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ericvmuellerericvmueller
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Merge pull request #14392 from ericvmueller/catchpole
FDS Validation: add python version of FDS_validation_script; add proc…
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‎Utilities/Python/FDS_validation_script.py‎

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#!$FIREMODELS/fds/.github/fds_python_env/bin/python
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import subprocess
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import fdsplotlib
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import importlib
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importlib.reload(fdsplotlib) # use for development (while making changes to fdsplotlib.py)
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# Scripts to run prior to dataplot
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print("catchpole_spread_rates..."); subprocess.run(["python","./scripts/catchpole_spread_rates.py"])
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# Dataplot and scatplot options
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# Statistics output options
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# Run dataplot and scatplot scripts
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# fdsplotlib.dataplot(config_filename='../Matlab/FDS_verification_dataplot_inputs.csv',
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# expdir='../../Verification/',
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# cmpdir='../../Verification/',
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# pltdir='../../Manuals/',
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# close_figs=True,
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# verbose=True,
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# plot_range=[2])
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# Special cases
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print("Python validation scripts completed successfully!")

‎Utilities/Python/scripts/catchpole_spread_rates.py‎

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import numpy as np
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import matplotlib.pyplot as plt
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import os
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import pandas as pd
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# include FDS plot styles, etc.
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import fdsplotlib
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# Get plot style parameters
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plot_style = fdsplotlib.get_plot_style("fds")
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plt.rcParams['text.usetex'] = True # supports latex math (set per plot below)
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plt.rcParams["pdf.use14corefonts"] = True # forces matplotlib to write native pdf fonts rather than embed
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plt.rcParams["font.family"] = plot_style["Font_Name"]
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plt.rcParams["font.size"] = plot_style["Label_Font_Size"]
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# Define paths
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base_path = "../../../out/USFS_Catchpole/"
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fig_path = "../../Manuals/FDS_Validation_Guide/SCRIPT_FIGURES/USFS_Catchpole/"
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# Experiment parameters
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tests = pd.read_csv("../../Validation/USFS_Catchpole/FDS_Input_Files/Test_Matrix.csv")
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for ti,test in tests.iterrows():
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chid = test['Test']
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fds_file = os.path.join(base_path, f"{chid}_devc.csv")
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git_file = os.path.join(base_path, f"{chid}_git.txt")
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fig_file = os.path.join(fig_path, f"{chid}.pdf")
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if os.path.exists(fds_file) is False:
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print(f'Error: File {fds_file} does not exist. Skipping case.')
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continue
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fds_data = pd.read_csv(fds_file,header=1)
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# fit spread rate
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try:
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# fit slope filtering to positions greater than 2 m from ignition
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R_FDS,intercept = np.polyfit(fds_data[fds_data['x']>2]['Time'],
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fds_data[fds_data['x']>2]['x'], 1) # 1 indicates linear fit (degree 1)
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# not enough data to fit
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except:
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R_FDS=0.
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if R_FDS<0:
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R_FDS=0
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fig, ax = plt.subplots(figsize=(plot_style["Paper_Width"], plot_style["Paper_Height"]))
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# Exp results
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x_exp = np.array([0., 8.])
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t_exp = np.array([0., 8./test['R']])
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ax.plot(t_exp,x_exp,'k-',label='Exp')
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# FDS results
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ax.plot(fds_data['Time'],fds_data['x'],'k--',label='FDS')
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# plot attributes
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ax.set_xlabel("Time (s)",
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fontdict={"fontname": plot_style["Font_Name"],
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"fontsize": plot_style["Label_Font_Size"]})
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ax.set_ylabel("Distance (m)",
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fontdict={"fontname": plot_style["Font_Name"],
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"fontsize": plot_style["Label_Font_Size"]})
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t_end = max(fds_data['Time'].max(),8./test['R'])
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ax.set_xlim([0, t_end])
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ax.set_ylim([0, 8.])
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plt.legend(loc="lower right", fontsize=plot_style["Key_Font_Size"],
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framealpha=1,frameon=True)
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ax.set_title(chid,fontsize=plot_style["Title_Font_Size"],
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loc="left",x=0.05,y=0.9)
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# add version sting
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version_str = fdsplotlib.get_version_string(git_file)
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fdsplotlib.add_version_string(ax, version_str, plot_type='linear')
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fig.tight_layout()
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plt.savefig(fig_file)
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plt.close()
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# write table for dataplot
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test['R_FDS'] = R_FDS
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test = test.drop('Test')
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out_file = os.path.join(base_path,f"{chid}_FDS.csv")
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pd.DataFrame([test]).to_csv(out_file,index=False)
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# add fds data to full table for summary plotting
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tests.loc[ti,'R_FDS'] = R_FDS
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##### Create summary plots
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# variables of interest
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dep_variables={"s":"Surface-to-Volume Ratio (1/m)",
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"beta":"Packing Ratio (-)",
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"U":"Wind Speed (m/s)",
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"M":"FMC (-)"}
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# fuel labels for filtering data
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fuel_labels=["MF","EXSC","PPMC","EX"]
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for dvar in dep_variables:
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fig_file = os.path.join(fig_path, f"Catchpole_R_v_{dvar}.pdf")
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fig, ax = plt.subplots(figsize=(plot_style["Paper_Width"], plot_style["Paper_Height"]))
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# show +/- 20% relative error
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[xmin,xmax] = [tests[dvar].min(),tests[dvar].max()]
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ax.semilogy([xmin,xmax],[0.8,0.8],'k--')
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ax.semilogy([xmin,xmax],[1.2,1.2],'k--')
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for fuel in fuel_labels:
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filtered_data = tests[tests['Test'].str.startswith(fuel)]
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if fuel=='EX':
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filtered_data = tests[
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(tests['Test'].str.startswith(fuel))&(~tests['Test'].str.startswith('EXSC'))]
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ax.semilogy(filtered_data[dvar],filtered_data['R_FDS']/filtered_data['R'],
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'.',label=fuel)
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# plot attributes
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ax.set_xlabel(dep_variables[dvar],
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fontdict={"fontname": plot_style["Font_Name"],
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"fontsize": plot_style["Label_Font_Size"]})
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ax.set_ylabel("$R_{FDS}/R_{Exp}$ (-)",
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fontdict={"fontname": plot_style["Font_Name"],
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"fontsize": plot_style["Label_Font_Size"]})
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plt.legend(fontsize=plot_style["Key_Font_Size"],
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framealpha=1,frameon=True)
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ax.set_xlim([xmin,xmax])
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# add version sting
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version_str = fdsplotlib.get_version_string(git_file)
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fdsplotlib.add_version_string(ax, version_str, plot_type='semilogy')
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plt.tight_layout()
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plt.savefig(fig_file)
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plt.close()
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# plot no-spread conditions
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fig_file = os.path.join(fig_path, "Catchpole_no_spread.pdf")
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fig, ax = plt.subplots(figsize=(plot_style["Paper_Width"], plot_style["Paper_Height"]))
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# dummy column for labeling
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tests['category']='go'
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tests.loc[tests['R_FDS']<1e-5,'category'] = 'no-go'
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# normalize by max and min
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tests_normalized = tests
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tests_normalized[list(dep_variables.keys())] = tests[list(dep_variables.keys())].apply(
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lambda x: (x - x.min()) / (x.max() - x.min()))
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# move M toward the middle of x-axis for more clarity
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tests_normalized=tests_normalized[['category','s','beta','M','U']]
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pd.plotting.parallel_coordinates(tests_normalized, 'category',
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cols=['s','beta','M','U'],
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color=[(1.,0.,0.,1), (0.,0.,0.,.2)],
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ax=ax,
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ls='-')
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ax.set_ylim([0, 1])
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ax.set_yticks([0, 1],['min','max'])
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plt.legend(loc="upper left", fontsize=plot_style["Key_Font_Size"],
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framealpha=1,frameon=True)
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# Show the plot
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plt.tight_layout()
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plt.savefig(fig_file)
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plt.close()
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