%matplotlib inline
import pandas as pd
import socket
host = socket.getfqdn()
from core import load, zoom, calc, save,plots,monitor
#reload funcs after updating ./core/*.py
import importlib
importlib.reload(load)
importlib.reload(zoom)
importlib.reload(calc)
importlib.reload(save)
importlib.reload(plots)
importlib.reload(monitor)
<module 'core.monitor' from '/ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/core/monitor.py'>
# 'month': = 'JOBID' almost month but not really,
# If you submit the job with job scheduler, above
#below are list of enviroment variable one can pass
#%env local='2"
# local : if True run dask local cluster, if not true, put number of workers
# setted in the 'local'
# if no 'local ' given, local will be setted automatically to 'True'
#%env ychunk='2'
#%env tchunk='2'
# controls chunk. 'False' sets no modification from original netcdf file's chunk.
# ychunk=10 will group the original netcdf file to 10 by 10
# tchunk=1 will chunk the time coordinate one by one
#%env control=FWC_SSH
# name of control file to be used for computation/plots/save/
#%env file_exp=
# 'file_exp': Which 'experiment' name is it?
#. this corresopnds to intake catalog name without path and .yaml
#%env year=
# for Validation, this correspoinds to path/year/month 's year
# for monitoring, this corresponids to 'date' having * means do all files in the monitoring directory
# setting it as *0[0-9] &*1[0-9]& *[2-3][0-9], the job can be separated in three lots.
#%env month=
# for monitoring this corresponds to file path path-XIOS.{month}/
#
#%env save= proceed saving? True or False , Default is setted as True
#%env plot= proceed plotting? True or False , Default is setted as True
#%env calc= proceed computation? or just load computed result? True or False , Default is setted as True
#%env save=False
%%time
# 'savefig': Do we save output in html? or not. keep it true.
savefig=True
client,cluster,control,catalog_url,month,year,daskreport,outputpath = load.set_control(host)
!mkdir -p $outputpath
!mkdir -p $daskreport
client
local True using host= irene5683.c-irene.mg1.tgcc.ccc.cea.fr starting dask cluster on local= True workers 16 10000000000 False not local in tgcc rome local cluster starting This code is running on irene5683.c-irene.mg1.tgcc.ccc.cea.fr using SEDNA_ALPHA_MONITOR file experiment, read from ../lib/SEDNA_ALPHA_MONITOR.yaml on year= * on month= 26 outputpath= ../results/SEDNA_ALPHA_MONITOR/26/ daskreport= ../results/dask/2586522irene5683.c-irene.mg1.tgcc.ccc.cea.fr_SEDNA_ALPHA_MONITOR_26FWC_integrals/ CPU times: user 348 ms, sys: 277 ms, total: 625 ms Wall time: 10.3 s
Client
|
Cluster
|
df=load.controlfile(control)
#Take out 'later' tagged computations
#df=df[~df['Value'].str.contains('later')]
df
Value | Inputs | Equation | Zone | Plot | Colourmap | MinMax | Unit | Oldname | Unnamed: 10 | |
---|---|---|---|---|---|---|---|---|---|---|
FWC_integrals | calc.FWC_load_integrals(data,nc_outputpath) | BBFG | FWC_integrals | (12000,24000) | Km^3 | I-1 |
Each computation consists of
%%time
import os
calcswitch=os.environ.get('calc', 'True')
loaddata=((df.Inputs != '').any())
print('calcswitch=',calcswitch,'df.Inputs != nothing',loaddata)
data = load.datas(catalog_url,df.Inputs,month,year,daskreport) if ((calcswitch=='True' )*loaddata) else 0
data
calcswitch= False df.Inputs != nothing False CPU times: user 588 µs, sys: 151 µs, total: 739 µs Wall time: 692 µs
0
%%time
monitor.auto(df,data,savefig,daskreport,outputpath,file_exp='SEDNA'
)
#calc= False #save= False #plot= True Zone='BBFG' Value='FWC_integrals' cmap='' clabel='Km^3' clim= (12000, 24000) outputpath='../results/SEDNA_ALPHA_MONITOR/26/' nc_outputpath='../nc_results/SEDNA_ALPHA_MONITOR/26/' filename='SEDNA_FWC_integrals_BBFG_FWC_integrals' #3 no computing , loading starts dtaa=save.load_data(plot=Plot,path=nc_outputpath,filename=filename) start saving data load 1Dnc file from ../nc_results/SEDNA_ALPHA_MONITOR/26/../*/SEDNA_FWC_integrals_BBFG_FWC_integrals*.nc load computed data completed
<xarray.Dataset> Dimensions: (t: 71) Coordinates: * t (t) object 2004-07-01 12:00:00 ... 2004-10-10 12:00:00 Data variables: FWC_Arctic (t) float64 dask.array<chunksize=(31,), meta=np.ndarray> FWC_CRF (t) float64 dask.array<chunksize=(31,), meta=np.ndarray>
array([cftime.DatetimeNoLeap(2004, 7, 1, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 2, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 3, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 4, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 5, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 6, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 7, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 8, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 9, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 10, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 11, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 12, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 13, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 14, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 15, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 16, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 17, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 18, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 19, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 20, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 21, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 22, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 23, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 24, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 25, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 26, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 27, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 28, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 29, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 30, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 7, 31, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 1, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 2, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 3, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 4, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 5, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 6, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 7, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 8, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 9, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 10, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 11, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 12, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 13, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 14, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 15, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 16, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 17, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 18, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 19, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 20, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 21, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 22, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 23, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 24, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 25, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 26, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 27, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 28, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 29, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 9, 30, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 1, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 2, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 3, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 4, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 5, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 6, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 7, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 8, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 9, 12, 0, 0, 0), cftime.DatetimeNoLeap(2004, 10, 10, 12, 0, 0, 0)], dtype=object)
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#5 Plotting filename= plots.FWC_integrals(data,path=outputpath,filename=filename,save=savefig,cmap=cmap,clim=clim,clabel=clabel) title SEDNA_FWC_integrals_BBFG_FWC_integrals
WARNING:param.CurvePlot03274: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend. WARNING:param.CurvePlot03291: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend.
../results/SEDNA_ALPHA_MONITOR/26/SEDNA_FWC_integrals_BBFG_FWC_integrals_20040701-20041010.html starts plotting plotting ../results/SEDNA_ALPHA_MONITOR/26/SEDNA_FWC_integrals_BBFG_FWC_integrals_20040701-20041010.html ../results/SEDNA_ALPHA_MONITOR/26/SEDNA_FWC_integrals_BBFG_FWC_integrals_20040701-20041010.html created
CPU times: user 1.02 s, sys: 305 ms, total: 1.33 s Wall time: 5.29 s