create classes for tests

testing/build_fortran_tests.py

@@ -92,7 +92,7 @@ def clean_cmake_files():
             or file.startswith(".env_mach_specific")
             ):
             os.remove(file)
-            
+
 def get_extra_cmake_args(build_dir:str, mpilib:str) -> str:
     """Makes a fake case to grab the required cmake arguments
     Args:

testing/functional_testing/allometry/allometry_test.py

@@ -1,5 +1,159 @@
-from testing_classes import FunctionalTest
+import os
+import math
+import xarray as xr
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from utils import round_up, get_color_palette, blank_plot
+from testing_classes import Heuristic
 
-class AllometryTest(FunctionalTest):
-    def __init__()
-
+class AllometryTest(Heuristic):
+
+    name = 'allometry'
+
+    def __init__(self, test_dict):
+        super().__init__(AllometryTest.name, test_dict['test_dir'], 
+                         test_dict['test_exe'], test_dict['out_file'], 
+                         test_dict['use_param_file'],
+                         test_dict['other_args'])
+
+    def plot_output(self, run_dir: str, save_figs: bool, plot_dir: str):
+        """Plots all allometry plots
+
+        Args:
+            run_dir (str): run directory
+            out_file (str): output file name
+            save_figs (bool): whether or not to save the figures
+            plot_dir (str): plot directory to save the figures to
+        """
+
+        # read in allometry data
+        allometry_dat = xr.open_dataset(os.path.join(run_dir, self.out_file))
+
+        plot_dict = {
+          'height': {
+            'varname': 'height',
+            'units': 'm',
+            },
+          'bagw': {
+            'varname': 'aboveground biomass',
+            'units': 'kgC',
+            },
+          'blmax': {
+            'varname': 'maximum leaf biomass',
+            'units': 'kgC',
+            },
+          'crown_area': {
+            'varname': 'crown area',
+            'units': 'm$^2$',
+            },
+          'sapwood_area': {
+            'varname': 'sapwood area',
+            'units': 'm$^2$',
+            },
+          'bsap': {
+            'varname': 'sapwood biomass',
+            'units': 'kgC',
+            },
+          'bbgw': {
+            'varname': 'belowground biomass',
+            'units': 'kgC',
+            },
+          'fineroot_biomass': {
+            'varname': 'fineroot biomass',
+            'units': 'kgC',
+            },
+          'bstore': {
+            'varname': 'storage biomass',
+            'units': 'kgC',
+            },
+          'bdead': {
+            'varname': 'deadwood biomass',
+            'units': 'kgC',
+            },
+          'total_biomass_parts': {
+            'varname': 'total biomass (calculated from parts)',
+            'units': 'kgC',
+            },
+          'total_biomass_tissues': {
+            'varname': 'total biomass (calculated from tissues)',
+            'units': 'kgC',
+            },
+
+        }
+        for plot, attributes in plot_dict.items():
+            self.plot_allometry_var(allometry_dat[plot], attributes['varname'],
+                              attributes['units'], save_figs, plot_dir)
+
+        self.plot_total_biomass(allometry_dat, save_figs, plot_dir)
+
+    @staticmethod
+    def plot_allometry_var(data: xr.Dataset, varname: str, units: str, 
+                           save_fig: bool, plot_dir :str=None):
+        """Plot an allometry variable
+
+        Args:
+            data (xarray DataArray): the data array of the variable to plot
+            var (str): variable name (for data structure)
+            varname (str): variable name for plot labels
+            units (str): variable units for plot labels
+            save_fig (bool): whether or not to write out plot
+            plot_dir (str): if saving figure, where to write to
+        """
+        data_frame = pd.DataFrame({'dbh': np.tile(data.dbh, len(data.pft)),
+                          'pft': np.repeat(data.pft, len(data.dbh)),
+                          data.name: data.values.flatten()})
+
+        max_dbh = data_frame['dbh'].max()
+        max_var = round_up(data_frame[data.name].max())
+
+        blank_plot(max_dbh, 0.0, max_var, 0.0, draw_horizontal_lines=True)
+
+        pfts = np.unique(data_frame.pft.values)
+        colors = get_color_palette(len(pfts))
+        for rank, pft in enumerate(pfts):
+            dat = data_frame[data_frame.pft == pft]
+            plt.plot(dat.dbh.values, dat[data.name].values, lw=2, color=colors[rank],
+                    label=pft)
+
+        plt.xlabel('DBH (cm)', fontsize=11)
+        plt.ylabel(f'{varname} ({units})', fontsize=11)
+        plt.title(f"Simulated {varname} for input parameter file", fontsize=11)
+        plt.legend(loc='upper left', title='PFT')
+
+        if save_fig:
+            fig_name = os.path.join(plot_dir, f"allometry_plot_{data.name}.png")
+            plt.savefig(fig_name)
+
+    @staticmethod
+    def plot_total_biomass(data: xr.Dataset, save_fig: bool, plot_dir: str):
+        """Plot two calculations of total biomass against each other
+
+        Args:
+            data (xarray DataSet): the allometry dataset
+        """
+        data_frame = pd.DataFrame({'dbh': np.tile(data.dbh, len(data.pft)),
+                          'pft': np.repeat(data.pft, len(data.dbh)),
+                          'total_biomass_parts': data.total_biomass_parts.values.flatten(),
+                          'total_biomass_tissues': data.total_biomass_tissues.values.flatten()})
+
+        max_biomass = np.maximum(data_frame['total_biomass_parts'].max(),
+                                data_frame['total_biomass_tissues'].max())
+
+        blank_plot(max_biomass, 0.0, max_biomass, 0.0, draw_horizontal_lines=False)
+
+        pfts = np.unique(data_frame.pft.values)
+        colors = get_color_palette(len(pfts))
+        for rank, pft in enumerate(pfts):
+            data = data_frame[data_frame.pft == pft]
+            plt.scatter(data.total_biomass_parts.values, data.total_biomass_parts.values,
+                    color=colors[rank], label=pft)
+
+        plt.xlabel('Total biomass (kgC) from parts', fontsize=11)
+        plt.ylabel('Total biomass (kgC) from tissues', fontsize=11)
+        plt.title("Simulated total biomass for input parameter file", fontsize=11)
+        plt.legend(loc='upper left', title='PFT')
+
+        if save_fig:
+            fig_name = os.path.join(plot_dir, "allometry_plot_total_biomass_compare.png")
+            plt.savefig(fig_name)