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https://github.com/OPM/opm-simulators.git
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121 lines
3.9 KiB
Python
Executable File
121 lines
3.9 KiB
Python
Executable File
#!/usr/bin/python3
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# Generates a PDF with plots of all summary curves from a reference
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# case and a 'new' simulation.
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import argparse
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from datetime import datetime, timedelta
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import matplotlib.pyplot as plt
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from matplotlib.dates import DateFormatter
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from matplotlib.backends.backend_pdf import PdfPages
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import numpy as np
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from opm.io.ecl import ESmry
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import os
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import pickle
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from scipy import integrate, stats
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# Run analysis of a test.
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# Calculate the deviation for each curve
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# and generate a pdf with plots ordered according to deviation
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def run_analysis(ref_file_name, sys_file_name, test_name):
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ref_file = ESmry(ref_file_name + '.SMSPEC')
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sim_file = ESmry(sys_file_name + '.SMSPEC')
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ref_time = ref_file.dates()
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sim_time = sim_file.dates()
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ref_time_in_secs = [(v - ref_time[0]).total_seconds() for v in ref_time]
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sim_time_in_secs = [(v - sim_time[0]).total_seconds() for v in sim_time]
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plt.rcParams['font.size'] = 8
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# Attempt at sorting the graphs in descending eyeball norm order.
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# - Normalize by inf-norm to get the same range in each graph, ie (0,1).
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# - Convert graphs to probability distributions (ie integral under curve should be 1).
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# - Use the wasserstein distance scaled by area under reference curve.
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deviation={}
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for r in ref_file.keys():
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if r == 'TIME' or r == 'YEARS':
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continue
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try:
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ref = ref_file[r]
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sim = sim_file[r]
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except:
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continue
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if len(ref) == 0 and len(sim) == 0:
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continue
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if not (any(ref) or any(sim)):
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continue
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ref /= np.linalg.norm(ref, np.inf)
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sim /= np.linalg.norm(sim, np.inf)
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A_ref = integrate.trapezoid(ref, ref_time_in_secs, 0.0)
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A_sim = integrate.trapezoid(sim, sim_time_in_secs, 0.0)
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deviation[r] = stats.wasserstein_distance(ref / A_ref, sim / A_sim) * A_ref
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p = PdfPages(f'{test_name}.pdf')
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for r in sorted(deviation, key = lambda x: deviation[x], reverse=True):
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try:
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ref = ref_file[r]
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sim = sim_file[r]
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except:
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continue
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fig, ax = plt.subplots()
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ax.plot(ref_time, ref, linestyle='dashed', linewidth=0.5, marker='o', markersize=1.0)
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ax.plot(sim_time, sim, linewidth=0.5, marker='x', markersize=1.0)
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ax.legend(['Reference', 'New simulation'])
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plt.title(r)
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u = ref_file.units(r)
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if u:
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plt.ylabel(u)
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myFmt = DateFormatter("%Y-%b")
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ax.xaxis.set_major_formatter(myFmt)
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ax.xaxis.set_major_locator(plt.MaxNLocator(20))
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plt.grid()
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fig.autofmt_xdate()
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fig.savefig(p, format='pdf')
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plt.close(fig)
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p.close()
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if os.path.exists('max_devs.pkl'):
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with open('max_devs.pkl', 'rb') as f:
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max_deviations = pickle.load(f)
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else:
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max_deviations = {}
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max_dev = max(deviation, key = lambda x: deviation[x])
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max_deviations[test_name] = deviation[max_dev]
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with open('max_devs.pkl', 'wb') as f:
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pickle.dump(max_deviations, f)
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# Rename files to rank them according to maximum deviations
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def reorder_files():
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with open('max_devs.pkl', 'rb') as f:
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max_deviations = pickle.load(f)
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c = 1
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for file in sorted(max_deviations, key = lambda x: max_deviations[x], reverse=True):
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os.rename(f'{file}.pdf', f'{c:02d}_{file}.pdf')
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c += 1
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# Main code
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parser = argparse.ArgumentParser('plot_well_comparison.py')
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parser.add_argument('-c', help='Name of test to process', dest='test_name')
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parser.add_argument('-r', help='Reference file', dest='ref_file')
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parser.add_argument('-s', help='Simulation file', dest='sim_file')
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parser.add_argument('-o', choices=['plot', 'rename'], help='Operation to do', required=True, dest='operation')
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args = parser.parse_args()
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if args.operation == 'plot':
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run_analysis(args.ref_file, args.sim_file, args.test_name)
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else:
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reorder_files()
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