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runbatch.py
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#%% ===========================================================================
### --- IMPORTS ---
### ===========================================================================
import os
import queue
import threading
import time
import shutil
import csv
import numpy as np
import pandas as pd
import subprocess
from datetime import datetime
import argparse
from builtins import input
from glob import glob
#%% Constants
LINUXORMAC = True if os.name == 'posix' else False
YAMPASERVERS = ['constellation01','cepheus','corvus','dorado','delphinus']
#%% ===========================================================================
### --- FUNCTIONS ---
### ===========================================================================
def writeerrorcheck(checkfile, errorcode=17):
"""
Inputs
------
checkfile: Filename to check. If it does not exist, stop the run.
errorcode: Value to return if check fails. Should be >0.
"""
if LINUXORMAC:
return f'if [ ! -f {checkfile} ]; then echo "missing {checkfile}"; exit {errorcode}; fi\n'
else:
return f'\nif not exist {checkfile} (\n echo file {checkfile} missing \n goto:eof \n) \n \n'
def writescripterrorcheck(script, errorcode=18):
"""
"""
if LINUXORMAC:
return f'if [ $? != 0 ]; then echo "{script} returned $?" >> gamslog.txt; exit {errorcode}; fi\n'
else:
return f'if not %errorlevel% == 0 (echo {script} returned %errorlevel%\ngoto:eof\n)\n'
def write_delete_file(checkfile, deletefile, PATH):
if LINUXORMAC:
PATH.writelines(f"if [ -f {checkfile} ]; then rm {deletefile}; fi\n")
else:
PATH.writelines("if exist " + checkfile + " (del " + deletefile + ')\n' )
def comment(text, PATH):
commentchar = '#' if LINUXORMAC else '::'
PATH.writelines(f'{commentchar} {text}\n')
def big_comment(text, PATH):
commentchar = '#' if LINUXORMAC else '::'
PATH.writelines(f'\n{commentchar}\n')
comment(text, PATH)
PATH.writelines(f'{commentchar}\n')
def get_ivt_numclass(reeds_path, casedir, caseSwitches):
"""
Extend ivt if necessary and calculate numclass
"""
ivt = pd.read_csv(
os.path.join(
reeds_path, 'inputs', 'userinput', 'ivt_{}.csv'.format(caseSwitches['ivt_suffix'])),
index_col=0)
ivt_step = pd.read_csv(os.path.join(reeds_path, 'inputs', 'userinput', 'ivt_step.csv'),
index_col=0).squeeze(1)
lastdatayear = max([int(c) for c in ivt.columns])
addyears = list(range(lastdatayear + 1, int(caseSwitches['endyear']) + 1))
num_added_years = len(addyears)
### Add v for the extra years
ivt_add = {}
for i in ivt.index:
vlast = ivt.loc[i,str(lastdatayear)]
if ivt_step[i] == 0:
### Use the same v forever
ivt_add[i] = [vlast] * num_added_years
else:
### Use the same spacing forever
forever = [[vlast + 1 + x] * ivt_step[i] for x in range(1000)]
forever = [item for sublist in forever for item in sublist]
ivt_add[i] = forever[:num_added_years]
ivt_add = pd.DataFrame(ivt_add, index=addyears).T
### Concat and resave
ivtout = pd.concat([ivt, ivt_add], axis=1)
ivtout.to_csv(os.path.join(casedir, 'inputs_case', 'ivt.csv'))
### Get numclass, which is used in b_inputs.gms
numclass = ivtout.max().max()
return numclass
def check_compatibility(sw):
### Hourly resolution
if (
(int(sw['endyear']) > 2050)
or int(sw['GSw_ClimateHydro'])
or int(sw['GSw_ClimateDemand'])
or int(sw['GSw_ClimateWater'])
or int(sw['GSw_EFS_Flex'])
or (float(sw['GSw_HydroWithinSeasFrac']) < 1)
or (float(sw['GSw_HydroPumpWithinSeasFrac']) < 1)
or (int(sw['GSw_Canada']) == 2)
):
raise NotImplementedError(
'At least one of GSw_Canada, GSw_ClimateHydro, GSw_ClimateDemand, GSw_ClimateWater, '
'endyear, GSw_EFS_Flex, GSw_HydroWithinSeasFrac, GSw_HydroPumpWithinSeasFrac '
'are using a currently-unsupported setting.')
if 24 % (int(sw['GSw_HourlyWindowOverlap']) * int(sw['GSw_HourlyChunkLengthRep'])):
raise ValueError(
('24 must be divisible by GSw_HourlyWindowOverlap * GSw_HourlyChunkLengthRep:'
'\nGSw_HourlyWindowOverlap = {}\nGSw_HourlyChunkLengthRep = {}'.format(
sw['GSw_HourlyWindowOverlap'], sw['GSw_HourlyChunkLengthRep'])))
if int(sw['GSw_HourlyWindow']) <= int(sw['GSw_HourlyWindowOverlap']):
raise ValueError(
('GSw_HourlyWindow must be greater than GSw_HourlyWindowOverlap:'
'\nGSw_HourlyWindow = {}\nGSw_HourlyWindowOverlap = {}'.format(
sw['GSw_HourlyWindow'], sw['GSw_HourlyWindowOverlap'])))
if ((sw['GSw_HourlyClusterAlgorithm'] not in ['hierarchical','optimized'])
and ('user' not in sw['GSw_HourlyClusterAlgorithm'])
):
raise ValueError(
"GSw_HourlyClusterAlgorithm must be set to 'hierarchical' or 'optimized', or must "
"contain the substring 'user' and match a scenario in "
"inputs/variability/period_szn_user.csv"
)
if ((sw['GSw_PRM_StressModel'].lower() not in ['pras','osprey'])
and ('user' not in sw['GSw_PRM_StressModel'])):
raise ValueError(
"GSw_PRM_StressModel must be set to 'pras' or 'osprey', or must "
"contain the substring 'user' and match a scenario at "
"inputs/variability/stressperiods_{GSw_PRM_StressModel}.csv"
)
if ('usa' not in sw['GSw_Region'].lower()) and (int(sw['GSw_GasCurve']) != 2):
raise ValueError(
'Should use GSw_GasCurve=2 (fixed prices) when running sub-nationally\n'
f"GSw_Region={sw['GSw_Region']}, GSw_GasCurve={sw['GSw_GasCurve']}"
)
### Aggregation
if (sw['GSw_RegionResolution'] != 'aggreg') and (
(int(sw['GSw_NumCSPclasses']) != 12)
or (int(sw['GSw_NumDUPVclasses']) != 7)
):
raise NotImplementedError(
'Aggregated CSP/DUPV classes only work with aggregated regions. '
'At least one of GSw_NumCSPclasses and GSw_NumDUPVclasses are incompatible with '
'GSw_RegionResolution != aggreg')
### Parsed string switches
## Automatic inputs
reeds_path = os.path.dirname(__file__)
hierarchy = pd.read_csv(os.path.join(reeds_path,'inputs','hierarchy.csv'))
for threshold in sw['GSw_PRM_StressThreshold'].split('/'):
## Example: threshold = 'transgrp_10_EUE_sum'
allowed_levels = ['country','interconnect','nercr','transreg','transgrp','st','r']
(hierarchy_level, ppm, stress_metric, period_agg_method) = threshold.split('_')
if hierarchy_level not in allowed_levels:
raise ValueError(
f"GSw_PRM_StressThreshold: level={hierarchy_level} but must be in:\n"
+ '\n'.join(allowed_levels)
)
if period_agg_method.lower() not in ['sum','max']:
raise ValueError("Fix period agg method in GSw_PRM_StressThreshold")
if not (float(ppm) >= 0):
raise ValueError(
"ppm in GSw_PRM_StressThreshold must be a positive number "
f"but '{ppm}' was provided"
)
if stress_metric.upper() not in ['EUE','NEUE']:
raise ValueError(
"stress metric in GSw_PRM_StressThreshold must be 'EUE' or 'NEUE' "
f"but '{stress_metric}' was provided"
)
if (sw['GSw_PRM_StressModel'].lower() != 'pras') and (stress_metric.upper() != 'EUE'):
err = (
f"The combination of GSw_PRM_StressModel={sw['GSw_PRM_StressModel']} and "
f"stress_metric={stress_metric} is not supported."
)
raise NotImplementedError(err)
for bir in sw['GSw_PVB_BIR'].split('_'):
if not (float(bir) >= 0):
raise ValueError("Fix GSw_PVB_BIR")
for ilr in sw['GSw_PVB_ILR'].split('_'):
if not (float(ilr) >= 0):
raise ValueError("Fix GSw_PVB_ILR")
for pvbtype in sw['GSw_PVB_Types'].split('_'):
if not (1 <= int(pvbtype) <= 3):
raise ValueError("Fix GSw_PVB_Types")
for year in sw['osprey_years'].split('_'):
if not (2007 <= int(year) <= 2013):
raise ValueError("Fix osprey_years")
for year in sw['GSw_HourlyWeatherYears'].split('_'):
if not (2007 <= int(year) <= 2013):
raise ValueError("Fix GSw_HourlyWeatherYears")
if '/' in sw['GSw_Region']:
level, regions = sw['GSw_Region'].split('/')
if level not in hierarchy:
raise ValueError("Fix level in GSw_Region")
for region in regions.split('.'):
if region.lower() not in hierarchy[level].str.lower().values:
err = f'GSw_Region: {region} needs to be in {hierarchy[level].unique()}'
raise Exception(err)
else:
modeled_regions = pd.read_csv(
os.path.join(reeds_path,'inputs','userinput','modeled_regions.csv')
)
if sw['GSw_Region'] not in modeled_regions:
raise ValueError("No column in modeled_regions.csv matching GSw_Region")
## Integer switches
for i in [
'debug',
'numbins_csp',
'numbins_upv',
'numbins_windofs',
'numbins_windons',
]:
try:
int(sw[i])
except ValueError:
raise ValueError(f"{i} must be an integer but is {sw[i]}")
def solvestring_sequential(
batch_case, caseSwitches,
cur_year, next_year, prev_year, restartfile,
toLogGamsString=' logOption=4 logFile=gamslog.txt appendLog=1 ',
hpc=0, iteration=0, stress_year=None,
):
"""
Typical inputs:
* restartfile: batch_case if first solve year else {batch_case}_{prev_year}
* caseSwitches: loaded from {batch_case}/inputs_case/switches.csv
"""
savefile = f"{batch_case}_{cur_year}i{iteration}"
_stress_year = f"{prev_year}i0" if stress_year is None else stress_year
out = (
"gams d_solveoneyear.gms"
+ (" license=gamslice.txt" if hpc else '')
+ " o=" + os.path.join("lstfiles", f"{savefile}.lst")
+ " r=" + os.path.join("g00files", restartfile)
+ " gdxcompress=1"
+ " xs=" + os.path.join("g00files", savefile)
+ toLogGamsString
+ f" --case={batch_case}"
+ f" --cur_year={cur_year}"
+ f" --next_year={next_year}"
+ f" --prev_year={prev_year}"
+ f" --stress_year={_stress_year}"
+ ''.join([f" --{s}={caseSwitches[s]}" for s in [
'GSw_SkipAugurYear',
'GSw_HourlyType', 'GSw_HourlyWrapLevel', 'GSw_ClimateWater',
'GSw_Canada', 'GSw_ClimateHydro',
'GSw_HourlyChunkLengthRep', 'GSw_HourlyChunkLengthStress',
'GSw_StateCO2ImportLevel',
'debug',
]])
+ '\n'
)
return out
def setup_sequential_year(
cur_year, prev_year, next_year,
caseSwitches, hpc,
solveyears, casedir, batch_case, toLogGamsString, OPATH, ticker,
restart_switches,
):
## Get save file (for this year) and restart file (from previous year)
savefile = f"{batch_case}_{cur_year}i0"
restartfile = batch_case if cur_year == min(solveyears) else f"{batch_case}_{prev_year}i0"
## Run the ReEDS LP
if (
(not restart_switches['restart'])
or (cur_year > min(solveyears))
or (restart_switches['restart'] and not restart_switches['restart_Augur'])
):
## solve one year
OPATH.writelines(
solvestring_sequential(
batch_case, caseSwitches,
cur_year, next_year, prev_year, restartfile,
toLogGamsString, hpc,
))
OPATH.writelines(writescripterrorcheck(f"d_solveoneyear.gms_{cur_year}"))
OPATH.writelines('python {t} --year={y}\n'.format(t=ticker, y=cur_year))
if int(caseSwitches['GSw_ValStr']):
OPATH.writelines("python valuestreams.py" + '\n')
## check to see if the restart file exists
OPATH.writelines(writeerrorcheck(os.path.join("g00files",savefile + ".g*")))
## Run Augur if it not the final solve year and if not skipping Augur
if ((
(cur_year < max(solveyears))
and (next_year > int(caseSwitches['GSw_SkipAugurYear']))
) or (
(cur_year == max(solveyears)) and int(caseSwitches['osprey_finalyear'])
)):
OPATH.writelines(
f"\npython Augur.py {next_year} {cur_year} {casedir}\n")
## Check to make sure Augur ran successfully; quit otherwise
OPATH.writelines(
writeerrorcheck(os.path.join(
"ReEDS_Augur", "augur_data", f"ReEDS_Augur_{cur_year}.gdx")))
## delete the previous restart file unless we're keeping them
if (cur_year > min(solveyears)) and (not int(caseSwitches['keep_g00_files'])):
write_delete_file(
checkfile=os.path.join("g00files", savefile + ".g00"),
deletefile=os.path.join("g00files", restartfile + '.g00'),
PATH=OPATH,
)
def setup_sequential(
caseSwitches, reeds_path, hpc,
solveyears, casedir, batch_case, toLogGamsString, OPATH, ticker,
restart_switches,
):
### loop over solve years
for i in range(len(solveyears)):
## current year is the value in solveyears
cur_year = solveyears[i]
if cur_year < max(solveyears):
## next year becomes the next item in the solveyears vector
next_year = solveyears[i+1]
## Get previous year if after first year
if i:
prev_year = solveyears[i-1]
else:
if restart_switches['restart']:
prev_year = restart_switches['restart_year']
else:
prev_year = solveyears[i]
### make an indicator in the batch file for what year is being solved
big_comment(f'Year: {cur_year}', OPATH)
### Write the tax credit phaseout call
OPATH.writelines(f"python tc_phaseout.py {cur_year} {casedir}\n\n")
### Write the GAMS LP and Augur calls
if (
int(caseSwitches['GSw_PRM_StressIterateMax'])
and (not int(caseSwitches['GSw_PRM_CapCredit']))
):
OPATH.writelines(
f"python d_solve_iterate.py {casedir} {cur_year}\n"
)
OPATH.writelines(writescripterrorcheck(f"d_solve_iterate.py_{cur_year}"))
else:
setup_sequential_year(
cur_year, prev_year, next_year,
caseSwitches, hpc,
solveyears, casedir, batch_case, toLogGamsString, OPATH, ticker,
restart_switches,
)
### Run Augur plots in background
OPATH.writelines(
f"python {os.path.join('ReEDS_Augur','G_plots.py')} "
f"--reeds_path={reeds_path} --casedir={casedir} --t={cur_year} &\n")
def setup_intertemporal(
caseSwitches, startiter, niter, ccworkers,
solveyears, endyear, batch_case, toLogGamsString, yearset_augur, OPATH,
):
### beginning year is passed to augurbatch
begyear = min(solveyears)
### first save file from d_solveprep is just the case name
savefile = batch_case
### if this is the first iteration
if startiter == 0:
## restart file becomes the previous calls save file
restartfile=savefile
## if this is not the first iteration...
if startiter > 0:
## restart file is now the case name plus the iteration number
restartfile = batch_case+"_"+startiter
### per the instructions, iterations are
### the number of iterations after the first solve
niter = niter+1
### for the number of iterations we have...
for i in range(startiter,niter):
## make an indicator in the batch file for what iteration is being solved
big_comment(f'Iteration: {i}', OPATH)
## call the intertemporal solve
savefile = batch_case+"_"+str(i)
if i==0:
## check to see if the restart file exists
## only need to do this with the zeroth iteration
## as the other checks will all be after the solves
OPATH.writelines(writeerrorcheck(os.path.join("g00files",restartfile + ".g*")))
OPATH.writelines(
"gams d_solveallyears.gms o="+os.path.join("lstfiles",batch_case + "_" + str(i) + ".lst")
+" r="+os.path.join("g00files",restartfile)
+ " gdxcompress=1 xs="+os.path.join("g00files",savefile) + toLogGamsString
+ " --niter=" + str(i) + " --case=" + batch_case
+ " --demand=" + caseSwitches['demand'] + ' \n')
## check to see if the save file exists
OPATH.writelines(writeerrorcheck(os.path.join("g00files",savefile + ".g*")))
## start threads for cc/curt
## no need to run cc curt scripts for final iteration
if i < niter-1:
## batch out calls to augurbatch
OPATH.writelines(
"python augurbatch.py " + batch_case + " " + str(ccworkers) + " "
+ yearset_augur + " " + savefile + " " + str(begyear) + " "
+ str(endyear) + " " + caseSwitches['distpvscen'] + " "
+ str(caseSwitches['calc_csp_cc']) + " "
+ str(caseSwitches['GSw_DR']) + " "
+ str(caseSwitches['timetype']) + " "
+ str(caseSwitches['GSw_WaterMain']) + " " + str(i) + " "
+ str(caseSwitches['marg_vre_mw']) + " "
+ str(caseSwitches['marg_stor_mw']) + " "
+ str(caseSwitches['marg_dr_mw']) + " "
+ '\n')
## merge all the resulting gdx files
## the output file will be for the next iteration
nextiter = i+1
gdxmergedfile = os.path.join(
"ReEDS_Augur","augur_data","ReEDS_Augur_merged_" + str(nextiter))
OPATH.writelines(
"gdxmerge "+os.path.join("ReEDS_Augur","augur_data","ReEDS_Augur*")
+ " output=" + gdxmergedfile + ' \n')
## check to make sure previous calls were successful
OPATH.writelines(writeerrorcheck(gdxmergedfile+".gdx"))
## restart file becomes the previous save file
restartfile=savefile
if caseSwitches['GSw_ValStr'] != '0':
OPATH.writelines( "python valuestreams.py" + '\n')
def setup_window(
caseSwitches, startiter, niter, ccworkers, reeds_path,
batch_case, toLogGamsString, yearset_augur, OPATH,
):
### load the windows
win_in = list(csv.reader(open(
os.path.join(
reeds_path,"inputs","userinput",
"windows_{}.csv".format(caseSwitches['windows_suffix'])),
'r'), delimiter=","))
restartfile = batch_case
### for windows indicated in the csv file
for win in win_in[1:]:
## beginning year is the first column (start)
begyear = win[1]
## end year is the second column (end)
endyear = win[2]
## for the number of iterations we have...
for i in range(startiter,niter):
big_comment(f'Window: {win}', OPATH)
comment(f'Iteration: {i}', OPATH)
## call the window solve
savefile = batch_case+"_"+str(i)
## check to see if the save file exists
OPATH.writelines(writeerrorcheck(os.path.join("g00files",restartfile + ".g*")))
## solve via the window solve file
OPATH.writelines(
"gams d_solvewindow.gms o=" + os.path.join("lstfiles",batch_case + "_" + str(i) + ".lst")
+" r=" + os.path.join("g00files",restartfile)
+ " gdxcompress=1 xs=g00files\\"+savefile + toLogGamsString + " --niter=" + str(i)
+ " --maxiter=" + str(niter-1) + " --case=" + batch_case + " --window=" + win[0] + ' \n')
## start threads for cc/curt
OPATH.writelines(writeerrorcheck(os.path.join("g00files",savefile + ".g*")))
OPATH.writelines(
"python augurbatch.py " + batch_case + " " + str(ccworkers) + " "
+ yearset_augur + " " + savefile + " " + str(begyear) + " "
+ str(endyear) + " " + caseSwitches['distpvscen'] + " "
+ str(caseSwitches['calc_csp_cc']) + " "
+ str(caseSwitches['GSw_DR']) + " "
+ str(caseSwitches['timetype']) + " "
+ str(caseSwitches['GSw_WaterMain']) + " " + str(i) + " "
+ str(caseSwitches['marg_vre_mw']) + " "
+ str(caseSwitches['marg_stor_mw']) + " "
+ str(caseSwitches['marg_dr_mw']) + " "
+ '\n')
## merge all the resulting r2_in gdx files
## the output file will be for the next iteration
nextiter = i+1
## create names for then merge the curt and cc gdx files
gdxmergedfile = os.path.join(
"ReEDS_Augur","augur_data","ReEDS_Augur_merged_" + str(nextiter))
OPATH.writelines(
"gdxmerge " + os.path.join("ReEDS_Augur","augur_data","ReEDS_Augur*")
+ " output=" + gdxmergedfile + ' \n')
## check to make sure previous calls were successful
OPATH.writelines(writeerrorcheck(gdxmergedfile+".gdx"))
restartfile=savefile
if caseSwitches['GSw_ValStr'] != '0':
OPATH.writelines( "python valuestreams.py" + '\n')
#%% ===========================================================================
### --- PROCEDURE ---
### ===========================================================================
def setupEnvironment(
BatchName=False, cases_suffix=False, simult_runs=0,
forcelocal=0, restart=False, skip_env_check=False,
debug=False, debugnode=False):
# #%% Settings for testing
# BatchName = 'v20230508_prasM0_Pacific'
# cases_suffix = 'test'
# WORKERS = 1
# forcelocal = 0
# restart = False
#%% Automatic inputs
reeds_path = os.path.dirname(__file__)
#%% User inputs
print(" ")
print("------------- ")
print(" ")
print("WINDOWS USERS - This script will open multiple command prompts, the number of which")
print("is based on the number of simultaneous runs you've chosen")
print(" ")
print("MAC/LINUX USERS - Your cases will run in the background. All console output")
print("is written to the cases' appropriate gamslog.txt file in the cases' runs folders")
print(" ")
print("------------- ")
print(" ")
print(" ")
if not BatchName:
print("-- Specify the batch prefix --")
print(" ")
print("The batch prefix is attached to the beginning of all cases' outputs files")
print("Note - it must start with a letter and not a number or symbol")
print(" ")
print("A value of 0 will assign the date and time as the batch name (e.g. v20190520_072310)")
print(" ")
BatchName = str(input('Batch Prefix: '))
if BatchName == '0':
BatchName = 'v' + time.strftime("%Y%m%d_%H%M%S")
#check for period in batchname and replace with underscore
BatchName = BatchName.replace('.', '_')
if not cases_suffix:
print("\n\nSpecify the suffix for the cases_suffix.csv file")
print("A blank input will default to the cases.csv file\n")
cases_suffix = str(input('Case Suffix: '))
#%% Check whether to submit slurm jobs (if on HPC) or run locally
hpc = True if (int(os.environ.get('REEDS_USE_SLURM',0))) else False
hpc = False if forcelocal else hpc
### If on NREL HPC but NOT submitting slurm job, ask for confirmation
if ('NREL_CLUSTER' in os.environ) and (not hpc):
print(
"It looks like you're running on the NREL HPC but the REEDS_USE_SLURM environment "
"variable is not set to 1, meaning the model will run locally rather than being "
"submitted as a slurm job. Are you sure you want to run locally?"
)
confirm_local = str(input('Run job locally? y/[n]: ') or 'n')
if confirm_local not in ['y','Y','yes','Yes','YES']:
quit()
#%% Check whether the ReEDS conda environment is activated
if (not skip_env_check) and (
('reeds2' not in os.environ['CONDA_DEFAULT_ENV'].lower())
or (not pd.__version__.startswith('2'))
):
print(
f"Your environment is {os.environ['CONDA_DEFAULT_ENV']} and your pandas "
f"version is {pd.__version__}.\nThe default environment is 'reeds2', with\n"
"pandas version 2.x, so the python parts of ReEDS are unlikely to work.\n"
"To build the environment for the first time, run:\n"
" `conda env create -f environment.yml`\n"
"To activate the created environment, run:\n"
" `conda activate reeds2` (or `activate reeds2` on Windows)\n"
"Do you want to continue without activating the environment?"
)
confirm_env = str(input("Continue? y/[n]: ") or 'n')
if confirm_env not in ['y','Y','yes','Yes','YES']:
quit()
#%% Load specified case file, infer other settings from cases.csv
df_cases = pd.read_csv(
os.path.join(reeds_path, 'cases.csv'), dtype=object, index_col=0)
cases_filename = 'cases.csv'
# If we have a case suffix, use cases_[suffix].csv for cases.
if cases_suffix not in ['','default']:
df_cases = df_cases[['Choices', 'Default Value']]
cases_filename = 'cases_' + cases_suffix + '.csv'
df_cases_suf = pd.read_csv(
os.path.join(reeds_path, cases_filename), dtype=object, index_col=0)
# Replace periods and spaces in case names with _
df_cases_suf.columns = [
c.replace(' ','_').replace('.','_') if c != 'Default Value' else c
for c in df_cases_suf.columns]
# Check to make sure user-specified cases file has up-to-date switches
missing_switches = [s for s in df_cases_suf.index if s not in df_cases.index]
if len(missing_switches):
error = ("The following switches are in {} but have changed names or are no longer "
"supported by ReEDS:\n\n{} \n\nPlease update your cases file; "
"for the full list of available switches see cases.csv."
"Note that switch names are case-sensitive."
).format(cases_filename, '\n'.join(missing_switches))
raise ValueError(error)
# First use 'Default Value' from cases_[suffix].csv to fill missing switches
# Later, we will also use 'Default Value' from cases.csv to fill any remaining holes.
if 'Default Value' in df_cases_suf.columns:
case_i = df_cases_suf.columns.get_loc('Default Value') + 1
casenames = df_cases_suf.columns[case_i:].tolist()
for case in casenames:
df_cases_suf[case] = df_cases_suf[case].fillna(df_cases_suf['Default Value'])
df_cases_suf.drop(['Choices','Default Value'], axis='columns',inplace=True, errors='ignore')
df_cases = df_cases.join(df_cases_suf, how='outer')
# Initiate the empty lists which will be filled with info from cases
caseList = []
caseSwitches = [] #list of dicts, one dict for each case
casenames = [c for c in df_cases.columns if c not in ['Description','Default Value','Choices']]
# Get the list of switch choices
choices = df_cases.Choices.copy()
for case in casenames:
#Fill any missing switches with the defaults in cases.csv
df_cases[case] = df_cases[case].fillna(df_cases['Default Value'])
# Ignore cases with ignore flag
if int(df_cases.loc['ignore',case]) == 1:
continue
# Check to make sure the switch setting is valid
for i, val in df_cases[case].items():
### Split choices by either '; ' or ','
if choices[i] in ['N/A',None,np.nan]:
pass
else:
i_choices = [
str(j).strip() for j in
np.ravel([i.split(',') for i in choices[i].split(';')]).tolist()
]
if str(val) not in i_choices:
error = (
'Invalid entry for "{}" for case "{}".\n'
'Entered "{}" but must be one of the following:\n\n{}'
).format(i, case, val, '\n'.join(i_choices))
raise ValueError(error)
#Check GSw_Region switch and ask user to correct if commas are used instead of periods to list multiple regions
if ',' in (df_cases[case].loc['GSw_Region']) :
print("Please change the delimeter in the GSw_Region switch from ',' to '.'")
quit()
# Propagate debug setting
if debug:
df_cases.loc['debug',case] = str(debug)
# Add switch settings to list of options passed to GAMS
shcom = ' --case=' + BatchName + "_" + case
for i,v in df_cases[case].items():
#exclude certain switches that don't need to be passed to GAMS
if i not in ['file_replacements','keep_run_terminal']:
shcom = shcom + ' --' + i + '=' + v
caseList.append(shcom)
caseSwitches.append(df_cases[case].to_dict())
# ignore cases with ignore flag
casenames = [case for case in casenames if int(df_cases.loc['ignore',case]) != 1]
df_cases.drop(
df_cases.loc['ignore'].loc[df_cases.loc['ignore']=='1'].index, axis=1, inplace=True)
# Make sure the run folders don't already exist
outpaths = [os.path.join(reeds_path,'runs',f'{BatchName}_{case}') for case in casenames]
existing_outpaths = [i for i in outpaths if os.path.isdir(i)]
if len(existing_outpaths) and not restart:
print(
f'The following {len(existing_outpaths)} output directories already exist:\n'
+ 'vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv\n'
+ '\n'.join([os.path.basename(i) for i in existing_outpaths])
+ '\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n'
)
overwrite = str(input('Do you want to overwrite them? y/[n]: ') or 'n')
if overwrite in ['y','Y','yes','Yes','YES']:
for outpath in existing_outpaths:
shutil.rmtree(outpath)
else:
keep = [i for (i,c) in enumerate(outpaths) if c not in existing_outpaths]
caseList = [caseList[i] for i in keep]
casenames = [casenames[i] for i in keep]
caseSwitches = [caseSwitches[i] for i in keep]
print(
f"\nThe following {(len(keep))} output directories don't exist:\n"
+ 'vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv\n'
+ '\n'.join([f'{BatchName}_{c}' for c in casenames])
+ '\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n'
)
skip = str(input('Do you want to run them and skip the rest? y/[n]: ') or 'n')
if skip not in ['y','Y','yes','Yes','YES']:
raise IsADirectoryError('\n'+'\n'.join(existing_outpaths))
df_cases.drop(
['Choices','Description','Default Value'],
axis='columns', inplace=True, errors='ignore')
print("{} cases being run:".format(len(caseList)))
for case in casenames:
print(case)
print(" ")
reschoice = 0
startiter = 0
ccworkers = 5
niter = 5
#%% Set number of workers, with user input if necessary
if len(caseList)==1:
print("Only one case is to be run, therefore only one thread is needed")
WORKERS = 1
elif simult_runs < 0:
WORKERS = len(caseList)
elif simult_runs > 0:
WORKERS = simult_runs
else:
WORKERS = int(input('Number of simultaneous runs [integer]: '))
print(WORKERS)
print("")
if 'int' in df_cases.loc['timetype'].tolist() or 'win' in df_cases.loc['timetype'].tolist():
ccworkers = int(input('Number of simultaneous CC/Curt runs [integer]: '))
print("")
print("The number of iterations defines the number of combinations of")
print(" solving the model and computing capacity credit and curtailment")
print(" Note this does not include the initial solve")
print("")
niter = int(input('How many iterations between the model and CC/Curt scripts: '))
# reschoice = int(input('Do you want to restart from a previous convergence attempt (0=no, 1=yes): '))
if reschoice==1:
startiter = int(input('Iteration to start from (recall it starts at zero): '))
envVar = {
'WORKERS': WORKERS,
'ccworkers': ccworkers,
'casenames': casenames,
'BatchName': BatchName,
'caseList': caseList,
'caseSwitches': caseSwitches,
'reeds_path' : reeds_path,
'niter' : niter,
'startiter' : startiter,
'cases_filename': cases_filename,
'hpc': hpc,
'restart': restart,
'debugnode': debugnode,
}
return envVar
def createmodelthreads(envVar):
q = queue.Queue()
num_worker_threads = envVar['WORKERS']
def worker():
while True:
ThreadInit = q.get()
if ThreadInit is None:
break
runModel(
options=ThreadInit['scen'],
caseSwitches=ThreadInit['caseSwitches'],
niter=ThreadInit['niter'],
reeds_path=ThreadInit['reeds_path'],
ccworkers=ThreadInit['ccworkers'],
startiter=ThreadInit['startiter'],
BatchName=ThreadInit['BatchName'],
case=ThreadInit['casename'],
cases_filename=ThreadInit['cases_filename'],
hpc=envVar['hpc'],
restart=envVar['restart'],
debugnode=envVar['debugnode'],
)
print(ThreadInit['batch_case'] + " has finished \n")
q.task_done()
threads = []
for i in range(num_worker_threads):
t = threading.Thread(target=worker)
t.start()
threads.append(t)
for i in range(len(envVar['caseList'])):
q.put({
'scen': envVar['caseList'][i],
'caseSwitches': envVar['caseSwitches'][i],
'batch_case':envVar['BatchName']+'_'+envVar['casenames'][i],
'niter':envVar['niter'],
'reeds_path':envVar['reeds_path'],
'ccworkers':envVar['ccworkers'],
'startiter':envVar['startiter'],
'BatchName':envVar['BatchName'],
'casename':envVar['casenames'][i],
'cases_filename':envVar['cases_filename'],
'restart':envVar['restart'],
})
# block until all tasks are done
q.join()
# stop workers
for i in range(num_worker_threads):
q.put(None)
for t in threads:
t.join()
def runModel(options, caseSwitches, niter, reeds_path, ccworkers, startiter,
BatchName, case, cases_filename, hpc=False, restart=False, debugnode=False):
### For testing/debugging
# caseSwitches = caseSwitches[0]
# options = caseList[0]
### Inferred inputs
batch_case = f'{BatchName}_{case}'
endyear = int(caseSwitches['endyear'])
casedir = os.path.join(reeds_path,'runs',batch_case)
inputs_case = os.path.join(casedir,"inputs_case")
# Indicate this run is a restart
if restart:
print("Restarting from previous run.")
else:
if os.path.exists(os.path.join(reeds_path,'runs',batch_case)):
print('Caution, case ' + batch_case + ' already exists in runs \n')
#%% Set up case-specific directory structure
os.makedirs(os.path.join(reeds_path,'runs',batch_case), exist_ok=True)
os.makedirs(os.path.join(reeds_path,'runs',batch_case,'g00files'), exist_ok=True)
os.makedirs(os.path.join(reeds_path,'runs',batch_case,'lstfiles'), exist_ok=True)
os.makedirs(os.path.join(reeds_path,'runs',batch_case,'outputs'), exist_ok=True)
os.makedirs(os.path.join(reeds_path,'runs',batch_case,'outputs','tc_phaseout_data'), exist_ok=True)
os.makedirs(inputs_case, exist_ok=True)
#%% Stop now if any switches are incompatible
check_compatibility(caseSwitches)
#%% Write the GAMS switches
gswitches = pd.Series(caseSwitches)
## Only keep switches that start with 'GSw' and have a numeric value
def isnumeric(x):
try:
float(x)
if '_' not in x:
return True
except Exception:
return False
gswitches = gswitches.loc[
gswitches.index.str.lower().str.startswith('gsw')
& gswitches.map(isnumeric)
].copy()
## In GAMS we change 'GSw' to 'Sw'
gswitches.index = gswitches.index.map(lambda x: x[1:])
## Add a 'comment' column and write to csv and GAMS-readable text
gswitches.reset_index().assign(comment='').to_csv(
os.path.join(inputs_case,'gswitches.csv'), header=False, index=False)
#%% Information on reV supply curves associated with this run
shutil.copytree(os.path.join(reeds_path,'inputs','supplycurvedata','metadata'),
os.path.join(inputs_case,'supplycurve_metadata'), dirs_exist_ok=True)
rev_paths = pd.read_csv(
os.path.join(reeds_path,'inputs','supplycurvedata','rev_paths.csv')
)
# Separate techs with no associated switch
rev_paths_none = rev_paths.loc[rev_paths.access_switch == "none",:].copy()
rev_paths = rev_paths.loc[rev_paths.access_switch != "none",:]
# Match possible supply curves with switches from this run
siteSwitches = pd.DataFrame.from_dict({s:caseSwitches[s] for s in rev_paths.access_switch.unique()},
orient='index').reset_index().rename(columns={'index':'access_switch', 0:'access_case'})
siteSwitches = siteSwitches.merge(rev_paths, on=['access_switch', 'access_case'])
siteSwitches = pd.concat([siteSwitches[rev_paths_none.columns.tolist()], rev_paths_none])
# Get bin information
bins = {"wind-ons":"numbins_windons", "wind-ofs": "numbins_windofs", "upv":"numbins_upv"}
binSwitches = pd.DataFrame.from_dict({b:caseSwitches[bins[b]] for b in bins},
orient='index').reset_index().rename(columns={'index':'tech', 0:'bins'})
siteSwitches = siteSwitches.merge(binSwitches, on=['tech'], how='left')
# Expand on reV path based on where this run is happening
#For running hourlize on the HPC link to shared-projects folder
if os.environ.get('NREL_CLUSTER') == 'kestrel':
hpc_path = '/projects/shared-projects-reeds/reeds/Supply_Curve_Data'
else:
hpc_path = '/shared-projects/reeds/Supply_Curve_Data'
if hpc:
rev_prefix = hpc_path
else:
hostname = os.environ.get('HOSTNAME')
if (hostname) and (hostname.split('.')[0] in YAMPASERVERS):
drive = '/data/shared/shared_data'
elif LINUXORMAC:
drive = '/Volumes'
else:
drive = '//nrelnas01'
rev_prefix = os.path.join(drive,'ReEDS','Supply_Curve_Data')
siteSwitches['rev_case'] = siteSwitches['rev_path'].apply(lambda row: os.path.basename(row))
siteSwitches['sc_path'] = siteSwitches['sc_path'].apply(lambda row: os.path.join(rev_prefix,row))
siteSwitches['hpc_path'] = siteSwitches['rev_path'].apply(lambda row: os.path.join(hpc_path,row))
siteSwitches[['tech','access_switch','access_case','bins','rev_case',
'sc_path','hpc_path','hpc_sc_file','cf_path','original_rev_folder']
].to_csv(os.path.join(inputs_case,'rev_paths.csv'), index=False)
#%% Set up the meta.csv file to track repo information and runtime
ticker = os.path.join(reeds_path,'input_processing','ticker.py')
loglines = ['computer,repo,branch,commit,description\n']
### Get some git metadata
try:
import git
import socket
repo = git.Repo()
try:
branch = repo.active_branch.name
description = repo.git.describe()
except TypeError:
branch = 'DETACHED_HEAD'
description = ''
loglines.append(
'{},{},{},{},{}\n'.format(
socket.gethostname(),
repo.git_dir, branch, repo.head.object.hexsha, description))
except Exception:
### In case the user hasn't installed GitPython (conda install GitPython)
### or isn't in a git repo or anything else goes wrong
loglines.append('None,None,None,None,None\n')
with open(os.path.join(casedir,'meta.csv'),'a') as METAFILE:
### Header for timing metadata
for line in loglines:
METAFILE.writelines(line)
METAFILE.writelines('#,#,#,#,#\n')
METAFILE.writelines('year,process,starttime,stoptime,processtime\n')
### Also write the git metadata to gamslog.txt for debugging
with open(os.path.join(casedir,'gamslog.txt'),'a') as LOGFILE:
for line in loglines:
LOGFILE.writelines(line)
### Write the environment info for debugging
try:
environment = subprocess.run('conda list', capture_output=True, shell=True)
pd.Series(environment.stdout.decode().split('\n')).to_csv(
os.path.join(casedir,'lstfiles','environment.csv'),
header=False, index=False,