# 8. Weather Regime plot

## 8.1. Description

The plot_weather_regime.py script contains the plotting portion for 3 scripts (elbow.py, Calc_EOF.py, and K_means.py) that were originally created Doug Miller at the script created by Univerity of Illinois. A METplus use case illustrates how to use this plot:

## 8.3. Description

The plot_weather_regime.py script contains the plotting portion for 3 scripts (elbow.py, Calc_EOF.py, and K_means.py) that were originally created Doug Miller at the script created by Univerity of Illinois.

These files are used by the image comparison test:

• obs_elbow.png

is the plot that should be generated when you run plot_elbow in plot_weather_regime.py

• obs_eof.png

is the plot that should be generated when you run plot_eof in plot_weather_regime.py

• obs_kmeans.png

is the plot that should be generated when you run plot_K_means in plot_weather_regime.py

## 8.4. How to Use

Import plot_weather_regime in your script like so:

`import plot_weather_regime as pwr`

For plot_elbow

In your code, generate the following as numpy arrays (except K, pot_title, and output_plotname):

K:

a range beginning at 1 and ending with the number of clusters used in the weather regime analysis

d:

a numpy array containing the differences between the curve and the line

mi:

a numpy array containing the location of the maximum distance

line:

a numpy array representing the straight line from the sum of squared difference for all clusters

curve:

a numpy array containing the actual values of sum of squared distances

plot_title:

A string that gives the name of the title of the plot

output_plotname:

The full path and filename of the output plot file, a .png version is written

For plot_eof

In your code, generate the following as numpy arrays (except wrnum, output_plotname, and plevels):

eof:

a numpy array containing the first 10 eof values

wrnum:

an integer giving the number of weather regimes

variance_fractions:

a numpy array containing the fractions of the total variance accounted for by each EOF mode

lons:

a numpy array of the longitude values under consideration

lats:

a numpy array of the latitude values under consideration

output_plotname:

The full path and filename of the output plot file, a .png version is written

plevels:

a list containing integers of the contour levels used in the plots

For plot_K_means

In your code, generate the following as numpy arrays (except wrnum, output_plotname, and plevels):

inputi:

a numpy array containing the K means for the weather regime classification

wrnum:

an integer giving the number of weather regimes

lons:

a numpy array of the longitude values under consideration

lats:

a numpy array of the latitude values under consideration

perc:

a numpy array of the size wrnum containing the frequency of occurrence of each cluster

output_plotname:

The full path and filename of the output plot file, a .png version is written

plevels:

a list containing integers of the contour levels used in the plots

Invoke the plotting functions

`pwr.plot_elbow(K,d,mi,line,curve,plot_title,plot_outname)`

`pwr.plot_eof(eof,wrnum,variance_fractions,lons,lats,plot_outname,plevels)`

`pwr.plot_K_means(kmeans,wrnum,lons,lats,perc,plot_outname,plevels)`

Output

A .png version of the elbow line plot, eof contour map plots, and weather regime map plots if all three are requeste. The output will be located based on what you specified (path and name) in the output_plotname.