind_rose.html

These instructions are relevant for generating the wind rose diagram from the command line. For METplotpy version 2.0, development was performed with Python 3.8 and related third-party packages (i.e. Python packages outside the Python standard library).

The wind rose diagram requires two configuration files, a default and custom configuration file in YAML (https://yaml.org/). The default configuration file is automatically loaded by the source code. The custom configuration file is useful for overriding the default settings in the wind_rose_defaults.yaml configuration file. If the user chooses to use all the settings in the default configuration file, an empty custom configuration file can be provided (however, the user will have the sample data and output plot located in the directories specified in the default configuration file. Some users may not have permission to do this) . The custom configuration files and sample data are located in the METplotpy/test/wind_rose directory of the downloaded/cloned source code. The default configuration file, wind_rose_defaults.yml is located in the METplotpy/metplotpy/plots/config directory.

Set up pre-requisites:

The Python requirements for METplotpy are found in the User's Guide, under the Installation section

Clone the METcalcpy repository to a directory where you have read/write permissions (replace /path/to/code with the full path to where you are saving the METcalcpy source code):

mkdir /path/to/code

cd /path/to/code

git clone https://github.com/dtcenter/METcalcpy

The following instructions are for users who have permission to create, modify, and use conda environments (skip if you already set the PYTHONPATH above). Select either Method 1 or Method 2:

Method 1: Follow instructions in Section 1.1.2 of the Installation section of the METplotpy User's Guide
Method 2: Using using PyPI (Python Package Index) enter the following:

pip install metcalcpy==2.0.1

Clone the METplotpy repository to a directory where you have read/write permissions (replace /path/to/code with the full path to where you are saving the METplotpy source code):

cd /path/to/code

git clone https://github.com/dtcenter/METplotpy

Create the Wind Rose diagram:

Overview of steps:

create a WORKING_DIR where you have read/write permissions
set the PYTHONPATH, WORKING_DIR, and METPLOTPY_BASE environments
copy the wind rose sample data to the WORKING_DIR
copy the wind rose custom configuration file to the WORKING_DIR
modify the location of the input data and output plot in the custom configuration file
run the Python script to generate the wind rose diagram

Create the working directory where you have read/write permissions:

mkdir -p /path/to/working_dir/wind_rose

Replace /path/to/working_dir with the full path to the working directory.

Set the PYTHONPATH, METPLOTPY_BASE, and WORKING_DIR environment variables. If you used Method 1 above:

csh:

setenv PYTHONPATH /path/to/METcalcpy:/path/to/METcalcpy/metcalcpy:/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

setenv METPLOTPY_BASE/path/to/METplotpy

setenv WORKING_DIR /path/to/working_dir/wind_rose

bash:

export PYTHONPATH=/path/to/METcalcpy:/path/to/METcalcpy/metcalcpy:/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

export METPLOTPY_BASE=/path/to/METplotpy

export WORKING_DIR=/path/to/working_dir

If you installed METcalcpy using Method 2 above (i.e. PyPI and pip), then set the PYTHONPATH without the METcalcpy paths:

csh:

setenv PYTHONPATH /path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

setenv METPLOTPY_BASE /path/to/METplotpy

setenv WORKING_DIR /path/to/working_dir/wind_rose

bash:

export PYTHONPATH=/path/to/METplotpy:/path/to/METplotpy/metplotpy:/path/to/METplotpy/metplotpy/plots

export METPLOTPY_BASE=/path/to/METplotpy

export WORKING_DIR=/path/to/working_dir/wind_rose

Copy data and custom config file to WORKING_DIR:

cp $METPLOTPY_BASE/test/wind_rose/point_stat_mpr.txt $WORKING_DIR

cp $METPLOTPY_BASE/test/wind_rose/wind_rose_custom.yaml $WORKING_DIR

cd $WORKING_DIR

Modify the custom configuration file:

Open the wind_rose_custom.yaml file in a text editor of your choice. Modify the stat_input and plot_filename to point explicitly to the location of the input data you copied and the name and location of the output plot:

stat_input: /path/to/working_dir/wind_rose/point_stats_mpr.txt

plot_filename: /path/to/working_dir/wind_rose/wind_rose_custom.png

Save and close the wind_rose_custom.yaml file.

Generate the wind rose diagram:

python $METPLOTPY_BASE/metplotpy/plots/wind_rose/wind_rose.py $WORKING_DIR/wind_rose_custom.yaml

In your WORKING_DIR, you will now see a wind_rose_custom.png file. You can view the png file using an appropriate viewer, such as 'display' if on a Linux/Unix host:

cd $WORKING_DIR

display wind_rose_custom.png

Your wind rose diagram will look like the following:

jpresto Wed, 04/06/2022 - 11:55