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yantoscayantosca
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Moved KPP-Standalone plotting code to gcpy/kpp folder
gcpy/examples/__init__.py - Removed "from ,kpp import*" gcpy/kpp/__init__.py - Added this import script for the gcpy/kpp folder gcpy/kpp/kppsa_utils.py - Moved most of the routines from the former gcpy/examples/kpp/kppsa_visualize.py script here so that they can be reused gcpy/kpp/kppsa_plot_sites.py - Added this script to plot KPP-Standalone box model output (Ref vs. Dev versions) from 500-1000 hPa. Based on the former kppsa_visualize.py script. gcpy/kpp/kppsa_quick_look.py - Added this script to create "quick-look" output from the KPP-Standalone box model output CHANGELOG.md - Updated accordingly Signed-off-by: Bob Yantosca <yantosca@seas.harvard.edu>
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‎CHANGELOG.md‎

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@@ -10,7 +10,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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- Added module `benchmark_gcclassic_stats.py` for scraping statistics from GEOS-Chem Classic cloud benchmarks
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- Added dry deposition velocity comparison plots in 1-month cloud benchmarks
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- Added `gcpy/benchmark/modules/benchmark_species_changes.py` to compute the table of species changes between versions
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- Added `gcpy/examples/kpp/kppsa_visualize.py` script to plot output from the KPP-Standalone box model
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- Added `gcpy/kpp/` folder containing scripts to plot output from the KPP-Standalone box model
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### Changed
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- Changed format of `% diff` column from `12.3e` to `12.3f` in benchmark timing tables

‎gcpy/examples/__init__.py‎

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#from .bpch_to_nc import *
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from .diagnostics import *
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from .dry_run import *
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from .kpp import *
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from .plotting import *
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from .timeseries import *
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from .working_with_files import *

‎gcpy/kpp/__init__.py‎

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"""
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GCPy import script
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"""
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from .kppsa_utils import *
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from .kppsa_quick_look import *
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from .kppsa_plot_sites import *

‎gcpy/kpp/kppsa_plot_sites.py‎

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#!/usr/bin/env python3
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"""
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Script to visualize output from the KPP standalone box model.
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"""
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# Imports
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import argparse
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from matplotlib.backends.backend_pdf import PdfPages
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import matplotlib.pyplot as plt
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from gcpy.util import verify_variable_type
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from gcpy.kpp.kppsa_utils import \
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kppsa_get_file_list, kppsa_get_unique_site_names,\
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kppsa_plot_one_page, kppsa_read_csv_files
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def kppsa_plot_species_at_sites(
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ref_file_list,
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ref_label,
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dev_file_list,
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dev_label,
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species,
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pdfname,
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):
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"""
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TBD
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"""
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verify_variable_type(ref_file_list, list)
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verify_variable_type(ref_label, str)
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verify_variable_type(dev_file_list, list)
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verify_variable_type(dev_label, str)
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verify_variable_type(species, str)
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verify_variable_type(pdfname, str)
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# Read data
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ref_data = kppsa_read_csv_files(ref_file_list)
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dev_data = kppsa_read_csv_files(dev_file_list)
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# Get a list of site names sorted from N to S
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site_names = kppsa_get_unique_site_names(ref_data)
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# Figure setup
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plt.style.use("seaborn-v0_8-darkgrid")
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rows_per_page = 3
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cols_per_page = 2
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plots_per_page = rows_per_page * cols_per_page
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# Open the plot as a PDF document
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if ".pdf" not in pdfname:
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pdfname += ".pdf"
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pdf = PdfPages(f"{pdfname}")
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# Loop over the number of obs sites that fit on a page
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for start in range(0, len(site_names), plots_per_page):
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end = start + plots_per_page - 1
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kppsa_plot_one_page(
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pdf,
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site_names[start:end+1],
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ref_data,
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ref_label,
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dev_data,
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dev_label,
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species,
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rows_per_page,
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cols_per_page,
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font_scale=1.0,
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)
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# Close the PDF file
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pdf.close()
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# Reset the plot style (this prevents the seaborn style from
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# being applied to other model vs. obs plotting scripts)
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plt.style.use("default")
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def main():
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"""
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TBD
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"""
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# Tell the parser which arguments to look for
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parser = argparse.ArgumentParser(
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description="Single-panel plotting example program"
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)
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parser.add_argument(
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"--refdir",
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metavar="REFDIR",
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type=str,
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required=True,
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help="Directory w/ KPP-Standalone log files (Ref version)"
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)
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parser.add_argument(
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"--reflabel",
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metavar="REFLABEL",
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type=str,
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required=False,
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help="Descriptive label for the Ref data",
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default="Ref"
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)
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parser.add_argument(
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"--devdir",
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metavar="DEVDIR",
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type=str,
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required=True,
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help="Directory w/ KPP-Standalone log files (Dev version)"
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)
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parser.add_argument(
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"--devlabel",
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metavar="DEVLABEL",
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type=str,
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required=False,
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help="Descriptive label for the Ref data",
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default="Dev"
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)
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parser.add_argument(
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"--pattern",
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metavar="PATTERN",
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type=str,
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required=False,
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help="Search for file names matching this pattern",
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)
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parser.add_argument(
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"--species",
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metavar="SPECIES",
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type=str,
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required=True,
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help="Species to plot"
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)
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parser.add_argument(
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"--pdfname",
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metavar="PDF-FILE-NAME",
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type=str,
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required=False,
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help="Name of the PDF file to be created",
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default="kppsa_output.pdf"
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)
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# Parse command-line arguments
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args = parser.parse_args()
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# Get a list of KPP-Standalone files matching the criteria (Ref)
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ref_file_list = kppsa_get_file_list(
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args.refdir,
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args.pattern,
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)
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if len(ref_file_list) == 0:
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msg = "Could not find any files matching {pattern} for Ref!"
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raise ValueError(msg)
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dev_file_list = kppsa_get_file_list(
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args.devdir,
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args.pattern,
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)
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if len(ref_file_list) == 0:
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msg = "Could not find any files matching {pattern} for Dev!"
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raise ValueError(msg)
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# Plot data
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kppsa_plot_species_at_sites(
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ref_file_list,
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args.reflabel,
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dev_file_list,
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args.devlabel,
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args.species,
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args.pdfname,
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)
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if __name__ == '__main__':
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main()

‎gcpy/kpp/kppsa_quick_look.py‎

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#!/usr/bin/env python3
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"""
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Creates a "quick-look" plot from KPP-Standalone box model output.
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"""
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# Imports
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import argparse
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import matplotlib.pyplot as plt
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from gcpy.util import verify_variable_type
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from gcpy.kpp.kppsa_utils import \
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kppsa_get_file_list, kppsa_get_unique_site_names, \
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kppsa_plot_single_site, kppsa_prepare_site_data, \
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kppsa_read_csv_files
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def kppsa_make_quick_look_plot(file_list, label, species):
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"""
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Creates a quick-look plot from KPP-Standalone box model output.
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Args
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file_list : list : List of KPP-Standalone log files
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site_name : str : Name of the site that you wish to plot
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label : str : Descriptive label for the data
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species : str : Name of the species that you wish to plot
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"""
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verify_variable_type(file_list, list)
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verify_variable_type(label, str)
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verify_variable_type(species, str)
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# Read data
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dframe = kppsa_read_csv_files(file_list)
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# Get the site name from the DataFrame
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site_name = kppsa_get_unique_site_names(dframe)[0]
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# Get the data for the given species and site
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site_data, site_title = kppsa_prepare_site_data(
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dframe,
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site_name,
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species,
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)
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# Figure setup
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plt.style.use("seaborn-v0_8-darkgrid")
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# Define a new matplotlib.figure.Figure object for this page
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# Landscape width: 11" x 8"
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fig = plt.figure(figsize=(11, 8))
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fig.tight_layout()
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# Figure setup
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plt.style.use("seaborn-v0_8-darkgrid")
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# Plot species vertical profile at a given site
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kppsa_plot_single_site(
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fig,
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rows_per_page=1,
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cols_per_page=1,
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subplot_index=0,
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subplot_title=site_title,
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ref_data=site_data,
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ref_label=label,
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dev_data=None,
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dev_label=None,
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species=species,
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font_scale=2.0,
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)
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# Add top-of-page legend
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plt.legend(
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ncol=3,
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bbox_to_anchor=(0.5, 0.98),
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bbox_transform=fig.transFigure,
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loc='upper center'
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)
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# Show the plot
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plt.show()
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# Reset the plot style (this prevents the seaborn style from
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# being applied to other model vs. obs plotting scripts)
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plt.style.use("default")
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def main():
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"""
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Parses arguments and calls function kppsa_make_quick_look_plot
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to generate a "quick-look" plot from KPP-Standalone box model
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output.
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"""
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# Tell the parser which arguments to look for
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parser = argparse.ArgumentParser(
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description="Single-panel plotting example program"
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)
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parser.add_argument(
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"-d", "--dirname",
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metavar="DIRNAME",
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type=str,
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required=True,
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help="Directory containing KPP-Standalone output files"
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)
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parser.add_argument(
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"-l", "--label",
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metavar="LABEL",
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type=str,
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required=False,
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help="Descriptive label",
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default="KPP-Standalone output"
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)
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parser.add_argument(
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"-p", "--pattern",
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metavar="PATTERN",
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type=str,
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required=False,
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help="Search for file names matching this pattern",
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)
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parser.add_argument(
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"-s", "--species",
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metavar="SPECIES",
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type=str,
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required=True,
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help="Species to plot"
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)
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# Parse command-line arguments
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args = parser.parse_args()
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# Get a list of KPP-Standalone files matching the criteria
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file_list = kppsa_get_file_list(
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args.dirname,
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args.pattern,
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)
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# Create the quick look plot from KPP-Standalone output
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kppsa_make_quick_look_plot(
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file_list,
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args.label,
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args.species
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)
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if __name__ == '__main__':
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main()

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