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specmicp/scripts/analyser/short_iter.py
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short_iter.py
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import pandas
import numpy as np
def analyse_file(iter_file, out_file):
df = open_file(iter_file)
with open(out_file, 'w') as out_file:
out_file.write("\n")
analyse_timestep(df, out_file)
analyse_iter(df, out_file)
analyse_cpu_time(df, out_file)
analyse_cpu_transport_time(df, out_file)
analyse_cpu_chemistry_time(df, out_file)
out_file.write("\n")
def open_file(iter_file):
df = pandas.read_csv(iter_file,
header=1, sep="\t\s*",
skiprows=8, skipfooter=14,
skip_blank_lines=False, usecols=range(1,11), index_col=False)
return df
def basic_print(serie, out_file):
out_file.write("mean : {0:.4f}\n".format(serie.mean()))
out_file.write("std : {0:.4f}\n".format(serie.std()))
out_file.write("median : {0:.4f}\n".format(serie.median()))
out_file.write("min : {0:.4f}\n".format(serie.min()))
out_file.write("max : {0:.4f}\n".format(serie.max()))
def analyse_iter(df, out_file):
try:
c_iter = df["Iterations"]
except KeyError:
c_iter = df["Iterations "] # ... format ...
out_file.write("\nIterations\n=========\n")
basic_print(c_iter, out_file)
hist_n, hist_range = np.histogram(c_iter)
out_file.write("\nHistogram : \n")
for i, n in enumerate(hist_n):
out_file.write("{0}\t{1}\n".format(hist_range[i], n))
out_file.write("{0}\t{1}\n".format(hist_range[-1], 0))
def analyse_timestep(df, out_file):
t_time = df["dt"]
out_file.write("Nb timesteps : {0}\n".format(t_time.count()))
out_file.write("\nTimestep\n=========\n")
basic_print(t_time, out_file)
def analyse_cpu_time(df, out_file):
t_time = df["Time"]
out_file.write("\nIteration CPU Time\n=========\n")
basic_print(t_time, out_file)
def analyse_cpu_transport_time(df, out_file):
t_time = df["Transport_time"]
out_file.write("\nIteration CPU Transport Time\n=========\n")
basic_print(t_time, out_file)
def analyse_cpu_chemistry_time(df, out_file):
t_time = df["Chemistry_time"]
out_file.write("\nIteration CPU Chemistry Time\n=========\n")
basic_print(t_time, out_file)
if __name__ == "__main__":
import sys
analyse_file(sys.argv[1], sys.argv[2])
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