************************** Ensemble spread-skill plot ************************** Description =========== The theory is that RMSE of the ensemble mean should have roughly a 1-1 relationship with the ensemble spread (I.e. standard deviation of the ensemble member values). Ensemble spread-skill plot measures that relationship. Example ======= Sample Data ----------- The data is text output from MET in columnar format. The sample data used to create an example Ensemble spread-skill plot is available in the METplotpy repository, where the Ensemble spread-skill plot tests are located: *$METPLOTPY_BASE/metplotpy/test/ens_ss/ens_ss.data* *$METPLOTPY_BASE* is the directory where the METplotpy code is saved: e.g. */usr/path/to/METplotpy* if the source code was cloned or forked from the Github repository or */usr/path/to/METplotpy-x.y.z* if the source code was downloaded as a zip or gzip'd tar file from the Release link of the Github repository. The *x.y.z* is the release number. Configuration Files ___________________ The Ensemble spread-skill plot utilizes YAML configuration files to indicate where input data is located and to set plot attributes. These plot attributes correspond to values that can be set via the METviewer tool. YAML is a recursive acronym for "YAML Ain't Markup Language" and according to `yaml.org `_, it is a "human-friendly data serialization language". It is commonly used for configuration files and in applications where data is being stored or transmitted. Two configuration files are required. The first is a default configuration file, **ens_ss_defaults.yaml**, which is found in the *$METPLOTPY_BASE/metplotpy/plots/config* directory. All default configuration files are located in the *$METPLOTPY_BASE/metplotpy/plots/config* directory. $METPLOTPY_BASE is the user-specified directory where the METplotpy source code has been saved. **Default configuration files are automatically loaded by the plotting code and do not need to be explicitly specified when generating a plot**. The second required YAML configuration file is a user-supplied "custom" configuration file that is used to customize/override the default settings in the **ens_ss_defaults.yaml** file. The custom configuration file can be an empty file if all default settings are to be applied. METplus Configuration ===================== Default Configuration File -------------------------- The following is the *mandatory*, **ens_ss_defaults.yaml** configuration file, which serves as a good starting point for creating a line plot as it represents the default values set in METviewer. .. literalinclude:: ../../metplotpy/plots/config/ens_ss_defaults.yaml In the default config file, logging is set to stdout and the log level is ERROR (i.e. only log messages of type ERROR will be logged). If the log_filename and log_level are not specified in the custom configuration file, these settings will be used. Custom Configuration File ------------------------- A second, *mandatory* configuration file is required, which is used to customize the settings to the plot. The **custom_ens_ss.yaml** file is included with the source code. If the user wishes to use all the default settings defined in the **ens_ss_defaults.yaml** file, an empty custom configuration file can be specified instead. .. literalinclude:: ../../test/ens_ss/custom_ens_ss.yaml Copy this custom config file from the directory where the source code was saved to the working directory: .. code-block:: ini cp $METPLOTPY_BASE/test/ens_ss/custom_ens_ss.yaml $WORKING_DIR/custom_ens_ss.yaml Modify the *stat_input* setting in the *$METPLOTPY_BASE/test/ens_ss/custom_ens_ss.yaml* file to explicitly point to the *$METPLOTPY_BASE/test/ens_ss* directory (where the custom config files and sample data reside). Replace the relative path, *./ens_ss.data*, with the full path, *$METPLOTPY_BASE/test/ens_ss/ens_ss.data* (including replacing *$METPLOTPY_BASE* with the full path to the METplotpy installation on the system). Modify the *plot_filename* setting to point to the directory of the plot, using the full path, including the name of the plot. For example: *stat_input: /username/myworkspace/METplotpy/test/ens_ss/ens_ss.data* *plot_filename: /username/working_dir/output_plots/ens_ss.png* This is where */username/myworkspace/METplotpy* is $METPLOTPY_BASE and */username/working_dir* is $WORKING_DIR. Make sure that the $WORKING_DIR directory that is specified exists and has the appropriate read and write permissions. The path listed for *plot_filename* may be changed to the output directory of one’s choosing. If this is not set, then the plot_filename setting specified in the *$METPLOTPY_BASE/metplotpy/plots/config/ens_ss_defaults.yaml* configuration file will be used. To save the intermediate **.points1** file (used by METviewer and useful for debugging), set the *dump_points_1* setting to True. Uncomment or add (if it doesn't exist) the *points_path* setting. For example: *dump_points_1: 'True'* *points_path: '/dir_to_save_points1_file'* Replace the */dir_to_save_points1_file* to the directory where the **.points1** file is saved. If points_path is commented out (indicated by a '#' symbol in front of it), remove the '#' symbol to uncomment the points_path so that it will be used by the code. Make sure that this directory exists and has the appropriate read and write permissions. **NOTE**: the *points_path* setting is **optional** and does not need to be defined unless saving the intermediate **.points1** file is desired. To save the log output to a file, uncomment the *log_filename* entry and specify the path and name of the log file. Select a directory with the appropriate read and write privileges. To modify the verbosity of logging than what is set in the default config file, uncomment the *log_level* entry and specify the log level (debug and info are higher verbosity, warning and error are lower verbosity). Run from the Command Line ========================= The **custom_ens_ss.yaml** configuration file, in combination with the **ens_ss_defaults.yaml** configuration file, generates the following plot: .. image:: figure/ens_ss.png Perform the following: * If the conda environment is being used, verify the conda environment is running and has has the required Python packages outlined in the `requirements section. `_ * Set the METPLOTPY_BASE environment variable to point to *$METPLOTPY_BASE*. For the ksh environment: .. code-block:: ini export METPLOTPY_BASE=$METPLOTPY_BASE For the csh environment: .. code-block:: ini setenv METPLOTPY_BASE $METPLOTPY_BASE Recall that *$METPLOTPY_BASE* is the directory path indicating where the METplotpy source code was saved. * Enter the following command: .. code-block:: ini python $METPLOTPY_BASE/metplotpy/plots/ens_ss.py $WORKING_DIR/custom_ens_ss.yaml * An **ens_ss.png** output file will be created in the directory specified in the *plot_filename* configuration setting in the **custom_ens_ss.yaml** configuration file.