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globalnews.py
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globalnews.py
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""" globalnews.py
Global NEWS 2 model, GNE implementation.
This module is the master model execution controller; it imports
gncfg, gncore, and the actual "model" code (dissolved.py, etc).
AVAILABILITY, USE RESTRICTIONS, AND CONTACT INFORMATION
-------------------------------------------------------
The Global NEWS 2 model ("NEWS 2") and the Global NEWS modeling Environment (GNE)
were developed by the Global NEWS group and are available at our web site:
http://www.marine.rutgers.edu/globalnews/
We encourage its use for research and educational (non-commercial) purposes, but
we request that active users contact us to inform about how it is being applied.
Such feedback and reporting will improve our continued development of the model code.
Global NEWS is a work group of UNESCO's Intergovernmental Oceanographic Commission (IOC).
Use of NEWS 2 should be ackwnowledged by citing Mayorga et al (in review);
Beusen et al. (2009) and Billen and Garnier (2007) should also be cited if
the DSi model and the ICEP index, respectively, are also used.
For questions and additional information, please contact:
Emilio Mayorga, Ph.D. mayorga@apl.washington.edu
Applied Physics Laboratory, University of Washington
Seattle, WA USA
---------------------------------------
RECENT MODIFICATION HISTORY
1/18/2010: Improved documentation and some run-time messages.
10/16-24/2008: Added functionality to allow an optional 'All-Forms' model
after the Global NEWS nutrient form models are completed. This new model
or calculation can use results from any nutrient form output. It is coded
in the python code file allformmodel.py. It's enabled through the new
optional argument -a (or --afm).
1/28/2008: Added actual usage text to usage(); cleaned up run-time messages a bit
and added date-time statements at every major code block in main() and runmodel().
9/17-18/2007
"""
import sys
import os.path
import getopt
from operator import itemgetter
import time
import numpy as ny
from numpy import log, exp, log10
# Import Global NEWS Environment ("gne") modules
# Generic gne code files ideally should be placed in the "gnecode"
# subfolder, but they may also be placed at the same base folder
__gne = os.path.join('.', 'gnecode')
if os.path.exists(__gne): sys.path.insert(0, __gne)
from gnecode.gncfg import *
import gnecode.gngis2tbls as gngis2tbls
__version__ = '$Revision: 2010-01-18$'
def localtimestrf(frmtopt="datetime"):
''' Return the local date-time as a formatted string.
frmtopt="datetime" (default) Return a complete date-time string.
frmtopt="timeonly" Return Hour:Minute:Seconds only.
'''
if frmtopt == "datetime":
return time.strftime("%a, %d %b %Y %H:%M:%S", time.localtime())
elif frmtopt == "timeonly":
return "Time: " + time.strftime("%H:%M:%S", time.localtime())
def usage():
''' Print out string describing model usage and optional arguments.
'''
print("\nRun-time arguments/options:")
print("-h OR --help Show this help text.")
print("-v Run in verbose mode (print out all internal messages).")
print("<none> Run Global NEWS model using vars.cfg config file.")
print("-a OR --afm Run Global NEWS 'All-Forms' model *after* all individual")
print(" nutrient forms have been calculated (with allformmodel.py).")
print("-g OR --gis Run GIS pre-processor using gis2tbls.cfg config file.")
print("-g OR --gis Run GIS pre-processor using gis2tbls.cfg config file.")
print("-p OR --postproc Run post-processing: create new loads variables")
print(" for selected inputs and outputs, all basins.")
def main():
global FLAGS
print("\n***** Global NEWS modeling Environment (GNE) *****")
print(" " + __version__)
print(" " + localtimestrf())
print(" ==========================================")
# Passing arguments at command-line
# opts, args = getopt.getopt(sys.argv[1:], "ho:v", ["help", "output="])
try:
# hmm, not sure what's fed to args if opts already gets the arg value
opts, args = getopt.getopt(sys.argv[1:], "agphv", ["afm", "gis", "postproc", "help"])
# extract list of just the "options" (arguments), without arg. values
opt = list(map(itemgetter(0), opts))
except getopt.GetoptError:
# print help information, then exit:
usage()
sys.exit(2)
if "-h" in opt or "--help" in opt:
usage()
sys.exit()
FLAGS['verbose'] = False
if "-v" in opt:
FLAGS['verbose'] = True
if "-g" in opt or "--gis" in opt:
rungis2tbls()
elif "-p" in opt or "--postproc" in opt:
runpostproc()
else:
if "-a" in opt or "--afm" in opt:
FLAGS['AllFormModel'] = True
else:
FLAGS['AllFormModel'] = False
runmodel()
#elif "-s" in opt or "--smry" in opt:
# runsummary() # does not exist yet!
print(" ==========================================")
print("***** GNE Run completed *****")
print(" %s\n" % localtimestrf())
def runmodel():
''' Execute a Global NEWS run using pre-processed basin inputs
as configured in vars.cfg.
'''
global IN, OUT, FLAGS
print("*** Running Global NEWS Model\n")
cfg_simple_sections("MODEL")
print("*** Done reading general model run configurations (cfg_simple_sections()) ***")
print(" %s" % localtimestrf("timeonly"))
PopulateCfgVars(fname_cfg_var, "MODEL")
print("*** Done reading variable configurations (PopulateCfgVars()) ***")
print(" %s" % localtimestrf("timeonly"))
load_var_arrays(INDOC_TBL, INDOC, IN, OUT)
print("*** Done loading input data into memory (load_var_arrays()) ***")
print(" %s" % localtimestrf("timeonly"))
print("\n*** Ready to run models ... ***")
# run only nutrient-form (parameter) subsets specified in vars.cfg, as appropriate
params_dissolved = [p for p in RUN['p'] if p in PGRP['dissolved']]
params_particulate = [p for p in RUN['p'] if p in PGRP['particulate']]
print(" Nutrient forms (parameters) requested:")
print(" " + ",".join(params_dissolved) + " " + ",".join(params_particulate))
if len(params_dissolved):
model_dissolved(params_dissolved)
print("*** Done with dissolved sub-models ***")
else:
print("*** No dissolved forms (parameters) requested")
print(" %s" % localtimestrf("timeonly"))
if len(params_particulate):
model_particulate(params_particulate)
print("*** Done with particulate sub-models ***")
else:
print("*** No particulate forms (parameters) requested")
print(" %s" % localtimestrf("timeonly"))
if FLAGS['AllFormModel']:
import allformmodel
allformmodel.model()
print("*** Done with 'All-Form' model ***")
else:
print("*** No 'All-Form' model requested")
print(" %s" % localtimestrf("timeonly"))
write_var_arrays(OUTDOC_TBL, OUTDOC, OUT)
print("*** Done writing output to files (write_var_arrays()) ***")
def rungis2tbls():
global IN, OUT
print("\n***Running Global NEWS Pre-Processor (GIS > Tables)\n")
# print the time, too?
cfg_simple_sections("GIS2TBLS")
print("*** Done with cfg_simple_sections ***\n")
PopulateCfgVars(fname_cfg_gis, "GIS2TBLS")
print("*** Done with PopulateCfgVars ***\n")
gngis2tbls.LoadBasinIDArea(INDOC_TBL, IN, OUT)
print("*** Done with LoadBasinIDArea ***\n")
# loop through gis input grids for all items in INDOC
#print "INDOC keys:", INDOC.keys(), " INDOC_TBL keys:", INDOC_TBL.keys()
gngis2tbls.CalcBasinStats(INDOC_TBL, INDOC)
print("*** Done with CalcBasinStats ***\n")
gngis2tbls.BasinStatsToOUTvarArrays(OUTDOC_TBL, OUTDOC, OUT, IN)
print("*** Done with BasinStatsToOUTvarArrays ***\n")
# INSERT HERE A NEW FUNCTION (SEPARATE FILE) TO FREELY DEFINE GENERATED
# OUT VARS THAT ARE NOT ZONALSTATS. WILL NEED TO MODIFY
# BasinStatsToOUTvarArrays TO NOT TRIP OVER THOSE NEW OUT VARS
# Maybe this new function should be called *only* if there are any
# "qualifying" OUT vars?? Do that test here, in the new function, or
# in BasinStatsToOUTvarArrays() and have it return a value?
excldvarset = set(list(INDOC.keys()) + ['BasinID', 'BasinArea'])
genoutset = set(OUTDOC.keys()).difference(excldvarset)
if len(genoutset):
import gis2tbls
gis2tbls.newoutvars()
print("*** Done with gis2tbls ***\n")
else:
print("*** No gis2tbls variables requested\n")
write_var_arrays(OUTDOC_TBL, OUTDOC, OUT)
print("*** Done with write_var_arrays ***\n")
def runpostproc():
global IN, OUT
print("\n***Running Post-processing \n")
# print the time, too?
cfg_simple_sections("MODEL")
print("*** Done with cfg_simple_sections ***\n")
PopulateCfgVars(fname_cfg_var, "MODEL")
print("*** Done with PopulateCfgVars ***\n")
load_var_arrays(INDOC_TBL, INDOC, IN, OUT)
print("*** Done with load_var_arrays ***\n")
# run only parameter subsets specified in vars.cfg (? is this applicable?)
print(" Parameters requested: ", RUN['p'])
if len(RUN['p']):
import postprocess
postprocess.processvars(RUN['p'])
print("*** Done with postprocess ***\n")
else:
print("*** No postprocess parameters requested\n")
write_var_arrays(OUTDOC_TBL, OUTDOC, OUT)
print("*** Done with write_var_arrays ***\n")
# NOW WRITE OUT A SEPARATE SUMMARY FILE (*_smry.csv) WITH
# GLOBAL AND MAYBE REGIONAL (CONTINENTAL, ETC) TOTALS???
def ParseStrBlock(delims, str_in, strblock_d):
if delims[0] in str_in:
bl0, blf = (str_in.index(delims[0]), str_in.index(delims[1]))
# 0 = enclosed block, b = beginning block, f = final block
# strblock_d['b']<strblock_d['0']>strblock_d['f']
# where < and > represent the chosen delimeters, "delims"
strblock_d['0'] = str_in[:bl0]
strblock_d['b'] = str_in[bl0+1:blf]
strblock_d['f'] = str_in[blf+1:]
return True
else:
return False
def read_cfgfile(fname_cfg, sect_prefix):
""" Read and parse configuration files
Return dictionary of parsed section/options
For section names [prefix.suffix]: cfg_dict[sect_suffix][option] = optionvalue
For section names [prefix]: cfg_dict[option] = optionvalue
"""
import os, os.path
import configparser
cfg = configparser.SafeConfigParser()
# Prevent default behavior of returning options in all-lowercase
cfg.optionxform = str
fpath_cfg = os.path.join(fpath_dev, fname_cfg)
cfg.read(fpath_cfg)
# is any error checking needed??
cfg_dict = {}
for section in cfg.sections():
if "." in section:
spre,ssuf = section.split(".")
if spre == sect_prefix:
cfg_dict[ssuf] = {}
for opt,val in cfg.items(section):
cfg_dict[ssuf][opt] = val
if FLAGS['verbose']: print(" %s[%s][%s] = %s" %(sect_prefix, ssuf, opt, cfg_dict[ssuf][opt]))
elif section == sect_prefix:
for opt,val in cfg.items(section):
cfg_dict[opt] = val
if FLAGS['verbose']: print(" %s[%s] = %s" %(section, opt, cfg_dict[opt]))
return cfg_dict
def parse_cfg_ccal(ccal_cfg_d, ccal_d):
""" Populate global CCAL dictionary
"""
for k1 in list(ccal_cfg_d.keys()):
ccal_d[k1] = {}
for k2,val in list(ccal_cfg_d[k1].items()):
ccal_d[k1][k2] = float(val)
def parse_cfg_modelrun(mrun_cfg_d, run_d):
""" Populate global RUN dictionary
"""
# Parse variable p
vallst = mrun_cfg_d['p'].split(',')
# note: run_d['p'] must be stored as list, not single value
# perform variable test & expansion based on PGRP
if len(vallst) == 1:
# entry could be a single parameter or a parameter group
if vallst[0] in PGRP['all']:
run_d['p'] = vallst
elif vallst[0] in list(PGRP.keys()):
run_d['p'] = list(PGRP[vallst[0]]) # convert tuple to list
else:
if FLAGS['verbose']: print("Generic var name: parameter sepecifier %s not valid" % (vallst[0]))
else:
run_d['p'] = vallst
# Parse variable param_ord
run_d['param_ord'] = []
vallst = mrun_cfg_d['param_ord'].split(',')
for idx, v in enumerate(vallst):
if PGRP['all'][idx] in run_d['p']:
# assign order index, converting from base 1 to base 0
run_d['param_ord'].append(int(v) - 1)
if FLAGS['verbose']: print(run_d)
def parse_cfg_basrea(basarea_cfg_d, basarea_d):
""" Populate global BASAREA dictionary
"""
# Parse variable BasinAreas, populate global dictionary
if basarea_cfg_d['BasinAreas'] == "NO":
basarea_d['BasinAreas'] = \
{'FLAG':False, 'outtable':None, 'varname':None}
else:
vallst = basarea_cfg_d['BasinAreas'].split('|')
basarea_d['BasinAreas'] = \
{'FLAG':True, 'outtable':vallst[0], 'varname':vallst[1]}
if FLAGS['verbose']: print("BASAREA: ", basarea_cfg_d['BasinAreas'])
def parse_cfg_tbls(tbls, strsubs, doctbl_d, doctype):
""" parse tables
This generic function can populate either INDOC_TBL or OUTDOC_TBL
INDOC_TBL and OUTDOC_TBL must be already initialized/declared (in gncfg.py)
doctbl_d: INDOC_TBL or OUTDOC_TBL
doctype: "IN" or "OUT"
"""
import os.path
vlist_len = {"INGIS":2, "IN":2, "OUT":2}
# what's the difference between .items() and .iteritems()?
for tblname,val in list(tbls.items()):
vlist = val.split("|")
# later, the basis for doctype == "OUT" might be made optional?
if len(vlist) != vlist_len[doctype]:
if FLAGS['verbose']: print("%s: Tables must have exactly %d arguments.\n" %(tblname, vlist_len[doctype]))
# Now exit.
# add empty tblname key to dictionary
doctbl_d[tblname] = {}
# Add filepath item
# one optional string substitution is allowed for now; parse it if present
# allowing multiple string substitutions later will be very useful
# first test for the existence of strblock in strsubs?
strblock = {}
if ParseStrBlock("()", vlist[0], strblock):
doctbl_d[tblname]['filepath'] = strsubs[strblock['b']] + strblock['f']
if FLAGS['verbose']: print(tblname,doctbl_d[tblname]['filepath'])
else:
doctbl_d[tblname]['filepath'] = vlist[0]
if doctype == "IN":
# test to see if the file exists
if not os.path.exists(doctbl_d[tblname]['filepath']):
if FLAGS['verbose']: print("Table does not exist: %s\n" %(doctbl_d[tblname]['filepath']))
# Now exit.
# Add basis item (check for valid values)
basis_valid = ('basin', 'nation', 'table', 'grid')
if vlist[1] in basis_valid:
doctbl_d[tblname]['basis'] = vlist[1]
else:
if FLAGS['verbose']: print("Table %s: basis '%s' is not recognized; must be (%s).\n" \
%(tblname, vlist[1], ','.join(basis_valid)))
# Now exit.
# OUT tables can only have a 'basin' basis; for now, just ignore entry in cfg
elif doctype == "OUT":
doctbl_d[tblname]['basis'] = 'basin'
# initialize list of variables to be used
# and their left-right field output order (for OUT)
doctbl_d[tblname]['varlst'] = []
doctbl_d[tblname]['fieldorder'] = []
def parse_cfg_vars(vars, doctbl_d, doc_d, doctype):
""" Parse variables, mapping them to columns (fields) in csv tables.
"""
vlist_len = {"IN":3, "OUT":4, "INGIS":3}
dattype = {'IN':'tbl', 'OUT':'tbl', 'INGIS':'gis'}
for varname,val in list(vars.items()):
vlist = val.split("|")
if len(vlist) != vlist_len[doctype]:
# for doctype "OUT", flgwrite 'Y' is assumed if it's ommitted
if doctype == "OUT" and len(vlist) == vlist_len[doctype] - 1:
vlist.append('Y')
else:
if FLAGS['verbose']: print("%s: Variable must have exactly %d arguments.\n" \
%(varname, vlist_len[doctype]))
# Now exit.
strblock = {}
if doctype == "OUT":
# if doctype == "OUT", try to parse generic variables
if ParseStrBlock("<>", varname, strblock):
vargen = strblock['b'].split('|')
# "p": variable name used for "parameter" in .cfg file
if vargen[0] == 'p':
varname0, varnamef = (strblock['0'], strblock['f'])
params_in = vargen[1].split(',')
# perform variable test & expansion based on PGRP
if len(params_in) == 1:
# entry could be a single paramer or a parameter group
# ignore case mismatch?? (eg, DOC vs doc)
if params_in[0] in PGRP['all']:
# it's already a simple parameter name, so use as-is
params = params_in
elif params_in[0] in list(PGRP.keys()):
# extract parameters from param group, convert to list
params = list(PGRP[params_in[0]])
else:
print("Generic var name: parameter sepecifier %s not valid" % (params_in[0]))
else:
# should do error check, to ensure parameters are valid
params = params_in
else:
print("Error with generic var name!")
if FLAGS['verbose']: print(strblock['b'],params, "\n")
# Parse and expand fieldname, if it, too, is generic
# A generic varname doesn't require a corresponding generic fieldname
ParseStrBlock("<>", vlist[1], strblock)
if strblock['b'] == 'p':
IsGenericFldName = True
fldname0, fldnamef = (strblock['0'], strblock['f'])
else:
IsGenericFldName = False
if FLAGS['verbose']:
print(">WARNING: For generic var name, field name is not generic")
# limit params list by actual model run parameters in RUN['p']
params = [p for p in PGRP['all'] if p in params and p in RUN['p']]
# add expanded variables to doc_d based on the vargen block
for p in params:
# if doctype == "OUT", more than one srctable is allowed.
varname_p = varname0 + p + varnamef
if IsGenericFldName:
fldname_p = fldname0 + p + fldnamef
else:
fldname_p = vlist[1]
doctbld_docd_assign(dattype[doctype], doctbl_d, doc_d, \
varname_p, vlist[0], fldname_p, \
vlist[2], vlist[3], varname, p)
else:
doctbld_docd_assign(dattype[doctype], doctbl_d, doc_d, varname, \
vlist[0], vlist[1], vlist[2], vlist[3])
else:
# if doctype == "IN", parse specific vars only; just one srctable is allowed.
doctbld_docd_assign(dattype[doctype], doctbl_d, doc_d, varname, \
vlist[0], vlist[1], vlist[2])
# if doctype == "OUT", create dummy, 0-value, varlst-length list for fieldorder key
if doctype == "OUT":
for tblname in doctbl_d:
varlst0 = [0 for i in range(len(doctbl_d[tblname]['varlst']))]
doctbl_d[tblname]['fieldorder'] = varlst0
if FLAGS['verbose']:
for tblname in sorted(doctbl_d):
print(tblname, doctbl_d[tblname]['varlst'])
def doctbld_docd_assign(dattype, doctbld, docd, varname, srctable, fldname, \
fldtype, flgwrite='N', genvar=None, genvarparam=None):
docd[varname] = {}
docd[varname]['genvarname'] = genvar
docd[varname]['genvar_p'] = genvarparam
# split works fine even if there's just one srctable
docd[varname]['srctable'] = srctable.split(',')
docd[varname]['fieldname'] = fldname
docd[varname]['flgwrite'] = {'Y':True, 'N':False}[flgwrite]
if dattype == "tbl":
if fldtype in ('double', 'int'):
docd[varname]['fieldtype'] = fldtype
else:
print("Variable %s: fieldtype '%s' is not recognized; must be 'double' or 'int'.\n" %(varname, fldtype))
# Now exit.
elif dattype == "gis": # here, fldtype is really the cell fraction grid, if any
if fldtype == 'all' or fldtype.startswith('clfr'):
docd[varname]['fieldtype'] = fldtype
else:
print("Variable %s: fieldtype '%s' is not recognized; must be 'all' or 'clfr*'.\n" %(varname, fldtype))
# Now exit.
# add variable to corresponding variable list for table(s)
for tblname in docd[varname]['srctable']:
doctbld[tblname]['varlst'].append(varname)
if FLAGS['verbose']: print("docd assignments: ",varname,docd[varname]['genvarname'], \
docd[varname]['srctable'],docd[varname]['fieldname'],docd[varname]['fieldtype'])
def load_var_arrays(doctbl_d, doc_d, data_d, out_data_d):
""" Data array will be populated into data_d[varname]
Open each table, load each requested fields and map them to variables.
Variables will be numpy arrays.
"""
import csv
# =====================================================
# LOAD AND HANDLE BasinID VARIABLE
# Basin sub-setting functionality is included.
id_var = 'BasinID'
id_fldname, id_tblname = doc_d[id_var]['fieldname'], doc_d[id_var]['srctable'][0]
# read csv table and load BasinID variable
fp = open(doctbl_d[id_tblname]['filepath'], "r")
basinid_lst = [int(row[id_fldname]) for row in csv.DictReader(fp)]
fp.close()
# Convert to int32 numpy array and load into IN
data_d[id_var] = ny.array(basinid_lst, dtype="int32")
# Create set out of global BasinID's array
# For use in basin sub-setting as input variables/tables are read in (below)
setBasinID = set(data_d[id_var])
# Copy to OUT[id_var] numpy array
out_data_d[id_var] = data_d[id_var]
if FLAGS['verbose']: print(" Number of basins to be processed: %d" % data_d[id_var].size)
# =====================================================
# LOAD ALL OTHER INPUT VARIABLES, STEPPING THROUGH INDIVIDUAL INPUT TABLES
for tbl in list(doctbl_d.keys()):
if len(doctbl_d[tbl]['varlst']) > 0:
# Initialize data_d dict with all its keys (variables), as numpy arrays
# (maybe this data_d initialization should be done in parse_cfg_vars()?
for var in doctbl_d[tbl]['varlst']:
if var != id_var:
if doc_d[var]['fieldtype'] == "double":
data_d[var] = ny.array([], dtype="float64")
#data_d[var] = ny.array([], dtype="float32")
elif doc_d[var]['fieldtype'] == "int":
data_d[var] = ny.array([], dtype="int32")
# create temporary dict {fieldname:varname} for current table (tbl),
# based on doctbl_d[tbl]['varlst'] and doc_d[varname]['fieldname']
# Then map fieldname to varname, and use in the block below
tbl_fld_var = {}
for var in doctbl_d[tbl]['varlst']:
if var != id_var:
tbl_fld_var[doc_d[var]['fieldname']] = var
if FLAGS['verbose']: print("tbl_fld_var: ", tbl_fld_var)
# Read the first row (field names)
fp = open(doctbl_d[tbl]['filepath'], "r")
fld_names_reader = csv.reader(fp)
fld_names = next(fld_names_reader)
fp.close()
# Set basinid_fld using the header (field names) reader list
# id_fldnames_lst is a list of expected basin id field names
id_fldnames_lst = ['basinid', 'BASINID']
if id_fldnames_lst[0] in fld_names:
basinid_fld = id_fldnames_lst[0]
elif id_fldnames_lst[1] in fld_names:
basinid_fld = id_fldnames_lst[1]
else:
print(" !!! Input table does not have a valid basin ID column name !!!\n")
# read csv table and load requested fields
fp = open(doctbl_d[tbl]['filepath'], "r")
csvreader = csv.DictReader(fp)
# SHOULD THERE BE A TEST TO ENSURE THAT ALL REQUESTED FIELDS
# ARE PRESENT IN THE FILE? OTHERWISE, ABORT WITH ERROR MESSAGE
for row in csvreader:
for fld,v in list(row.items()):
if int(row[basinid_fld]) in setBasinID and fld in list(tbl_fld_var.keys()):
# load requested fields into the data_d dict by
# concatenating each row value to the numpy arrays
# This test is done for every single row! It may be more
# efficient to extract indices for the requested fields, then
# just use those indices directly into the row dictionary.
# And maybe use simple reader and not DictRead, for efficiency.
var = tbl_fld_var[fld]
if var != id_var:
if doc_d[var]['fieldtype'] == "double":
data_d[var] = ny.r_[data_d[var], float(v)]
elif doc_d[var]['fieldtype'] == "int":
data_d[var] = ny.r_[data_d[var], int(v)]
fp.close()
if FLAGS['verbose']:
for var in doctbl_d[tbl]['varlst']:
print(" ", var, "(", data_d[var].size, "):", data_d[var])
def write_var_arrays(doctbl_d, doc_d, data_d):
"""
To write out variables to csv tables, use the compact
writerows() csv writer method. One way to prepare the output numpy arrays
for writing is to use zip(). eg, for 3 numpy arrays:
a = ny.array([1,2])
b = ny.array([10,20])
c = ny.array([5,7])
zip(a,b,c)
[(1, 10, 5), (2, 20, 7)]
fp = open("myfile.csv", "wb") # without the 'b', blank lines may be inserted
writer = csv.writer(fp)
writer.writerow(["fld1","fld2","fld3"])
writer.writerows(zip(a,b,c))
Getting the field order just right is a big deal.
"""
import csv
for tbl in doctbl_d:
if len(doctbl_d[tbl]['varlst']) > 0:
fldnameseq = []
writeseq = []
# remove vars that were never written out to the OUT dict
# either by choice or by oversight. Alternatively, write out None?
orderedflds = dict(list(zip(doctbl_d[tbl]['fieldorder'], doctbl_d[tbl]['varlst'])))
for ord,var in sorted(orderedflds.items()):
if var in data_d and \
var in doc_d and doc_d[var]['flgwrite']:
fldnameseq.append(doc_d[var]['fieldname'])
writeseq.append("data_d['" + var + "']")
# write requested fields to csv table
fp = open(doctbl_d[tbl]['filepath'], "w", newline='')
csvwriter = csv.writer(fp)
csvwriter.writerow(fldnameseq)
csvwriter.writerows(eval("zip(" + ",".join(writeseq) + ")"))
fp.close()
def cfg_outvars_order(fname_cfg_var, doctbl_d, doc_d):
"""
Re-read vars.cfg\[OUT.VARS] using raw file access to extract the order of
each variable (ConfigParser doesn't return the order).
1. Open cfg file and go to [OUT.VARS] line
2. Read through all lines in that section (until EOF or start of next [] section)
3. Throw away comment and blank lines (lines with nothing but white space)
4. Step through var lines.
5. For explicit vars, increment field order index
6. For generic vars, expand into multiple vars, assign field order index based
on previous var field order and parameter relative indices
(build generic-var handling functionality latere, after developing the
simpler field order extraction tools for explicit vars)
7. Match each var name to a key in OUTDOC dict
8. Update OUTDOC_TBL and OUTDOC dicts with the field order
"""
# create a dictionary of genvarname vs. var names list from doc_d
genvars_d = {}
for var in doc_d:
gv = doc_d[var]['genvarname']
if gv:
gvpar = doc_d[var]['genvar_p']
if gv in genvars_d:
genvars_d[gv]['p'].append(gvpar)
genvars_d[gv]['var'].append(var)
else:
genvars_d[gv] = {}
genvars_d[gv]['p'] = [gvpar]
genvars_d[gv]['var'] = [var]
# sort lists in the correct relative order using RUN['p'] & RUN['param_ord']
for gv in genvars_d:
if FLAGS['verbose']: print("genvars: ", gv, genvars_d[gv]['p'], genvars_d[gv]['var'])
genvars_d[gv]['p'].sort(key=lambda p: RUN['param_ord'][RUN['p'].index(p)])
genvars_d[gv]['var'].sort(key=lambda v: \
RUN['param_ord'][RUN['p'].index(doc_d[v]['genvar_p'])])
if FLAGS['verbose']: print("genvars sorted: ", gv, genvars_d[gv]['p'], genvars_d[gv]['var'])
# open file, suck in all lines, close file
f = open(fname_cfg_var, "r")
cfg_lines = f.readlines()
f.close()
# remove leading/trailing whitespace and \n, remove blank and comment lines
# Then go to sect_name line and extract only lines below it
cfg_lines = [line.strip() for line in cfg_lines]
cfg_lines = [ln for ln in cfg_lines if ln != '' and not ln.startswith("#")]
sect_name = "[OUT.VARS]"
sect_idx = cfg_lines.index(sect_name)
sect_lines = cfg_lines[sect_idx+1:]
# maybe it's best to first search for EOF or the next section header?
# though *initially*, I can safely assume this section is the last one!
# assign field order for each var/tbl
# use enumerate to extract var index (order) concurrently
# extract varname from each var line (stripping leading/trailing whitespace)
# THIS SCHEME PROBABLY BREAKS DOWN WITH MORE COMPLEX SETS OF TABLES & VARS!
# ord_offset WILL PROBABLY GET OUT OF WHACK. EVALUATE AND FIX IT.
# or maybe it's ok, just that the assigned fieldorder values are non-consecutive?
ord_offset = 0
for ordidx,line in enumerate(sect_lines):
var = line.split("=")[0].strip()
if var in genvars_d:
# expand generic var names
for varexp in genvars_d[var]['var']:
for tblname in doc_d[varexp]['srctable']:
varidx = doctbl_d[tblname]['varlst'].index(varexp)
doctbl_d[tblname]['fieldorder'][varidx] = ordidx + ord_offset
ord_offset += 1
elif var in doc_d:
for tblname in doc_d[var]['srctable']:
varidx = doctbl_d[tblname]['varlst'].index(var)
doctbl_d[tblname]['fieldorder'][varidx] = ordidx + ord_offset
else:
# Generic variable name was not expanded because it's not being used.
# The RUN parameters requested don't match the var parameter block.
# Decrease order offset to maintain a proper sequental order index
ord_offset -= 1
def ExportVar(varsave, varname, param=None):
''' Export variable (array) to the gloabl OUT dictionary, to make it
available for writing out to files. If variable is actually a literal
(single value) and not a full-length numpy array, expand it to full-length
float32 numpy array using IN['BasinID'] to extract the length.
If param is not None, the variable has a generic name and must be
expanded.
'''
global OUT
# expand to full-length array if variable is a literal or has length == 1
# Better to use numpy tools? fill() after ny.empty(), or repeat()
# [BUT ONLY IF IN['BasinID'].size > 1 AND dtype IS NOT A STRING (IE, NOT srcMax
# ARRAYS)!!! IF IN['BasinID'].size == 1, VARIABLE STILL NEEDS TO BE CONVERTED
# TO NUMPY ARRAY IF IT'S A SCALAR!]
ExpandToArrayFlg = False
if ny.isscalar(varsave) or len(varsave) == 1:
# Expand only if scalar or array is not a numpy string-type
# (There are no foreseeable cases of string scalars that would be exported)
# But must first test if variable is a numpy array!
if isinstance(varsave, ny.ndarray):
if 'string' not in varsave.dtype.name:
ExpandToArrayFlg = True
else:
ExpandToArrayFlg = True
if ExpandToArrayFlg:
varsave = ny.array(varsave, dtype='float64') \
* ny.ones(IN['BasinID'].size)
#varsave = ny.array(varsave, dtype='float32') \
if param == None:
OUT[varname] = varsave
else:
# generic var name
OUT[param + varname] = varsave
# The handling of generic var names will only work if the parameter
# is the first element of the var name!! That's very limiting and
# will need to be generalized
def cfg_simple_sections(steptype):
global CCAL, RUN, BASAREA
if steptype == "MODEL":
sect_dict = read_cfgfile(fname_cfg_cal, "CAL")
parse_cfg_ccal(sect_dict, CCAL)
sect_dict = read_cfgfile(fname_cfg_var, "MODELRUN")
parse_cfg_modelrun(sect_dict, RUN)
elif steptype == "GIS2TBLS":
sect_dict = read_cfgfile(fname_cfg_gis, "CREATEBASAREAS")
parse_cfg_basrea(sect_dict, BASAREA)
def PopulateCfgVars(fname_cfg, steptype):
""" Parse config file(s), load data into vars
steptype: "GIS2TBLS" or "MODEL"
"""
global INDOC_TBL, INDOC, IN, OUTDOC_TBL, OUTDOC, OUT
strsubs = read_cfgfile(fname_cfg_gen, "STRSUBS")
# IN sections and dictionaries
sel = {'MODEL': ('IN','TBLS','VARS'), \
'GIS2TBLS': ('INGIS','FILES','GISVARS')}
in_dict = read_cfgfile(fname_cfg, "IN")
parse_cfg_tbls(in_dict[sel[steptype][1]], strsubs, INDOC_TBL, sel[steptype][0])
parse_cfg_vars(in_dict[sel[steptype][2]], INDOC_TBL, INDOC, sel[steptype][0])
# OUT sections and dictionaries
out_dict = read_cfgfile(fname_cfg, "OUT")
parse_cfg_tbls(out_dict['TBLS'], strsubs, OUTDOC_TBL, "OUT")
parse_cfg_vars(out_dict['VARS'], OUTDOC_TBL, OUTDOC, "OUT")
cfg_outvars_order(fname_cfg, OUTDOC_TBL, OUTDOC)
# ---- copied from dissolved.py -----
R_MIN = 0.003 # 3 mm/yr
def model_dissolved(run_forms):
""" Dissolved nutrient form sub-models.
"""
# nutrient form list is limited to dissolved and actual
# model run forms ('parameters') in RUN['F']
for F in run_forms:
# DSi is implemented as a separate, isolated function.
if F == 'DIC':
Yld_F = DICModel() # Currently an empty function.
elif F == 'DSi':
Yld_F = DSiModel()
else:
# POINT (SEWAGE) SOURCES
RSpnt_E, FEpnt_F = Calc_PointSources(F)
RSpnt_F = FEpnt_F * RSpnt_E
# DIFFUSE (NON-POINT) SOURCES
# Calculate FEws_F, FEws_nat,F, f_F(Rnat)
FEws_F, FEws_nat_F, f_F = Calc_WSExportFunc(F)
# Diffuse River Sources: explicit
WSdif_ant_E, WSdif_nat_E = Calc_WSdifExplicit(F)
RSdif_expl_ant_F = FEws_F * WSdif_ant_E
RSdif_expl_nat_F = FEws_nat_F * WSdif_nat_E
# Diffuse River Sources: export coefficient
RSdif_ec_F = Calc_RSdifExportCoeff(f_F, F)
if F == 'DOC':
RSdif_ec_ant_F = 0.0
RSdif_ec_nat_F = RSdif_ec_F
else:
Agfr = IN['agric'] / 100.0
RSdif_ec_ant_F = Agfr * RSdif_ec_F
RSdif_ec_nat_F = (1 - Agfr) * RSdif_ec_F
# Total diffuse River Sources: anthropogenic vs. natural
RSdif_ant_F = RSdif_expl_ant_F + RSdif_ec_ant_F
RSdif_nat_F = RSdif_expl_nat_F + RSdif_ec_nat_F
# DISSOLVED YIELD (kg/km2/yr)
FEriv_F = Calc_FEriv(F)
#RS_ant_F = RSpnt_F + RSdif_ant_F
#RSdif_F = RSdif_ant_F + RSdif_nat_F
Yld_F = FEriv_F * (RSpnt_F + (RSdif_ant_F + RSdif_nat_F))
# SAVE VARIABLES FOR (OPTIONAL) EXPORT TO FILE
# Some are saved into global OUT dictionary mainly for reuse in SourceContrib()
ExportVar(RSdif_ec_ant_F, 'RSdif_ec_ant', F)
ExportVar(RSdif_ec_nat_F, 'RSdif_ec_nat', F)
ExportVar(RSdif_ant_F, 'RSdif_ant', F)
ExportVar(RSdif_nat_F, 'RSdif_nat', F)
ExportVar(RSpnt_F, 'RSpnt', F)
# CALCULATE SOURCE CONTRIBUTIONS
SourceContrib(F)
# DISSOLVED LOAD (ton/yr, or Mg/yr)
Ld_F = Yld_F * IN['A'] / 1000.0
# SAVE VARIABLES FOR (OPTIONAL) EXPORT TO FILE
ExportVar(Yld_F, 'Yld', F)
ExportVar(Ld_F, 'Ld', F)
def DSiModel():
""" DSi model. A multiple linear regression model, from Beusen et al. (2009)
"""
# Runoff must be in meters/yr, but current input is in mm/yr
Rnat = IN['Rnat'] / 1000.0
# Truncate (clip) input (independent) variables to the acceptable range
# before using in T_DSiyldNAT equation
IndepVarsTruncate = lambda var,minval,maxval: IN[var].clip(min=minval,max=maxval)
Precip = IndepVarsTruncate('precip',0.519952,10.9972)
GaezSlope = IndepVarsTruncate('gslope',1.95543000000000,41.9841000000000)
BulkDens = IndepVarsTruncate('bulkdens',0.93677500000000,1.6459700000000)
VolcLithFr = IndepVarsTruncate('frvolclith',0.00000000000000,0.7621180000000)
# CALCULATE BOX-COX TRANSFORMED ("T_") YIELD (ton SiO2/km2/yr), pre-dam
T_Yld_DSi_pred = 1.60765821573*log(Precip) + 0.03099949128*GaezSlope + \
-2.59587868714*BulkDens + 1.69157777610*VolcLithFr + 2.56118766111
# CALCULATE UN-TRANSFORMED YIELD (ton SiO2/km2/yr)
boxcox_lambda = 0.068623051867468
Yld_DSi_pred = (boxcox_lambda*T_Yld_DSi_pred + 1) ** (1/boxcox_lambda)
# Set Yld_DSi_pred to 0 in arid basins (Rnat < R_MIN)
Yld_DSi_pred[Rnat < R_MIN] = 0.0
# Set yield to 0 if bulk density is ~ 0
Yld_DSi_pred[IN['bulkdens'] < 0.01] = 0.0
# Unit conversion of yield, to kg Si/km2/yr
Yld_DSi_pred *= 1000*(28.09/60.09)
# Apply reservoir retention term (currently from TSS only)
D_TSS = IN['D_TSS']
Yld_DSi = (1 - D_TSS) * Yld_DSi_pred
return Yld_DSi
def DICModel():
""" DIC model. Function currently empty; DIC model development is being
done elsewhere.
"""
print("Blank DIC model function. DIC model development is being done elsewhere.")
return 0
def Calc_PointSources(F):
""" Calculate point source/sewage variables.
"""
ccalf = CCAL[F]
# element (N, P, C)
E = F[-1]
# FEpnt_F
if F == 'DIN':
# IN['hwfrem_N_aspct'] is in %, not 0-1
hwfrem_E = IN['hwfrem_N_aspct'] / 100.0
hwfrem_E_max = 0.8
FEpnt_F = 0.485 + 0.255*(hwfrem_E/hwfrem_E_max)
else:
FEpnt_F = ccalf['c']
# RSpntExc_E
if E in ('N', 'P'):
RSpntExc_E = IN['RSpntExc_'+E]
else:
RSpntExc_E = 0.0
# RSpntDet_E
if E == 'P':
RSpntDet_E = IN['RSpntDet_P']
else:
RSpntDet_E = 0.0
# RSpnt_E (total)
RSpnt_E = RSpntExc_E + RSpntDet_E
# SAVE VARIABLES FOR (OPTIONAL) EXPORT TO FILE
# Some are saved into global OUT dictionary mainly for reuse in SourceContrib()
ExportVar(RSpntExc_E, 'RSpntExc_'+E, F)
ExportVar(RSpntDet_E, 'RSpntDet_'+E, F)
ExportVar(RSpnt_E, 'RSpnt_'+E, F)