Code style fix for precip variabliity codes

pcmdi_metrics/precip_variability/README.md

@@ -1,16 +1,16 @@
 # Precip variability across time scales
 
 ## Driver code:
-./variability_across_timescales_PS_3hr_driver.py 
+./variability_across_timescales_PS_3hr_driver.py
 
 ## Parameter codes:
-./param/variability_across_timescales_PS_3hr_params_IMERG.py 
-./param/variability_across_timescales_PS_3hr_params_TRMM.py 
-./param/variability_across_timescales_PS_3hr_params_CMORPH.py 
-./param/variability_across_timescales_PS_3hr_params_cmip5.py 
-./param/variability_across_timescales_PS_3hr_params_cmip6.py 
+./param/variability_across_timescales_PS_3hr_params_IMERG.py
+./param/variability_across_timescales_PS_3hr_params_TRMM.py
+./param/variability_across_timescales_PS_3hr_params_CMORPH.py
+./param/variability_across_timescales_PS_3hr_params_cmip5.py
+./param/variability_across_timescales_PS_3hr_params_cmip6.py
 
 ## Run scripts:
-./scripts_pcmdi/run_obs.bash 
-./scripts_pcmdi/run_cmip5.bash 
-./scripts_pcmdi/run_cmip6.bash 
+./scripts_pcmdi/run_obs.bash
+./scripts_pcmdi/run_cmip5.bash
+./scripts_pcmdi/run_cmip6.bash

pcmdi_metrics/precip_variability/lib/__init__.py

@@ -1,2 +1,11 @@
 from .argparse_functions import AddParserArgument # noqa
-from .lib_variability_across_timescales import (Regrid2deg, ClimAnom, Powerspectrum, lag1_autocorrelation, rednoise, RedNoiseSignificanceLevel, Avg_PS_DomFrq, prdday_to_frqidx) # noqa
+from .lib_variability_across_timescales import ( # noqa
+ Avg_PS_DomFrq,
+ ClimAnom,
+ Powerspectrum,
+ RedNoiseSignificanceLevel,
+ Regrid2deg,
+ lag1_autocorrelation,
+ prdday_to_frqidx,
+ rednoise,
+)

pcmdi_metrics/precip_variability/lib/argparse_functions.py

@@ -1,75 +1,73 @@
 def AddParserArgument(P):
- P.add_argument("--mip",
- type=str,
- dest='mip',
- default=None,
- help="cmip5, cmip6 or other mip")
- P.add_argument("--mod",
- type=str,
- dest='mod',
- default=None,
- help="model")
- P.add_argument("--var",
- type=str,
- dest='var',
- default=None,
- help="pr or other variable")
- P.add_argument("--frq",
- type=str,
- dest='frq',
- default=None,
- help="day, 3hr or other frequency")
- P.add_argument("--modpath",
- type=str,
- dest='modpath',
- default=None,
- help="data directory path")
- P.add_argument("--results_dir",
- type=str,
- dest='results_dir',
- default=None,
- help="results directory path")
- P.add_argument("--case_id",
- type=str,
- dest='case_id',
- default=None,
- help="case_id with date")
- P.add_argument("--prd",
- type=int,
- dest='prd',
- nargs='+',
- default=None,
- help="start- and end-year for analysis (e.g., 1985 2004)")
- P.add_argument("--fac",
- type=str,
- dest='fac',
- default=None,
- help="factor to make unit of [mm/day]")
- P.add_argument("--nperseg",
- type=int,
- dest='nperseg',
- default=None,
- help="length of segment in power spectra")
- P.add_argument("--noverlap",
- type=int,
- dest='noverlap',
- default=None,
- help="length of overlap between segments in power spectra")
- P.add_argument("--ref",
- type=str,
- dest='ref',
- default=None,
- help="reference data path")
- P.add_argument("--cmec",
- dest="cmec",
- default=False,
- action="store_true",
- help="Use to save CMEC format metrics JSON")
- P.add_argument("--no_cmec",
- dest="cmec",
- default=False,
- action="store_false",
- help="Do not save CMEC format metrics JSON")
+ P.add_argument(
+ "--mip", type=str, dest="mip", default=None, help="cmip5, cmip6 or other mip"
+ )
+ P.add_argument("--mod", type=str, dest="mod", default=None, help="model")
+ P.add_argument(
+ "--var", type=str, dest="var", default=None, help="pr or other variable"
+ )
+ P.add_argument(
+ "--frq", type=str, dest="frq", default=None, help="day, 3hr or other frequency"
+ )
+ P.add_argument(
+ "--modpath", type=str, dest="modpath", default=None, help="data directory path"
+ )
+ P.add_argument(
+ "--results_dir",
+ type=str,
+ dest="results_dir",
+ default=None,
+ help="results directory path",
+ )
+ P.add_argument(
+ "--case_id", type=str, dest="case_id", default=None, help="case_id with date"
+ )
+ P.add_argument(
+ "--prd",
+ type=int,
+ dest="prd",
+ nargs="+",
+ default=None,
+ help="start- and end-year for analysis (e.g., 1985 2004)",
+ )
+ P.add_argument(
+ "--fac",
+ type=str,
+ dest="fac",
+ default=None,
+ help="factor to make unit of [mm/day]",
+ )
+ P.add_argument(
+ "--nperseg",
+ type=int,
+ dest="nperseg",
+ default=None,
+ help="length of segment in power spectra",
+ )
+ P.add_argument(
+ "--noverlap",
+ type=int,
+ dest="noverlap",
+ default=None,
+ help="length of overlap between segments in power spectra",
+ )
+ P.add_argument(
+ "--ref", type=str, dest="ref", default=None, help="reference data path"
+ )
+ P.add_argument(
+ "--cmec",
+ dest="cmec",
+ default=False,
+ action="store_true",
+ help="Use to save CMEC format metrics JSON",
+ )
+ P.add_argument(
+ "--no_cmec",
+ dest="cmec",
+ default=False,
+ action="store_false",
+ help="Do not save CMEC format metrics JSON",
+ )
  P.set_defaults(cmec=False)
 
  return P

pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py

@@ -1,14 +1,15 @@
+import math
+import sys
+
 import cdms2 as cdms
-import MV2 as MV
 import cdutil
 import genutil
+import MV2 as MV
 import numpy as np
+import pandas as pd
 from regrid2 import Horizontal
 from scipy import signal
 from scipy.stats import chi2
-import pandas as pd
-import math
-import sys
 
 
 # ==================================================================================
@@ -74,8 +75,7 @@ def ClimAnom(d, ntd, syr, eyr):
  )
  )
  yrtmpseg = MV.reshape(
- yrtmp, (int(yrtmp.shape[0] / ntd), ntd,
- yrtmp.shape[1], yrtmp.shape[2])
+ yrtmp, (int(yrtmp.shape[0] / ntd), ntd, yrtmp.shape[1], yrtmp.shape[2])
  )
  if yrtmpseg.shape[0] == 365:
  dseg[iyr, 0:59] = yrtmpseg[0:59]
@@ -99,8 +99,7 @@ def ClimAnom(d, ntd, syr, eyr):
  )
  )
  yrtmpseg = MV.reshape(
- yrtmp, (int(yrtmp.shape[0] / ntd), ntd,
- yrtmp.shape[1], yrtmp.shape[2])
+ yrtmp, (int(yrtmp.shape[0] / ntd), ntd, yrtmp.shape[1], yrtmp.shape[2])
  )
  dseg[iyr] = yrtmpseg
 
@@ -128,8 +127,7 @@ def ClimAnom(d, ntd, syr, eyr):
  if yrtmp.shape[0] == 365 * ntd:
  anom = np.append(
  anom,
- (np.delete(dseg[iyr], 59, axis=0) -
- np.delete(clim, 59, axis=0)),
+ (np.delete(dseg[iyr], 59, axis=0) - np.delete(clim, 59, axis=0)),
  )
  else:
  anom = np.append(anom, (dseg[iyr] - clim))
@@ -251,8 +249,7 @@ def rednoise(VAR, NUMHAR, R1):
  RN = []
  for K in range(NUMHAR):
  RN.append(
- WHITENOISE *
- (TOP / (BOT - R1X2 * float(math.cos(math.pi * K / NUMHAR))))
+ WHITENOISE * (TOP / (BOT - R1X2 * float(math.cos(math.pi * K / NUMHAR))))
  )
  return RN
 
@@ -289,28 +286,42 @@ def Avg_PS_DomFrq(d, frequency, ntd, dat, mip, frc):
  Output
  - psdmfm: Domain and Frequency averaged of spectral power (json)
  """
- domains = ["Total_50S50N", "Ocean_50S50N", "Land_50S50N",
- "Total_30N50N", "Ocean_30N50N", "Land_30N50N",
- "Total_30S30N", "Ocean_30S30N", "Land_30S30N",
- "Total_50S30S", "Ocean_50S30S", "Land_50S30S"]
+ domains = [
+ "Total_50S50N",
+ "Ocean_50S50N",
+ "Land_50S50N",
+ "Total_30N50N",
+ "Ocean_30N50N",
+ "Land_30N50N",
+ "Total_30S30N",
+ "Ocean_30S30N",
+ "Land_30S30N",
+ "Total_50S30S",
+ "Ocean_50S30S",
+ "Land_50S30S",
+ ]
 
  if ntd == 8: # 3-hourly data
  frqs_forced = ["semi-diurnal", "diurnal", "semi-annual", "annual"]
- frqs_unforced = ["sub-daily", "synoptic",
- "sub-seasonal", "seasonal-annual", "interannual"]
+ frqs_unforced = [
+ "sub-daily",
+ "synoptic",
+ "sub-seasonal",
+ "seasonal-annual",
+ "interannual",
+ ]
  elif ntd == 1: # daily data
  frqs_forced = ["semi-annual", "annual"]
- frqs_unforced = ["synoptic", "sub-seasonal",
- "seasonal-annual", "interannual"]
+ frqs_unforced = ["synoptic", "sub-seasonal", "seasonal-annual", "interannual"]
  else:
- sys.exit("ERROR: ntd "+ntd+" is not defined!")
+ sys.exit("ERROR: ntd " + ntd + " is not defined!")
 
  if frc == "forced":
  frqs = frqs_forced
  elif frc == "unforced":
  frqs = frqs_unforced
  else:
- sys.exit("ERROR: frc "+frc+" is not defined!")
+ sys.exit("ERROR: frc " + frc + " is not defined!")
 
  mask = cdutil.generateLandSeaMask(d[0])
  d, mask2 = genutil.grower(d, mask)
@@ -329,52 +340,48 @@ def Avg_PS_DomFrq(d, frequency, ntd, dat, mip, frc):
  dmask = d
 
  if "50S50N" in dom:
- am = cdutil.averager(
- dmask(latitude=(-50, 50)), axis="xy")
+ am = cdutil.averager(dmask(latitude=(-50, 50)), axis="xy")
  if "30N50N" in dom:
- am = cdutil.averager(
- dmask(latitude=(30, 50)), axis="xy")
+ am = cdutil.averager(dmask(latitude=(30, 50)), axis="xy")
  if "30S30N" in dom:
- am = cdutil.averager(
- dmask(latitude=(-30, 30)), axis="xy")
+ am = cdutil.averager(dmask(latitude=(-30, 30)), axis="xy")
  if "50S30S" in dom:
- am = cdutil.averager(
- dmask(latitude=(-50, -30)), axis="xy")
+ am = cdutil.averager(dmask(latitude=(-50, -30)), axis="xy")
  am = np.array(am)
 
  for frq in frqs:
- if (frq == 'semi-diurnal'): # pr=0.5day
+ if frq == "semi-diurnal": # pr=0.5day
  idx = prdday_to_frqidx(0.5, frequency, ntd)
  amfm = am[idx]
- elif (frq == 'diurnal'): # pr=1day
+ elif frq == "diurnal": # pr=1day
  idx = prdday_to_frqidx(1, frequency, ntd)
  amfm = am[idx]
- elif (frq == 'semi-annual'): # 180day=<pr=<183day
+ elif frq == "semi-annual": # 180day=<pr=<183day
  idx2 = prdday_to_frqidx(180, frequency, ntd)
  idx1 = prdday_to_frqidx(183, frequency, ntd)
- amfm = np.amax(am[idx1:idx2+1])
- elif (frq == 'annual'): # 360day=<pr=<366day
+ amfm = np.amax(am[idx1 : idx2 + 1])
+ elif frq == "annual": # 360day=<pr=<366day
  idx2 = prdday_to_frqidx(360, frequency, ntd)
  idx1 = prdday_to_frqidx(366, frequency, ntd)
- amfm = np.amax(am[idx1:idx2+1])
- elif (frq == 'sub-daily'): # pr<1day
+ amfm = np.amax(am[idx1 : idx2 + 1])
+ elif frq == "sub-daily": # pr<1day
  idx1 = prdday_to_frqidx(1, frequency, ntd)
- amfm = cdutil.averager(am[idx1+1:], weights='unweighted')
- elif (frq == 'synoptic'): # 1day=<pr<20day
+ amfm = cdutil.averager(am[idx1 + 1 :], weights="unweighted")
+ elif frq == "synoptic": # 1day=<pr<20day
  idx2 = prdday_to_frqidx(1, frequency, ntd)
  idx1 = prdday_to_frqidx(20, frequency, ntd)
- amfm = cdutil.averager(am[idx1+1:idx2+1], weights='unweighted')
- elif (frq == 'sub-seasonal'): # 20day=<pr<90day
+ amfm = cdutil.averager(am[idx1 + 1 : idx2 + 1], weights="unweighted")
+ elif frq == "sub-seasonal": # 20day=<pr<90day
  idx2 = prdday_to_frqidx(20, frequency, ntd)
  idx1 = prdday_to_frqidx(90, frequency, ntd)
- amfm = cdutil.averager(am[idx1+1:idx2+1], weights='unweighted')
- elif (frq == 'seasonal-annual'): # 90day=<pr<365day
+ amfm = cdutil.averager(am[idx1 + 1 : idx2 + 1], weights="unweighted")
+ elif frq == "seasonal-annual": # 90day=<pr<365day
  idx2 = prdday_to_frqidx(90, frequency, ntd)
  idx1 = prdday_to_frqidx(365, frequency, ntd)
- amfm = cdutil.averager(am[idx1+1:idx2+1], weights='unweighted')
- elif (frq == 'interannual'): # 365day=<pr
+ amfm = cdutil.averager(am[idx1 + 1 : idx2 + 1], weights="unweighted")
+ elif frq == "interannual": # 365day=<pr
  idx2 = prdday_to_frqidx(365, frequency, ntd)
- amfm = cdutil.averager(am[:idx2+1], weights='unweighted')
+ amfm = cdutil.averager(am[: idx2 + 1], weights="unweighted")
  psdmfm[dom][frq] = amfm.tolist()
 
  print("Complete domain and frequency average of spectral power")

pcmdi_metrics/precip_variability/param/variability_across_timescales_PS_3hr_params_CMORPH.py

@@ -16,9 +16,10 @@
 infile = "*.nc"
 
 case_id = "{:v%Y%m%d}".format(datetime.datetime.now())
-pmpdir = "/work/ahn6/pr/variability_across_timescales/power_spectrum/"+ver+"_test/"
+pmpdir = "/work/ahn6/pr/variability_across_timescales/power_spectrum/" + ver + "_test/"
 results_dir = os.path.join(
- pmpdir, '%(output_type)', 'precip_variability', '%(mip)', '%(case_id)')
+ pmpdir, "%(output_type)", "precip_variability", "%(mip)", "%(case_id)"
+)
 
 xmldir = "./xml_obs/"
 if not (os.path.isdir(xmldir)):

pcmdi_metrics/precip_variability/param/variability_across_timescales_PS_3hr_params_IMERG.py

@@ -16,9 +16,10 @@
 infile = "*.nc"
 
 case_id = "{:v%Y%m%d}".format(datetime.datetime.now())
-pmpdir = "/work/ahn6/pr/variability_across_timescales/power_spectrum/"+ver+"_test/"
+pmpdir = "/work/ahn6/pr/variability_across_timescales/power_spectrum/" + ver + "_test/"
 results_dir = os.path.join(
- pmpdir, '%(output_type)', 'precip_variability', '%(mip)', '%(case_id)')
+ pmpdir, "%(output_type)", "precip_variability", "%(mip)", "%(case_id)"
+)
 
 xmldir = "./xml_obs/"
 if not (os.path.isdir(xmldir)):