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Autopep whitespace changes
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@calebbraun
calebbraun committed Dec 18, 2018
1 parent 19c283b commit 8a187e6
Showing 1 changed file with 41 additions and 47 deletions.
88 changes: 41 additions & 47 deletions cassandra/components.py
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Original file line number Diff line number Diff line change
Expand Up @@ -729,25 +729,25 @@ class FldgenComponent(ComponentBase):
params:
loadpkgs - Flag indicating whether the fldgen and an2month packages need
to be explicitly loaded. If false, those packages must be
preinstalled in the user's R library.
preinstalled in the user's R library.
pkgdir - Directory containing R package repositories for fldgen and
an2month (ignored if loadpkgs is False).
emulator - RDS file containing the trained emulator to use for the
calculation.
ngrids - Number of climate fields to generate.
calculation.
ngrids - Number of climate fields to generate.
startyr - Starting year for the climate fields
nyear - Number of years in the climate fields. This MUST match the
number of years the emulator was trained on.
TODO: get this from the emulator when we read it in so that
TODO: get this from the emulator when we read it in so that
we don't have to set it manually.
scenario - Hector scenario to use for the mean field calculation.
RNGseed - Optional seed for the R random number generator. If omitted,
then the R instance will seed its RNG with whatever default it
normally uses.
a2mfrac - monthly fraction dataset to use for monthly downscaling. If
a2mfrac - monthly fraction dataset to use for monthly downscaling. If
omitted, the data is assumed to have been generated at monthly
resolution.
debugdir - Location to write debug file output. If omitted, no debug output
debugdir - Location to write debug file output. If omitted, no debug output
is produced.
Capability dependencies:
Expand Down Expand Up @@ -793,21 +793,19 @@ def __init__(self, cap_tbl):
self.addcapability('gridded_pr_coord')
self.addcapability('gridded_tas_coord')


def finalize_parsing(self):
self.params['loadpkgs'] = util.parseTFstring(self.params['loadpkgs'])
self.params['ngrids'] = int(self.params['ngrids'])
self.params['startyr'] = int(self.params['startyr'])
self.params['nyear'] = int(self.params['nyear'])



def run_component(self):
"""Run the fldgen and an2month R scripts."""
from rpy2.robjects.packages import importr
import rpy2.robjects as robjects
import numpy as np
from rpy2.robjects import numpy2ri
numpy2ri.activate() # enable automatic conversion of numpy objects to R equivalents.
numpy2ri.activate() # enable automatic conversion of numpy objects to R equivalents.

if self.params['loadpkgs']:
pkgdir = self.params["pkgdir"]
Expand All @@ -819,44 +817,41 @@ def run_component(self):
devtools.load_all(an2month)
devtools.load_all(fldgen)


# Import fldgen and run the generator
fldgen = importr('fldgen')
emu = fldgen.loadmodel(self.params['emulator'])
if self.params.get('RNGseed') is not None:
setseed = robjects.r['set.seed']
setseed(self.params['RNGseed'])

fullgrids_annual = self.run_fldgen(emu,fldgen)
fullgrids_annual = self.run_fldgen(emu, fldgen)

coords = self.extract_coords(emu, fldgen)

coords = self.extract_coords(emu, fldgen)

if self.params.get('a2mfrac') is None:
## Data is already at monthly resolution; however, we do still
## need to transpose it so that months are in columns.
# Data is already at monthly resolution; however, we do still
# need to transpose it so that months are in columns.
fullgrids_monthly = {}
fullgrids_monthly['pr'] = [np.transpose(np.asarray(x)) for x in fullgrids_annual['pr']]
fullgrids_monthly['tas'] = [np.transpose(np.asarray(x)) for x in fullgrids_annual['tas']]
else:
fullgrids_monthly = self.run_monthlyds(fullgrids_annual, coords)


self.addresults('gridded_pr', fullgrids_monthly['pr'])
self.addresults('gridded_tas', fullgrids_monthly['tas'])
self.addresults('gridded_pr_coord', coords['pr'])
self.addresults('gridded_tas_coord', coords['tas'])

## Produce debug output, if requested
# Produce debug output, if requested
ddir = self.params.get('debugdir')
if ddir is not None:
import os.path
import numpy as np


for var in ['tas','pr']:
for var in ['tas', 'pr']:
filestem = os.path.join(ddir, f'debug-{var}')
for i, m in enumerate(fullgrids_monthly[var]):
## Write debug output with months in rows, as it will be easier to visually scan that way.
# Write debug output with months in rows, as it will be easier to visually scan that way.
tasdata = np.transpose(m[0:10, 0:24])
filename = f'{filestem}-{i}.csv'
np.savetxt(filename, tasdata)
Expand All @@ -866,20 +861,20 @@ def run_component(self):
def run_fldgen(self, emu, fldgen):
"""Run the fldgen calculation and return the results.
:param emu: Fldgen emulator structure
:param emu: Fldgen emulator structure
:param fldgen: Fldgen package handle from rpy2
:return: Dictionary with entries 'tas' and 'pr'. Each entry is a list
of numpy arrays.
of numpy arrays.
"""
import numpy as np
## Calculate residuals

# Calculate residuals
resids = fldgen.generate_TP_resids(emu, self.params['ngrids'])

## Get global mean temperatures. This is returned as a dataframe
## containing multiple scenarios, so we need to filter it down to the
## one we want.
# Get global mean temperatures. This is returned as a dataframe
# containing multiple scenarios, so we need to filter it down to the
# one we want.
tgavdf = self.fetch('Tgav')
scen = self.params['scenario']
if scen not in tgavdf['scenario'].values:
Expand All @@ -888,26 +883,25 @@ def run_fldgen(self, emu, fldgen):

startyr = self.params['startyr']
endyr = startyr + self.params['nyear']
## We need to filter this down to just the years we are going to use
# We need to filter this down to just the years we are going to use
tgavdf = tgavdf[np.logical_and(tgavdf['year'] >= startyr, tgavdf['year'] < endyr)].loc[:, ]

year = tgavdf['year'].values
perm = np.argsort(year)
tgav = tgavdf['value'].values[perm]

fullgrids = fldgen.generate_TP_fullgrids(emu, resids, tgav)

## fullgrids is a list of paired temperature and precipitation grids. in R notation they
## are stored in fullgrids$fullgrids[[i]]$tas and fullgrids$fullgrids[[i]]$pr. We don't care about
## anything else in the fullgrids structure above. (Remember x[[1]] in R is
## x[0] in python.)
# fullgrids is a list of paired temperature and precipitation grids. in R notation they
# are stored in fullgrids$fullgrids[[i]]$tas and fullgrids$fullgrids[[i]]$pr. We don't care about
# anything else in the fullgrids structure above. (Remember x[[1]] in R is
# x[0] in python.)
gridstructs = fullgrids.rx2('fullgrids')

tas = [np.asarray(gs.rx2('tas')) for gs in gridstructs]
pr = [np.asarray(gs.rx2('pr')) for gs in gridstructs]

return {'tas':tas, 'pr':pr}

return {'tas': tas, 'pr': pr}

def extract_coords(self, emu, fldgen):
"""Extract the coordinate structure from the emulator
Expand All @@ -924,13 +918,13 @@ def extract_coords(self, emu, fldgen):
griddataT = emu[0]
griddataP = emu[1]
coords = {}
for name, griddata in zip(['tas','pr'], [griddataT, griddataP]):
for name, griddata in zip(['tas', 'pr'], [griddataT, griddataP]):
gd = dict(griddata.items())
try:
coord = np.asarray(gd['coord'])
except KeyError:
## If the grid is regular, then fldgen doesn't store a coordinate
## array. Use the coord_array function tocreate one.
# If the grid is regular, then fldgen doesn't store a coordinate
# array. Use the coord_array function tocreate one.
coord = np.asarray(fldgen.coord_array(gd['lat'], gd['lon']))
coords[name] = coord

Expand All @@ -941,27 +935,27 @@ def run_monthlyds(self, annual_flds, coords):
:param annual_flds: Structure returned from run_fldgen
:param coords: Coordinate matrix returned from fldgen
:return: Dictionary with 'pr' and 'tas' entries. Each entry is a list of
matrices of field data at monthly resolution (grid cells in rows,
:return: Dictionary with 'pr' and 'tas' entries. Each entry is a list of
matrices of field data at monthly resolution (grid cells in rows,
months in columns)
"""

from rpy2.robjects.packages import importr
import numpy as np

an2month = importr('an2month')
rslt = {}

rslt = {}
for var in annual_flds:
ntime = np.asarray(annual_flds[var][0]).shape[0] # there is probably an easier way to do this.
ntime = np.asarray(annual_flds[var][0]).shape[0] # there is probably an easier way to do this.
time = np.arange(ntime) + self.params['startyr'] - 1
monthly = an2month.downscaling_component_api(self.params['a2mfrac'], annual_flds[var],
coords[var], time, var)

if var == 'pr':
## If this is precipitation, convert units.
# If this is precipitation, convert units.
monthly = [an2month.pr_conversion(x) for x in monthly]

rslt[var] = [np.transpose(np.asarray(x)) for x in monthly]
logging.debug(f'Result for {var}: len = {len(rslt[var])}. Shape = {rslt[var][0].shape}')

Expand Down Expand Up @@ -1022,7 +1016,7 @@ def run_component(self):
retcols = ['year', 'scenario', 'variable', 'value', 'units']

tgav = scendata[scendata['variable'] == 'Tgav'].loc[:, retcols]
tgav['value'] += float(self.params['T0']) # convert anomaly to temperature
tgav['value'] += float(self.params['T0']) # convert anomaly to temperature
self.addresults('Tgav', tgav)
self.addresults('atm-co2', scendata[scendata['variable'] == 'Ca'].loc[:, retcols])
self.addresults('Ftot', scendata[scendata['variable'] == 'Ftot'].loc[:, retcols])
Expand Down

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