%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= irene4404.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 irene4404.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/6475893irene4404.c-irene.mg1.tgcc.ccc.cea.fr_SEDNA_DELTA_MONITOR_04M_IceClim/ CPU times: user 509 ms, sys: 146 ms, total: 655 ms Wall time: 18.4 s
Client-afe99dfe-196b-11ed-a0d0-080038b9352d
| Connection method: Cluster object | Cluster type: distributed.LocalCluster |
| Dashboard: http://127.0.0.1:8787/status |
d77f071d
| Dashboard: http://127.0.0.1:8787/status | Workers: 16 |
| Total threads: 128 | Total memory: 251.06 GiB |
| Status: running | Using processes: True |
Scheduler-060bc7b4-d4a6-4474-a5e4-c848396ea7d2
| Comm: tcp://127.0.0.1:35626 | Workers: 16 |
| Dashboard: http://127.0.0.1:8787/status | Total threads: 128 |
| Started: Just now | Total memory: 251.06 GiB |
| Comm: tcp://127.0.0.1:44769 | Total threads: 8 |
| Dashboard: http://127.0.0.1:33992/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:36057 | |
| Local directory: /tmp/dask-worker-space/worker-tu2vqls5 | |
| Comm: tcp://127.0.0.1:38020 | Total threads: 8 |
| Dashboard: http://127.0.0.1:41890/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:39297 | |
| Local directory: /tmp/dask-worker-space/worker-zws41ar0 | |
| Comm: tcp://127.0.0.1:46296 | Total threads: 8 |
| Dashboard: http://127.0.0.1:41002/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:36471 | |
| Local directory: /tmp/dask-worker-space/worker-on_2w3hw | |
| Comm: tcp://127.0.0.1:42951 | Total threads: 8 |
| Dashboard: http://127.0.0.1:40122/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:38807 | |
| Local directory: /tmp/dask-worker-space/worker-_6615ct2 | |
| Comm: tcp://127.0.0.1:33776 | Total threads: 8 |
| Dashboard: http://127.0.0.1:37820/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:42527 | |
| Local directory: /tmp/dask-worker-space/worker-bpxk6t67 | |
| Comm: tcp://127.0.0.1:41384 | Total threads: 8 |
| Dashboard: http://127.0.0.1:37817/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:37052 | |
| Local directory: /tmp/dask-worker-space/worker-82_7h6p3 | |
| Comm: tcp://127.0.0.1:32915 | Total threads: 8 |
| Dashboard: http://127.0.0.1:38891/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:45303 | |
| Local directory: /tmp/dask-worker-space/worker-krjoa0ou | |
| Comm: tcp://127.0.0.1:46398 | Total threads: 8 |
| Dashboard: http://127.0.0.1:35402/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:46128 | |
| Local directory: /tmp/dask-worker-space/worker-jjrtk6o0 | |
| Comm: tcp://127.0.0.1:34161 | Total threads: 8 |
| Dashboard: http://127.0.0.1:40337/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:39749 | |
| Local directory: /tmp/dask-worker-space/worker-ytshmvjj | |
| Comm: tcp://127.0.0.1:43680 | Total threads: 8 |
| Dashboard: http://127.0.0.1:33876/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:35284 | |
| Local directory: /tmp/dask-worker-space/worker-ioig609h | |
| Comm: tcp://127.0.0.1:36899 | Total threads: 8 |
| Dashboard: http://127.0.0.1:42797/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:35280 | |
| Local directory: /tmp/dask-worker-space/worker-ejzwkc1m | |
| Comm: tcp://127.0.0.1:43217 | Total threads: 8 |
| Dashboard: http://127.0.0.1:44781/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:35398 | |
| Local directory: /tmp/dask-worker-space/worker-8vh2g9gp | |
| Comm: tcp://127.0.0.1:43673 | Total threads: 8 |
| Dashboard: http://127.0.0.1:33516/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:36504 | |
| Local directory: /tmp/dask-worker-space/worker-o0iai17y | |
| Comm: tcp://127.0.0.1:33020 | Total threads: 8 |
| Dashboard: http://127.0.0.1:46167/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:37194 | |
| Local directory: /tmp/dask-worker-space/worker-72adnwxp | |
| Comm: tcp://127.0.0.1:40530 | Total threads: 8 |
| Dashboard: http://127.0.0.1:36499/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:43322 | |
| Local directory: /tmp/dask-worker-space/worker-fhfxcdr5 | |
| Comm: tcp://127.0.0.1:36008 | Total threads: 8 |
| Dashboard: http://127.0.0.1:32881/status | Memory: 15.69 GiB |
| Nanny: tcp://127.0.0.1:37704 | |
| Local directory: /tmp/dask-worker-space/worker-8u24mbxr | |
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 | |
|---|---|---|---|---|---|---|---|---|---|---|
| IceClim | calc.IceClim_load(data,nc_outputpath) | ALL | IceClim | Spectral | (0,5) | m | M-4 |
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 False lazy= True CPU times: user 287 µs, sys: 45 µs, total: 332 µs Wall time: 332 µs
0
%%time
monitor.auto(df,data,savefig,daskreport,outputpath,file_exp='SEDNA'
)
#calc= True
#save= False
#plot= True
Value='IceClim'
Zone='ALL'
Plot='IceClim'
cmap='Spectral'
clabel='m'
clim= (0, 5)
outputpath='../results/SEDNA_DELTA_MONITOR/'
nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/'
filename='SEDNA_IceClim_ALL_IceClim'
#3 Start computing
data= calc.IceClim_load(data,nc_outputpath)
monitor.optimize_dataset(data)
start loading data
filename= ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_maps_ALL_IceConce/t_*/y_*/x_*.nc dim ('x', 'y', 't')
load computed data completed
start loading data
filename= ../nc_results/SEDNA_DELTA_MONITOR/SEDNA_maps_ALL_IceThickness/t_*/y_*/x_*.nc dim ('x', 'y', 't')
load computed data completed
add optimise here once otimise can recognise
<xarray.Dataset>
Dimensions: (t: 61, y: 6540, x: 6560)
Coordinates:
nav_lat (y, x) float32 dask.array<chunksize=(130, 6560), meta=np.ndarray>
nav_lon (y, x) float32 dask.array<chunksize=(130, 6560), meta=np.ndarray>
* t (t) object 2012-03-01 12:00:00 ... 2012-04-30 12:00:00
* y (y) int64 1 2 3 4 5 6 7 8 ... 6534 6535 6536 6537 6538 6539 6540
* x (x) int64 1 2 3 4 5 6 7 8 ... 6554 6555 6556 6557 6558 6559 6560
mask2d (y, x) bool dask.array<chunksize=(130, 6560), meta=np.ndarray>
Data variables:
siconc (t, y, x) float32 dask.array<chunksize=(31, 130, 6560), meta=np.ndarray>
sivolu (t, y, x) float32 dask.array<chunksize=(31, 130, 6560), meta=np.ndarray>#5 Plotting filename= plots.IceClim(data,path=outputpath,filename=filename,save=savefig,cmap=cmap,clim=clim,clabel=clabel) ../results/SEDNA_DELTA_MONITOR/SEDNA_IceClim_ALL_IceClim_20120301-20120430.html starts plotting
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/geoviews/operation/projection.py:99: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry. if proj_geom.geom_type == 'GeometryCollection' and len(proj_geom) == 0: /ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/geoviews/operation/projection.py:99: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry. if proj_geom.geom_type == 'GeometryCollection' and len(proj_geom) == 0:
../results/SEDNA_DELTA_MONITOR/SEDNA_IceClim_ALL_IceClim_20120301-20120430.html created
CPU times: user 34min 33s, sys: 9min 25s, total: 43min 59s Wall time: 43min 43s