%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'>
If you submit the job with job scheduler; below are list of enviroment variable one can pass
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 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. For DELTA experiment, year corresponds to really 'year'
%env month=
for monitoring this corresponds to file path path-XIOS.{month}/
For DELTA experiment, year corresponds to really 'month'
proceed saving? True or False , Default is setted as True
proceed plotting? True or False , Default is setted as True
proceed computation? or just load computed result? True or False , Default is setted as True
save output file used for plotting
using kerchunked file -> False, not using kerhcunk -> True
name of control file to be used for computation/plots/save/ We have number of M_xxx.csv
Monitor.sh calls M_MLD_2D
and AWTD.sh, Fluxnet.sh, Siconc.sh, IceClim.sh, FWC_SSH.sh, Integrals.sh , Sections.sh
M_AWTMD
M_Fluxnet
M_Ice_quantities
M_IceClim M_IceConce M_IceThick
M_FWC_2D M_FWC_integrals M_FWC_SSH M_SSH_anomaly
M_Mean_temp_velo M_Mooring
M_Sectionx M_Sectiony
%%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= irene5109.c-irene.mg1.tgcc.ccc.cea.fr starting dask cluster on local= True workers 16 10000000000 rome local cluster starting This code is running on irene5109.c-irene.mg1.tgcc.ccc.cea.fr using SEDNA_DELTA_MONITOR file experiment, read from ../lib/SEDNA_DELTA_MONITOR.yaml on year= 2012 on month= 04 outputpath= ../results/SEDNA_DELTA_MONITOR/ daskreport= ../results/dask/6419599irene5109.c-irene.mg1.tgcc.ccc.cea.fr_SEDNA_DELTA_MONITOR_04M_Fluxnet/ CPU times: user 597 ms, sys: 148 ms, total: 744 ms Wall time: 21.4 s
Client-9be4a869-13e4-11ed-8d04-080038b983db
Connection method: Cluster object | Cluster type: distributed.LocalCluster |
Dashboard: http://127.0.0.1:8787/status |
7c58f52a
Dashboard: http://127.0.0.1:8787/status | Workers: 16 |
Total threads: 128 | Total memory: 251.06 GiB |
Status: running | Using processes: True |
Scheduler-6c7ee32c-62dd-461d-8f70-84529a3e48ba
Comm: tcp://127.0.0.1:40443 | Workers: 16 |
Dashboard: http://127.0.0.1:8787/status | Total threads: 128 |
Started: Just now | Total memory: 251.06 GiB |
Comm: tcp://127.0.0.1:34120 | Total threads: 8 |
Dashboard: http://127.0.0.1:39349/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:42631 | |
Local directory: /tmp/dask-worker-space/worker-y5mhsrp_ |
Comm: tcp://127.0.0.1:33655 | Total threads: 8 |
Dashboard: http://127.0.0.1:41249/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:39636 | |
Local directory: /tmp/dask-worker-space/worker-3vr0k7m1 |
Comm: tcp://127.0.0.1:43542 | Total threads: 8 |
Dashboard: http://127.0.0.1:39864/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:43473 | |
Local directory: /tmp/dask-worker-space/worker-7ki6zv95 |
Comm: tcp://127.0.0.1:37168 | Total threads: 8 |
Dashboard: http://127.0.0.1:34510/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:36060 | |
Local directory: /tmp/dask-worker-space/worker-pvsiev_o |
Comm: tcp://127.0.0.1:45937 | Total threads: 8 |
Dashboard: http://127.0.0.1:44120/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:32867 | |
Local directory: /tmp/dask-worker-space/worker-nvp0n9rm |
Comm: tcp://127.0.0.1:45049 | Total threads: 8 |
Dashboard: http://127.0.0.1:42762/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:41888 | |
Local directory: /tmp/dask-worker-space/worker-aazqem90 |
Comm: tcp://127.0.0.1:43232 | Total threads: 8 |
Dashboard: http://127.0.0.1:33893/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:37315 | |
Local directory: /tmp/dask-worker-space/worker-wrn6mh03 |
Comm: tcp://127.0.0.1:40878 | Total threads: 8 |
Dashboard: http://127.0.0.1:37645/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:41818 | |
Local directory: /tmp/dask-worker-space/worker-cou4yfhf |
Comm: tcp://127.0.0.1:35455 | Total threads: 8 |
Dashboard: http://127.0.0.1:37140/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:39443 | |
Local directory: /tmp/dask-worker-space/worker-bhdyup62 |
Comm: tcp://127.0.0.1:40133 | Total threads: 8 |
Dashboard: http://127.0.0.1:41076/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:40636 | |
Local directory: /tmp/dask-worker-space/worker-eul2gg4_ |
Comm: tcp://127.0.0.1:41824 | Total threads: 8 |
Dashboard: http://127.0.0.1:45327/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:45709 | |
Local directory: /tmp/dask-worker-space/worker-t33s7oot |
Comm: tcp://127.0.0.1:38561 | Total threads: 8 |
Dashboard: http://127.0.0.1:33134/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:36031 | |
Local directory: /tmp/dask-worker-space/worker-4vf_ap7g |
Comm: tcp://127.0.0.1:38067 | Total threads: 8 |
Dashboard: http://127.0.0.1:44170/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:38994 | |
Local directory: /tmp/dask-worker-space/worker-6d1sujkq |
Comm: tcp://127.0.0.1:39055 | Total threads: 8 |
Dashboard: http://127.0.0.1:34325/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:45523 | |
Local directory: /tmp/dask-worker-space/worker-9cuvmzyy |
Comm: tcp://127.0.0.1:36699 | Total threads: 8 |
Dashboard: http://127.0.0.1:35606/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:40329 | |
Local directory: /tmp/dask-worker-space/worker-xfmis_2y |
Comm: tcp://127.0.0.1:46017 | Total threads: 8 |
Dashboard: http://127.0.0.1:44665/status | Memory: 15.69 GiB |
Nanny: tcp://127.0.0.1:36657 | |
Local directory: /tmp/dask-worker-space/worker-tg6lxsva |
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 | |
---|---|---|---|---|---|---|---|---|---|---|
Fluxnet | gridV.vomecrty,param.e3v_0,param.e1v,param.mas... | calc.Fluxnet(data) | FramS_All | Fluxnet_integrals | None | ((-10,10),(-10,50) ,(-150,50),(-25,5) ) | (Sv,TW, mSv,10^-2 Sv) | I-6 | ||
Fluxnet | gridV.vomecrty,param.e3v_0,param.e1v,param.mas... | calc.Fluxnet(data) | Davis | Fluxnet_integrals | None | ((-5.0,5.0),(-25,27) ,(-200,50),(-9,5) ) | (Sv,TW, mSv,10^-2 Sv) | I-6 | ||
Fluxnet | gridV.vomecrty,param.e3v_0,param.e1v,param.mas... | calc.Fluxnet(data) | Bering | Fluxnet_integrals | None | ((-2,2),(-10,50) ,(-150,50),(-2,4) ) | (Sv,TW, mSv,10^-2 Sv) | I-6 |
Each computation consists of
%%time
import os
calcswitch=os.environ.get('calc', 'True')
lazy=os.environ.get('lazy','False' )
loaddata=((df.Inputs != '').any())
print('calcswitch=',calcswitch,'df.Inputs != nothing',loaddata, 'lazy=',lazy)
data = load.datas(catalog_url,df.Inputs,month,year,daskreport,lazy=lazy) if ((calcswitch=='True' )*loaddata) else 0
data
calcswitch= True df.Inputs != nothing True lazy= False ../lib/SEDNA_DELTA_MONITOR.yaml using param_xios reading ../lib/SEDNA_DELTA_MONITOR.yaml using param_xios reading <bound method DataSourceBase.describe of sources: param_xios: args: combine: nested concat_dim: y urlpath: /ccc/work/cont003/gen7420/odakatin/CONFIGS/SEDNA/SEDNA-I/SEDNA_Domain_cfg_Tgt_20210423_tsh10m_L1/param_f32/x_*.nc xarray_kwargs: compat: override coords: minimal data_vars: minimal parallel: true description: SEDNA NEMO parameters from MPI output nav_lon lat fails driver: intake_xarray.netcdf.NetCDFSource metadata: catalog_dir: /ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/../lib/ > {'name': 'param_xios', 'container': 'xarray', 'plugin': ['netcdf'], 'driver': ['netcdf'], 'description': 'SEDNA NEMO parameters from MPI output nav_lon lat fails', 'direct_access': 'forbid', 'user_parameters': [{'name': 'path', 'description': 'file coordinate', 'type': 'str', 'default': '/ccc/work/cont003/gen7420/odakatin/CONFIGS/SEDNA/MESH/SEDNA_mesh_mask_Tgt_20210423_tsh10m_L1/param'}], 'metadata': {}, 'args': {'urlpath': '/ccc/work/cont003/gen7420/odakatin/CONFIGS/SEDNA/SEDNA-I/SEDNA_Domain_cfg_Tgt_20210423_tsh10m_L1/param_f32/x_*.nc', 'combine': 'nested', 'concat_dim': 'y'}} 0 read gridS ['vosaline'] lazy= False using load_data_xios_kerchunk reading gridS using load_data_xios_kerchunk reading <bound method DataSourceBase.describe of sources: data_xios_kerchunk: args: consolidated: false storage_options: fo: file:////ccc/cont003/home/ra5563/ra5563/catalogue/DELTA/201204/gridS_0[0-5][0-9][0-9].json target_protocol: file urlpath: reference:// description: CREG025 NEMO outputs from different xios server in kerchunk format driver: intake_xarray.xzarr.ZarrSource metadata: catalog_dir: /ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/../lib/ > took 43.43989181518555 seconds 0 merging gridS ['vosaline'] 1 read gridT ['votemper'] lazy= False using load_data_xios_kerchunk reading gridT using load_data_xios_kerchunk reading <bound method DataSourceBase.describe of sources: data_xios_kerchunk: args: consolidated: false storage_options: fo: file:////ccc/cont003/home/ra5563/ra5563/catalogue/DELTA/201204/gridT_0[0-5][0-9][0-9].json target_protocol: file urlpath: reference:// description: CREG025 NEMO outputs from different xios server in kerchunk format driver: intake_xarray.xzarr.ZarrSource metadata: catalog_dir: /ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/../lib/ > took 19.458295583724976 seconds 1 merging gridT ['votemper'] took 0.7658843994140625 seconds 2 read gridV ['vomecrty'] lazy= False using load_data_xios_kerchunk reading gridV using load_data_xios_kerchunk reading <bound method DataSourceBase.describe of sources: data_xios_kerchunk: args: consolidated: false storage_options: fo: file:////ccc/cont003/home/ra5563/ra5563/catalogue/DELTA/201204/gridV_0[0-5][0-9][0-9].json target_protocol: file urlpath: reference:// description: CREG025 NEMO outputs from different xios server in kerchunk format driver: intake_xarray.xzarr.ZarrSource metadata: catalog_dir: /ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/../lib/ > took 29.37765336036682 seconds 2 merging gridV ['vomecrty'] took 0.9338371753692627 seconds 3 read icemod ['sivolu', 'sivelv'] lazy= False using load_data_xios_kerchunk reading icemod using load_data_xios_kerchunk reading <bound method DataSourceBase.describe of sources: data_xios_kerchunk: args: consolidated: false storage_options: fo: file:////ccc/cont003/home/ra5563/ra5563/catalogue/DELTA/201204/icemod_0[0-5][0-9][0-9].json target_protocol: file urlpath: reference:// description: CREG025 NEMO outputs from different xios server in kerchunk format driver: intake_xarray.xzarr.ZarrSource metadata: catalog_dir: /ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/../lib/ > took 33.46159505844116 seconds 3 merging icemod ['sivolu', 'sivelv'] took 0.8142223358154297 seconds param nav_lon will be included in data param mask will be included in data param mask2d will be included in data param e1v will be included in data param e3v_0 will be included in data param nav_lat will be included in data CPU times: user 1min 22s, sys: 8.85 s, total: 1min 31s Wall time: 2min 32s
<xarray.Dataset> Dimensions: (t: 30, z: 150, y: 6540, x: 6560) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:00:00 * y (y) int64 1 2 3 4 5 6 7 ... 6535 6536 6537 6538 6539 6540 * x (x) int64 1 2 3 4 5 6 7 ... 6555 6556 6557 6558 6559 6560 nav_lat (y, x) float32 dask.array<chunksize=(13, 6560), meta=np.ndarray> nav_lon (y, x) float32 dask.array<chunksize=(13, 6560), meta=np.ndarray> * z (z) int64 1 2 3 4 5 6 7 8 ... 143 144 145 146 147 148 149 150 mask (z, y, x) bool dask.array<chunksize=(150, 13, 6560), meta=np.ndarray> mask2d (y, x) bool dask.array<chunksize=(13, 6560), meta=np.ndarray> e1v (y, x) float64 dask.array<chunksize=(13, 6560), meta=np.ndarray> e3v_0 (z, y, x) float64 dask.array<chunksize=(150, 13, 6560), meta=np.ndarray> Data variables: vosaline (t, z, y, x) float32 dask.array<chunksize=(1, 150, 13, 6560), meta=np.ndarray> votemper (t, z, y, x) float32 dask.array<chunksize=(1, 150, 13, 6560), meta=np.ndarray> vomecrty (t, z, y, x) float32 dask.array<chunksize=(1, 150, 13, 6560), meta=np.ndarray> sivolu (t, y, x) float32 dask.array<chunksize=(1, 13, 6560), meta=np.ndarray> sivelv (t, y, x) float32 dask.array<chunksize=(1, 13, 6560), meta=np.ndarray> Attributes: (12/26) CASE: DELTA CONFIG: SEDNA Conventions: CF-1.6 DOMAIN_dimensions_ids: [2, 3] DOMAIN_halo_size_end: [0, 0] DOMAIN_halo_size_start: [0, 0] ... ... nj: 13 output_frequency: 1d start_date: 20090101 timeStamp: 2022-Jan-21 08:38:37 GMT title: ocean T grid variables uuid: d277f069-4681-4bdc-a897-fbf6d4f734e8
%%time
monitor.auto(df,data,savefig,daskreport,outputpath,file_exp='SEDNA'
)
#calc= True #save= True #plot= False Value='Fluxnet' Zone='FramS_All' Plot='Fluxnet_integrals' cmap='None' clabel='(Sv,TW, mSv,10^-2 Sv)' clim= ((-10, 10), (-10, 50), (-150, 50), (-25, 5)) outputpath='../results/SEDNA_DELTA_MONITOR/' nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/' filename='SEDNA_Fluxnet_integrals_FramS_All_Fluxnet' data=monitor.optimize_dataset(data) #2 Zooming Data data= zoom.FramS_All(data) data=monitor.optimize_dataset(data)
<xarray.Dataset> Dimensions: (t: 30, z: 150, y: 2, x: 601) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:00:00 * y (y) int64 2608 2609 * x (x) int64 3734 3735 3736 3737 3738 ... 4331 4332 4333 4334 nav_lat (y, x) float32 dask.array<chunksize=(2, 601), meta=np.ndarray> nav_lon (y, x) float32 dask.array<chunksize=(2, 601), meta=np.ndarray> * z (z) int64 1 2 3 4 5 6 7 8 ... 143 144 145 146 147 148 149 150 mask (z, y, x) bool dask.array<chunksize=(150, 2, 601), meta=np.ndarray> mask2d (y, x) bool dask.array<chunksize=(2, 601), meta=np.ndarray> e1v (y, x) float64 dask.array<chunksize=(2, 601), meta=np.ndarray> e3v_0 (z, y, x) float64 dask.array<chunksize=(150, 2, 601), meta=np.ndarray> Data variables: vosaline (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 601), meta=np.ndarray> votemper (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 601), meta=np.ndarray> vomecrty (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 601), meta=np.ndarray> sivolu (t, y, x, z) float32 dask.array<chunksize=(1, 2, 601, 150), meta=np.ndarray> sivelv (t, y, x, z) float32 dask.array<chunksize=(1, 2, 601, 150), meta=np.ndarray> Attributes: (12/26) CASE: DELTA CONFIG: SEDNA Conventions: CF-1.6 DOMAIN_dimensions_ids: [2, 3] DOMAIN_halo_size_end: [0, 0] DOMAIN_halo_size_start: [0, 0] ... ... nj: 13 output_frequency: 1d start_date: 20090101 timeStamp: 2022-Jan-21 08:38:37 GMT title: ocean T grid variables uuid: d277f069-4681-4bdc-a897-fbf6d4f734e8
#3 Start computing data= calc.Fluxnet(data) monitor.optimize_dataset(data) add optimise here once otimise can recognise
<xarray.Dataset> Dimensions: (t: 30) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:0... y int64 2608 Data variables: Volume flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Ice export (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray>
#4 Saving SEDNA_Fluxnet_integrals_FramS_All_Fluxnet data=save.datas(data,plot=Plot,path=nc_outputpath,filename=filename) start saving data saving data in a csv file ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_FramS_All_Fluxnet2012-04-01_2012-04-30.nc save computed data at ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_FramS_All_Fluxnet2012-04-01_2012-04-30.nc completed Value='Fluxnet' Zone='Davis' Plot='Fluxnet_integrals' cmap='None' clabel='(Sv,TW, mSv,10^-2 Sv)' clim= ((-5.0, 5.0), (-25, 27), (-200, 50), (-9, 5)) outputpath='../results/SEDNA_DELTA_MONITOR/' nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/' filename='SEDNA_Fluxnet_integrals_Davis_Fluxnet' data=monitor.optimize_dataset(data) #2 Zooming Data data= zoom.Davis(data) data=monitor.optimize_dataset(data)
<xarray.Dataset> Dimensions: (t: 30, z: 150, y: 2, x: 421) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:00:00 * y (y) int64 1308 1309 * x (x) int64 1749 1750 1751 1752 1753 ... 2166 2167 2168 2169 nav_lat (y, x) float32 dask.array<chunksize=(1, 421), meta=np.ndarray> nav_lon (y, x) float32 dask.array<chunksize=(1, 421), meta=np.ndarray> * z (z) int64 1 2 3 4 5 6 7 8 ... 143 144 145 146 147 148 149 150 mask (z, y, x) bool dask.array<chunksize=(150, 1, 421), meta=np.ndarray> mask2d (y, x) bool dask.array<chunksize=(1, 421), meta=np.ndarray> e1v (y, x) float64 dask.array<chunksize=(1, 421), meta=np.ndarray> e3v_0 (z, y, x) float64 dask.array<chunksize=(150, 1, 421), meta=np.ndarray> Data variables: vosaline (t, z, y, x) float32 dask.array<chunksize=(1, 150, 1, 421), meta=np.ndarray> votemper (t, z, y, x) float32 dask.array<chunksize=(1, 150, 1, 421), meta=np.ndarray> vomecrty (t, z, y, x) float32 dask.array<chunksize=(1, 150, 1, 421), meta=np.ndarray> sivolu (t, y, x, z) float32 dask.array<chunksize=(1, 1, 421, 150), meta=np.ndarray> sivelv (t, y, x, z) float32 dask.array<chunksize=(1, 1, 421, 150), meta=np.ndarray> Attributes: (12/26) CASE: DELTA CONFIG: SEDNA Conventions: CF-1.6 DOMAIN_dimensions_ids: [2, 3] DOMAIN_halo_size_end: [0, 0] DOMAIN_halo_size_start: [0, 0] ... ... nj: 13 output_frequency: 1d start_date: 20090101 timeStamp: 2022-Jan-21 08:38:37 GMT title: ocean T grid variables uuid: d277f069-4681-4bdc-a897-fbf6d4f734e8
#3 Start computing data= calc.Fluxnet(data) monitor.optimize_dataset(data) add optimise here once otimise can recognise
<xarray.Dataset> Dimensions: (t: 30) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:0... y int64 1308 Data variables: Volume flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Ice export (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray>
#4 Saving SEDNA_Fluxnet_integrals_Davis_Fluxnet data=save.datas(data,plot=Plot,path=nc_outputpath,filename=filename) start saving data saving data in a csv file ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_Davis_Fluxnet2012-04-01_2012-04-30.nc save computed data at ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_Davis_Fluxnet2012-04-01_2012-04-30.nc completed Value='Fluxnet' Zone='Bering' Plot='Fluxnet_integrals' cmap='None' clabel='(Sv,TW, mSv,10^-2 Sv)' clim= ((-2, 2), (-10, 50), (-150, 50), (-2, 4)) outputpath='../results/SEDNA_DELTA_MONITOR/' nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/' filename='SEDNA_Fluxnet_integrals_Bering_Fluxnet' data=monitor.optimize_dataset(data) #2 Zooming Data data= zoom.Bering(data) data=monitor.optimize_dataset(data)
<xarray.Dataset> Dimensions: (t: 30, z: 150, y: 2, x: 146) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:00:00 * y (y) int64 6538 6539 * x (x) int64 2421 2422 2423 2424 2425 ... 2563 2564 2565 2566 nav_lat (y, x) float32 dask.array<chunksize=(2, 146), meta=np.ndarray> nav_lon (y, x) float32 dask.array<chunksize=(2, 146), meta=np.ndarray> * z (z) int64 1 2 3 4 5 6 7 8 ... 143 144 145 146 147 148 149 150 mask (z, y, x) bool dask.array<chunksize=(150, 2, 146), meta=np.ndarray> mask2d (y, x) bool dask.array<chunksize=(2, 146), meta=np.ndarray> e1v (y, x) float64 dask.array<chunksize=(2, 146), meta=np.ndarray> e3v_0 (z, y, x) float64 dask.array<chunksize=(150, 2, 146), meta=np.ndarray> Data variables: vosaline (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 146), meta=np.ndarray> votemper (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 146), meta=np.ndarray> vomecrty (t, z, y, x) float32 dask.array<chunksize=(1, 150, 2, 146), meta=np.ndarray> sivolu (t, y, x, z) float32 dask.array<chunksize=(1, 2, 146, 150), meta=np.ndarray> sivelv (t, y, x, z) float32 dask.array<chunksize=(1, 2, 146, 150), meta=np.ndarray> Attributes: (12/26) CASE: DELTA CONFIG: SEDNA Conventions: CF-1.6 DOMAIN_dimensions_ids: [2, 3] DOMAIN_halo_size_end: [0, 0] DOMAIN_halo_size_start: [0, 0] ... ... nj: 13 output_frequency: 1d start_date: 20090101 timeStamp: 2022-Jan-21 08:38:37 GMT title: ocean T grid variables uuid: d277f069-4681-4bdc-a897-fbf6d4f734e8
#3 Start computing data= calc.Fluxnet(data) monitor.optimize_dataset(data) add optimise here once otimise can recognise
<xarray.Dataset> Dimensions: (t: 30) Coordinates: time_centered (t) object dask.array<chunksize=(1,), meta=np.ndarray> * t (t) object 2012-04-01 12:00:00 ... 2012-04-30 12:0... y int64 6538 Data variables: Volume flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Net (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater Northward (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Ice export (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Volume flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Heat flux South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray> Freshwater South (t) float64 dask.array<chunksize=(1,), meta=np.ndarray>
#4 Saving SEDNA_Fluxnet_integrals_Bering_Fluxnet data=save.datas(data,plot=Plot,path=nc_outputpath,filename=filename) start saving data saving data in a csv file ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_Bering_Fluxnet2012-04-01_2012-04-30.nc save computed data at ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_Fluxnet_integrals_Bering_Fluxnet2012-04-01_2012-04-30.nc completed CPU times: user 23.6 s, sys: 1.01 s, total: 24.7 s Wall time: 32.3 s