add quadratic test; refactor to allow picking which test to run

CMakeLists.txt

@@ -87,4 +87,5 @@ link_directories(${CMAKE_CURRENT_BINARY_DIR})
 # has tests in it. However, it appears that the order needs to be done
 # carefully: for example, include_directories and link_directories needs to be
 # done before adding the tests themselves.
-add_subdirectory(${HLM_ROOT}/src/fates/functional_unit_testing/allometry fates_allom_test)
+add_subdirectory(${HLM_ROOT}/src/fates/functional_unit_testing/allometry fates_allom_test)
+add_subdirectory(${HLM_ROOT}/src/fates/functional_unit_testing/math_utils fates_math_test)

functional_unit_testing/CMakeLists.txt

@@ -1 +1,2 @@
-add_subdirectory(allometry)
+add_subdirectory(allometry)
+add_subdirectory(math_utils)

functional_unit_testing/allometry/AllometryUtils.py

@@ -0,0 +1,179 @@
+"""Utility functions for allometry functional unit tests
+"""
+import os
+import math
+import pandas as pd
+import numpy as np
+import xarray as xr
+import matplotlib
+import matplotlib.pyplot as plt
+from utils import get_color_pallete, round_up
+
+def plot_allometry_var(data, varname, units, save_fig, plot_dir=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
+    """
+    df = pd.DataFrame({'dbh': np.tile(data.dbh, len(data.pft)),
+                       'pft': np.repeat(data.pft, len(data.dbh)),
+                       data.name: data.values.flatten()})
+
+    maxdbh = df['dbh'].max()
+    maxvar = round_up(df[data.name].max())
+
+    colors = get_color_pallete()
+
+    plt.figure(figsize=(7, 5))
+    ax = plt.subplot(111)
+    ax.spines["top"].set_visible(False)
+    ax.spines["bottom"].set_visible(False)
+    ax.spines["right"].set_visible(False)
+    ax.spines["left"].set_visible(False)
+
+    ax.get_xaxis().tick_bottom()
+    ax.get_yaxis().tick_left()
+
+    plt.xlim(0.0, maxdbh)
+    plt.ylim(0.0, maxvar)
+
+    plt.yticks(fontsize=10)
+    plt.xticks(fontsize=10)
+
+    inc = (int(maxvar) - 0)/20
+    for i in range(0, 20):
+        y = 0.0 + i*inc
+        plt.plot(range(math.floor(0), math.ceil(maxdbh)),
+                  [y] * len(range(math.floor(0), math.ceil(maxdbh))),
+                  "--", lw=0.5, color="black", alpha=0.3)
+
+    plt.tick_params(bottom=False, top=False, left=False, right=False)
+
+    pfts = np.unique(df.pft.values)
+    for rank, pft in enumerate(pfts):
+        dat = df[df.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_{var}.png")
+        plt.savefig(fig_name)
+
+def plot_total_biomass(data, save_fig, plot_dir):
+    """Plot two calculations of total biomass against each other
+
+    Args:
+        data (xarray DataSet): the allometry dataset
+    """
+    df = 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()})
+
+    colors = get_color_pallete()
+
+    plt.figure(figsize=(7, 5))
+    ax = plt.subplot(111)
+    ax.spines["top"].set_visible(False)
+    ax.spines["bottom"].set_visible(False)
+    ax.spines["right"].set_visible(False)
+    ax.spines["left"].set_visible(False)
+
+    ax.get_xaxis().tick_bottom()
+    ax.get_yaxis().tick_left()
+
+    maxbiomass = np.maximum(df['total_biomass_parts'].max(), df['total_biomass_tissues'].max())
+
+    plt.xlim(0.0, maxbiomass)
+    plt.ylim(0.0, maxbiomass)
+
+    plt.yticks(fontsize=10)
+    plt.xticks(fontsize=10)
+    plt.tick_params(bottom=False, top=False, left=False, right=False)
+
+    pfts = np.unique(df.pft.values)
+    for rank, pft in enumerate(pfts):
+        data = df[df.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)
+
+def plot_allometry_dat(run_dir, out_file, save_figs, plot_dir):
+
+    # read in allometry data
+    allometry_dat = xr.open_dataset(os.path.join(run_dir, 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 in plot_dict:
+        plot_allometry_var(allometry_dat[plot], plot_dict[plot]['varname'],
+                           plot_dict[plot]['units'], save_figs, plot_dir)
+
+    plot_total_biomass(allometry_dat, save_figs, plot_dir)

functional_unit_testing/allometry/CMakeLists.txt

@@ -16,13 +16,8 @@ link_directories(${NETCDF_C_DIR}/lib
 add_executable(FATES_allom_exe ${allom_sources})
 
 target_link_libraries(FATES_allom_exe
-                  netcdf 
+                  netcdf
                   netcdff
                   fates
                   csm_share
-                  funit)
-
-add_test(allom_test FATES_allom_exe)
-
-# Tell CTest how to figure out that "STOP 1" fails for the current
-define_Fortran_stop_failure(allom_test)
+                  funit)