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hpc_recombine_additional.py
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hpc_recombine_additional.py
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import os
import en_utilities as um
import pandas as pd
import shutil
import numpy as np
import stat
import subprocess
import en_utilities as um
# Input parameters:
# -----------------
project = 'EN2_x'
study_root = 'xfe8_'
sites = ['J'] # '['F','G','H','I','J']
# Establish paths etc
# -------------------
new_project = project+'_hpc'
base_path = 'C:\\Users\\z5044992\\Documents\\MainDATA\\DATA_EN_4\\studies'
# Paths for hpc outputs
np_path = os.path.join(base_path, new_project)
if not os.path.exists(np_path):
os.makedirs(np_path)
i_path = os.path.join(np_path, 'inputs')
hpc_path = os.path.join(np_path, 'outputs')
#loop over sites
for site in sites:
study = study_root + site
# Path for combined output:
o_path = os.path.join(base_path, project, 'outputs', study)
if not os.path.exists(o_path):
os.makedirs(o_path)
so_path = os.path.join(o_path, 'scenarios')
if not os.path.exists(so_path):
os.makedirs(so_path)
po_path = os.path.join(o_path, 'pv')
if not os.path.exists(po_path):
os.makedirs(po_path)
to_path = os.path.join(o_path, 'saved_tariffs')
if not os.path.exists(to_path):
os.makedirs(to_path)
tso_path = os.path.join(o_path, 'timeseries')
if not os.path.exists(tso_path):
os.makedirs(tso_path)
# ---------------------
# combine results files
# ---------------------
# Combine results, customer_results and results_std
types = ['customer_results.csv', 'results.csv', 'results_std_dev.csv']
folder_list = [f for f in os.listdir(hpc_path) if 'hpc' in f and study in f and not '.csv' in f]
df = dict(zip(types, [pd.DataFrame(), pd.DataFrame(), pd.DataFrame()]))
# read existing results files to append:
for type in types:
o_name = study + '_' + type
o_file = os.path.join(o_path, o_name)
df[type] = pd.read_csv(o_file)
df[type] = df[type].set_index('scenario')
#Combine results files:
for ff in folder_list:
folder_path = os.path.join(hpc_path, ff)
for type in types: # NB customer_results must come first
file_list = [f for f in os.listdir(folder_path) if 'hpc' in f and '.csv' in f and type in f]
for f in file_list:
small_file = os.path.join(folder_path, f)
df_s = pd.read_csv(small_file)
df_s = df_s.set_index('scenario')
df[type] = df[type].append(df_s, sort=False)
os.remove(small_file)
for type in types:
df[type] = df[type].sort_index()
o_name = study + '_' + type
o_file = os.path.join(o_path, o_name)
df[type].to_csv(o_file)
# -------------------
# copy scenario files
# -------------------
for ff in folder_list:
spath = os.path.join(hpc_path, ff, 'scenarios')
if os.path.exists(spath):
slist = os.listdir(spath)
if len(slist) > 0:
for s in slist:
sf = os.path.join(spath, s)
newname = s.split('_')[0]+'_'+ s.split('_')[1] + '_' + s.split('_')[len(s.split('_'))-1]
nf = os.path.join(so_path, newname)
shutil.move(sf, nf)
os.rmdir(spath)
pvpath = os.path.join(hpc_path, ff, 'pv')
# # -------------
# # copy PV files
# # -------------
# if os.path.exists(pvpath):
# slist = os.listdir(pvpath)
# for s in slist:
# sf = os.path.join(pvpath, s)
# nf = os.path.join(po_path, s)
# shutil.move(sf, nf)
if os.path.exists(pvpath):
os.rmdir(pvpath)
# -------------
# copy tariff files
# -------------
tariffpath = os.path.join(hpc_path, ff, 'saved_tariffs')
if os.path.exists(tariffpath):
slist = os.listdir(tariffpath)
if len(slist) > 0:
for s in slist:
sf = os.path.join(tariffpath, s)
newname = s[7:-4] + '_' + ff[-6:] + '.csv'
nf = os.path.join(to_path,newname)
shutil.move(sf, nf)
os.rmdir(tariffpath)
# -------------
# copy timeseries files
# -------------
for tstype in ['timeseries', 'timeseries_b', 'timeseries_d']:
tspath = os.path.join(hpc_path, ff, tstype)
if os.path.exists(tspath):
slist = os.listdir(tspath)
if len(slist) > 0:
for s in slist:
sf = os.path.join(tspath, s)
newname = s[len(study) + 1:]
nf = os.path.join(tso_path, newname)
shutil.move(sf, nf)
os.rmdir(tspath)
fff = os.path.join(hpc_path, ff)
os.rmdir(fff)