In [1]:
%matplotlib inline
import pandas as pd
import socket
host = socket.getfqdn()

from core import  load, zoom, calc, save,plots,monitor
In [2]:
#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)
Out[2]:
<module 'core.monitor' from '/ccc/work/cont003/gen7420/odakatin/monitor-sedna/notebook/core/monitor.py'>

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 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 control=FWC_SSH¶

name of control file to be used for computation/plots/save/ & how it is called from Monitor.sh¶

Monitor.sh calls M_MLD_2D

and AWTD.sh, Fluxnet.sh, Siconc.sh, IceClim.sh, FWC_SSH.sh

  • AWTD.sh M_AWTMD

  • Fluxnet.sh M_Fluxnet

  • Siconc.sh M_Ice_quantities
  • IceClim.sh M_IceClim M_IceConce M_IceThick

FWC_SSH.sh M_FWC_2D M_FWC_integrals M_FWC_SSH M_SSH_anomaly

Integrals.sh M_Mean_temp_velo M_Mooring M_Sectionx M_Sectiony

%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¶

%env lazy=False¶

For debugging this cell can help¶

%env file_exp=SEDNA_DELTA_MONITOR %env year=2012 %env month=01

0[1-2]¶

%env ychunk=10 %env ychunk=False %env save=False %env plot=True %env calc=True # %env lazy=False

False¶

%env control=M_Fluxnet

M_Sectiony ok with ychunk=False local=True lazy=False¶

In [3]:
%%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= irene4604.c-irene.mg1.tgcc.ccc.cea.fr starting dask cluster on local= True workers 16
10000000000
False
tgcc local cluster starting
This code is running on  irene4604.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= 01  outputpath= ../results/SEDNA_DELTA_MONITOR/ daskreport= ../results/dask/6419110irene4604.c-irene.mg1.tgcc.ccc.cea.fr_SEDNA_DELTA_MONITOR_01M_AWTMD/
CPU times: user 3.76 s, sys: 741 ms, total: 4.5 s
Wall time: 1min 33s
Out[3]:

Client

Client-ec42dfc4-13d8-11ed-be3a-080038b9474d

Connection method: Cluster object Cluster type: distributed.LocalCluster
Dashboard: http://127.0.0.1:8787/status

Cluster Info

LocalCluster

b4c53324

Dashboard: http://127.0.0.1:8787/status Workers: 64
Total threads: 256 Total memory: 251.06 GiB
Status: running Using processes: True

Scheduler Info

Scheduler

Scheduler-848add83-1f56-408b-b081-537ce6a36d13

Comm: tcp://127.0.0.1:33368 Workers: 64
Dashboard: http://127.0.0.1:8787/status Total threads: 256
Started: 1 minute ago Total memory: 251.06 GiB

Workers

Worker: 0

Comm: tcp://127.0.0.1:33076 Total threads: 4
Dashboard: http://127.0.0.1:42568/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36906
Local directory: /tmp/dask-worker-space/worker-5erg1uzh

Worker: 1

Comm: tcp://127.0.0.1:44402 Total threads: 4
Dashboard: http://127.0.0.1:41747/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35118
Local directory: /tmp/dask-worker-space/worker-fp1q5c72

Worker: 2

Comm: tcp://127.0.0.1:42439 Total threads: 4
Dashboard: http://127.0.0.1:38039/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45380
Local directory: /tmp/dask-worker-space/worker-25_cmehr

Worker: 3

Comm: tcp://127.0.0.1:38040 Total threads: 4
Dashboard: http://127.0.0.1:40638/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42929
Local directory: /tmp/dask-worker-space/worker-wtv8zc9a

Worker: 4

Comm: tcp://127.0.0.1:34351 Total threads: 4
Dashboard: http://127.0.0.1:44811/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33027
Local directory: /tmp/dask-worker-space/worker-wi9feq6a

Worker: 5

Comm: tcp://127.0.0.1:34749 Total threads: 4
Dashboard: http://127.0.0.1:37416/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:34502
Local directory: /tmp/dask-worker-space/worker-oyx6vdx9

Worker: 6

Comm: tcp://127.0.0.1:44569 Total threads: 4
Dashboard: http://127.0.0.1:45900/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43612
Local directory: /tmp/dask-worker-space/worker-i290y6uf

Worker: 7

Comm: tcp://127.0.0.1:46813 Total threads: 4
Dashboard: http://127.0.0.1:44805/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36061
Local directory: /tmp/dask-worker-space/worker-g67khqiz

Worker: 8

Comm: tcp://127.0.0.1:45839 Total threads: 4
Dashboard: http://127.0.0.1:46566/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35747
Local directory: /tmp/dask-worker-space/worker-7f0m7rzx

Worker: 9

Comm: tcp://127.0.0.1:37616 Total threads: 4
Dashboard: http://127.0.0.1:45107/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37927
Local directory: /tmp/dask-worker-space/worker-li500pm1

Worker: 10

Comm: tcp://127.0.0.1:37518 Total threads: 4
Dashboard: http://127.0.0.1:33838/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42263
Local directory: /tmp/dask-worker-space/worker-9mlgyzdc

Worker: 11

Comm: tcp://127.0.0.1:44081 Total threads: 4
Dashboard: http://127.0.0.1:37795/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:34806
Local directory: /tmp/dask-worker-space/worker-d1acoji2

Worker: 12

Comm: tcp://127.0.0.1:34090 Total threads: 4
Dashboard: http://127.0.0.1:38132/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:34255
Local directory: /tmp/dask-worker-space/worker-8tei1qel

Worker: 13

Comm: tcp://127.0.0.1:33566 Total threads: 4
Dashboard: http://127.0.0.1:43002/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33292
Local directory: /tmp/dask-worker-space/worker-j18wv0ck

Worker: 14

Comm: tcp://127.0.0.1:37718 Total threads: 4
Dashboard: http://127.0.0.1:42669/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40329
Local directory: /tmp/dask-worker-space/worker-8xci732t

Worker: 15

Comm: tcp://127.0.0.1:33828 Total threads: 4
Dashboard: http://127.0.0.1:44540/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45955
Local directory: /tmp/dask-worker-space/worker-qd8hip7t

Worker: 16

Comm: tcp://127.0.0.1:37558 Total threads: 4
Dashboard: http://127.0.0.1:35059/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42406
Local directory: /tmp/dask-worker-space/worker-blniqljk

Worker: 17

Comm: tcp://127.0.0.1:33918 Total threads: 4
Dashboard: http://127.0.0.1:43762/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38693
Local directory: /tmp/dask-worker-space/worker-8s2rucbs

Worker: 18

Comm: tcp://127.0.0.1:45103 Total threads: 4
Dashboard: http://127.0.0.1:42860/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36673
Local directory: /tmp/dask-worker-space/worker-d8fi5nzi

Worker: 19

Comm: tcp://127.0.0.1:38319 Total threads: 4
Dashboard: http://127.0.0.1:33880/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:34997
Local directory: /tmp/dask-worker-space/worker-0ubbwnkw

Worker: 20

Comm: tcp://127.0.0.1:35708 Total threads: 4
Dashboard: http://127.0.0.1:33417/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40389
Local directory: /tmp/dask-worker-space/worker-egs97s2j

Worker: 21

Comm: tcp://127.0.0.1:34256 Total threads: 4
Dashboard: http://127.0.0.1:33602/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:34411
Local directory: /tmp/dask-worker-space/worker-8subw54e

Worker: 22

Comm: tcp://127.0.0.1:45816 Total threads: 4
Dashboard: http://127.0.0.1:44330/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33815
Local directory: /tmp/dask-worker-space/worker-iihlewp_

Worker: 23

Comm: tcp://127.0.0.1:46122 Total threads: 4
Dashboard: http://127.0.0.1:42993/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33544
Local directory: /tmp/dask-worker-space/worker-cyb9mf5g

Worker: 24

Comm: tcp://127.0.0.1:33744 Total threads: 4
Dashboard: http://127.0.0.1:37658/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37618
Local directory: /tmp/dask-worker-space/worker-rjqsoxk3

Worker: 25

Comm: tcp://127.0.0.1:46506 Total threads: 4
Dashboard: http://127.0.0.1:46060/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38854
Local directory: /tmp/dask-worker-space/worker-t0miru_i

Worker: 26

Comm: tcp://127.0.0.1:39693 Total threads: 4
Dashboard: http://127.0.0.1:39063/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38457
Local directory: /tmp/dask-worker-space/worker-cp5sxm67

Worker: 27

Comm: tcp://127.0.0.1:42161 Total threads: 4
Dashboard: http://127.0.0.1:41699/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35297
Local directory: /tmp/dask-worker-space/worker-0i701k0i

Worker: 28

Comm: tcp://127.0.0.1:35523 Total threads: 4
Dashboard: http://127.0.0.1:38871/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39278
Local directory: /tmp/dask-worker-space/worker-_bset0zh

Worker: 29

Comm: tcp://127.0.0.1:34210 Total threads: 4
Dashboard: http://127.0.0.1:33537/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42082
Local directory: /tmp/dask-worker-space/worker-x3kvblpt

Worker: 30

Comm: tcp://127.0.0.1:42450 Total threads: 4
Dashboard: http://127.0.0.1:36088/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36988
Local directory: /tmp/dask-worker-space/worker-_tb6lfrp

Worker: 31

Comm: tcp://127.0.0.1:34538 Total threads: 4
Dashboard: http://127.0.0.1:45799/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33152
Local directory: /tmp/dask-worker-space/worker-16qg7bgc

Worker: 32

Comm: tcp://127.0.0.1:46676 Total threads: 4
Dashboard: http://127.0.0.1:35503/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42545
Local directory: /tmp/dask-worker-space/worker-xejux_js

Worker: 33

Comm: tcp://127.0.0.1:41707 Total threads: 4
Dashboard: http://127.0.0.1:44738/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:44316
Local directory: /tmp/dask-worker-space/worker-s4857g1o

Worker: 34

Comm: tcp://127.0.0.1:42632 Total threads: 4
Dashboard: http://127.0.0.1:38544/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41001
Local directory: /tmp/dask-worker-space/worker-o079w5ba

Worker: 35

Comm: tcp://127.0.0.1:32997 Total threads: 4
Dashboard: http://127.0.0.1:34193/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36099
Local directory: /tmp/dask-worker-space/worker-xh1z3861

Worker: 36

Comm: tcp://127.0.0.1:35811 Total threads: 4
Dashboard: http://127.0.0.1:33279/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45802
Local directory: /tmp/dask-worker-space/worker-9cx4a2or

Worker: 37

Comm: tcp://127.0.0.1:33899 Total threads: 4
Dashboard: http://127.0.0.1:34204/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:46238
Local directory: /tmp/dask-worker-space/worker-mdzg8wf3

Worker: 38

Comm: tcp://127.0.0.1:35173 Total threads: 4
Dashboard: http://127.0.0.1:33950/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39400
Local directory: /tmp/dask-worker-space/worker-gqxsavdw

Worker: 39

Comm: tcp://127.0.0.1:36751 Total threads: 4
Dashboard: http://127.0.0.1:39456/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38139
Local directory: /tmp/dask-worker-space/worker-osorcjrf

Worker: 40

Comm: tcp://127.0.0.1:40973 Total threads: 4
Dashboard: http://127.0.0.1:38234/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39766
Local directory: /tmp/dask-worker-space/worker-tu9yppjk

Worker: 41

Comm: tcp://127.0.0.1:34486 Total threads: 4
Dashboard: http://127.0.0.1:38066/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:46521
Local directory: /tmp/dask-worker-space/worker-3fgpf4xf

Worker: 42

Comm: tcp://127.0.0.1:42466 Total threads: 4
Dashboard: http://127.0.0.1:36182/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36590
Local directory: /tmp/dask-worker-space/worker-0a6frhsm

Worker: 43

Comm: tcp://127.0.0.1:38002 Total threads: 4
Dashboard: http://127.0.0.1:33962/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33913
Local directory: /tmp/dask-worker-space/worker-ct20fqlj

Worker: 44

Comm: tcp://127.0.0.1:41528 Total threads: 4
Dashboard: http://127.0.0.1:32959/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41487
Local directory: /tmp/dask-worker-space/worker-hm7krr3m

Worker: 45

Comm: tcp://127.0.0.1:37786 Total threads: 4
Dashboard: http://127.0.0.1:41374/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39909
Local directory: /tmp/dask-worker-space/worker-ehi9z6se

Worker: 46

Comm: tcp://127.0.0.1:38627 Total threads: 4
Dashboard: http://127.0.0.1:33249/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39324
Local directory: /tmp/dask-worker-space/worker-rwu_ezag

Worker: 47

Comm: tcp://127.0.0.1:40972 Total threads: 4
Dashboard: http://127.0.0.1:44067/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38044
Local directory: /tmp/dask-worker-space/worker-lnn8g2jb

Worker: 48

Comm: tcp://127.0.0.1:40527 Total threads: 4
Dashboard: http://127.0.0.1:37391/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37843
Local directory: /tmp/dask-worker-space/worker-2ytadab8

Worker: 49

Comm: tcp://127.0.0.1:46614 Total threads: 4
Dashboard: http://127.0.0.1:37109/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:32771
Local directory: /tmp/dask-worker-space/worker-iqu8u98l

Worker: 50

Comm: tcp://127.0.0.1:34371 Total threads: 4
Dashboard: http://127.0.0.1:37717/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36951
Local directory: /tmp/dask-worker-space/worker-yj0edgi3

Worker: 51

Comm: tcp://127.0.0.1:38191 Total threads: 4
Dashboard: http://127.0.0.1:34734/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35847
Local directory: /tmp/dask-worker-space/worker-4a3bzcge

Worker: 52

Comm: tcp://127.0.0.1:45336 Total threads: 4
Dashboard: http://127.0.0.1:38606/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43277
Local directory: /tmp/dask-worker-space/worker-k7mxs5_f

Worker: 53

Comm: tcp://127.0.0.1:34850 Total threads: 4
Dashboard: http://127.0.0.1:36482/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43590
Local directory: /tmp/dask-worker-space/worker-gtuqyam3

Worker: 54

Comm: tcp://127.0.0.1:44988 Total threads: 4
Dashboard: http://127.0.0.1:44584/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43844
Local directory: /tmp/dask-worker-space/worker-6qht5_l7

Worker: 55

Comm: tcp://127.0.0.1:33008 Total threads: 4
Dashboard: http://127.0.0.1:33505/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39620
Local directory: /tmp/dask-worker-space/worker-xgwzgfqm

Worker: 56

Comm: tcp://127.0.0.1:42810 Total threads: 4
Dashboard: http://127.0.0.1:42345/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45452
Local directory: /tmp/dask-worker-space/worker-o5er5aim

Worker: 57

Comm: tcp://127.0.0.1:37871 Total threads: 4
Dashboard: http://127.0.0.1:42546/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40848
Local directory: /tmp/dask-worker-space/worker-kgwpq54e

Worker: 58

Comm: tcp://127.0.0.1:35543 Total threads: 4
Dashboard: http://127.0.0.1:33862/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39395
Local directory: /tmp/dask-worker-space/worker-uqdnl3g4

Worker: 59

Comm: tcp://127.0.0.1:44168 Total threads: 4
Dashboard: http://127.0.0.1:40586/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35586
Local directory: /tmp/dask-worker-space/worker-he6dwlp4

Worker: 60

Comm: tcp://127.0.0.1:34424 Total threads: 4
Dashboard: http://127.0.0.1:35893/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:46426
Local directory: /tmp/dask-worker-space/worker-tvgv9pci

Worker: 61

Comm: tcp://127.0.0.1:41680 Total threads: 4
Dashboard: http://127.0.0.1:42685/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:44746
Local directory: /tmp/dask-worker-space/worker-fz8m6juw

Worker: 62

Comm: tcp://127.0.0.1:45446 Total threads: 4
Dashboard: http://127.0.0.1:43445/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40526
Local directory: /tmp/dask-worker-space/worker-fr735bdo

Worker: 63

Comm: tcp://127.0.0.1:36097 Total threads: 4
Dashboard: http://127.0.0.1:45161/status Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42875
Local directory: /tmp/dask-worker-space/worker-gspro31m

read plotting information from a csv file¶

In [4]:
df=load.controlfile(control)
#Take out 'later' tagged computations
#df=df[~df['Value'].str.contains('later')]
df
Out[4]:
Value Inputs Equation Zone Plot Colourmap MinMax Unit Oldname Unnamed: 10
AW_maxtemp_depth gridT.votemper,gridS.vosaline,param.mask,param... calc.AWTD4(data) ALL AWTD_map jet (0,800) m M-5

Computation starts here¶

Each computation consists of

  1. Load NEMO data set
  2. Zoom data set
  3. Compute (or load computed data set)
  4. Save
  5. Plot
  6. Close
In [5]:
%%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/201201/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 35.775102615356445 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/201201/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 36.24394702911377 seconds
1 merging gridT ['votemper']
      took 0.8498268127441406 seconds
param mask2d will be included in data
param nav_lat will be included in data
param nav_lon will be included in data
param mask will be included in data
param depth will be included in data
CPU times: user 49.9 s, sys: 14.2 s, total: 1min 4s
Wall time: 2min 7s
Out[5]:
<xarray.Dataset>
Dimensions:        (t: 31, z: 150, y: 6540, x: 6560)
Coordinates:
    time_centered  (t) object dask.array<chunksize=(1,), meta=np.ndarray>
  * t              (t) object 2012-01-01 12:00:00 ... 2012-01-31 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
  * z              (z) int64 1 2 3 4 5 6 7 8 ... 143 144 145 146 147 148 149 150
    mask2d         (y, x) bool dask.array<chunksize=(13, 6560), meta=np.ndarray>
    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>
    mask           (z, y, x) bool dask.array<chunksize=(150, 13, 6560), meta=np.ndarray>
    depth          (z, y, x) float32 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>
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-17 19:00:16 GMT
    title:                   ocean T grid variables
    uuid:                    d8db76f6-a436-451a-9ab1-72dc892753af
xarray.Dataset
    • t: 31
    • z: 150
    • y: 6540
    • x: 6560
    • time_centered
      (t)
      object
      dask.array<chunksize=(1,), meta=np.ndarray>
      bounds :
      time_centered_bounds
      long_name :
      Time axis
      standard_name :
      time
      time_origin :
      1900-01-01 00:00:00
      Array Chunk
      Bytes 248 B 8 B
      Shape (31,) (1,)
      Count 189 Tasks 31 Chunks
      Type object numpy.ndarray
      31 1
    • t
      (t)
      object
      2012-01-01 12:00:00 ... 2012-01-...
      axis :
      T
      bounds :
      time_counter_bounds
      long_name :
      Time axis
      standard_name :
      time
      time_origin :
      1900-01-01 00:00:00
      array([cftime.DatetimeNoLeap(2012, 1, 1, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 2, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 3, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 4, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 5, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 6, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 7, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 8, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 9, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 10, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 11, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 12, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 13, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 14, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 15, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 16, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 17, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 18, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 19, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 20, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 21, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 22, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 23, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 24, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 25, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 26, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 27, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 28, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 29, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 30, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 31, 12, 0, 0, 0, has_year_zero=True)],
            dtype=object)
    • y
      (y)
      int64
      1 2 3 4 5 ... 6537 6538 6539 6540
      array([   1,    2,    3, ..., 6538, 6539, 6540])
    • x
      (x)
      int64
      1 2 3 4 5 ... 6557 6558 6559 6560
      array([   1,    2,    3, ..., 6558, 6559, 6560])
    • z
      (z)
      int64
      1 2 3 4 5 6 ... 146 147 148 149 150
      array([  1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,  14,
              15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,  28,
              29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,  42,
              43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,  56,
              57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,  70,
              71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,  84,
              85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,  98,
              99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,
             113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126,
             127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140,
             141, 142, 143, 144, 145, 146, 147, 148, 149, 150])
    • mask2d
      (y, x)
      bool
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 40.91 MiB 83.28 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type bool numpy.ndarray
      6560 6540
    • nav_lat
      (y, x)
      float32
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 163.66 MiB 333.12 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type float32 numpy.ndarray
      6560 6540
    • nav_lon
      (y, x)
      float32
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 163.66 MiB 333.12 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type float32 numpy.ndarray
      6560 6540
    • mask
      (z, y, x)
      bool
      dask.array<chunksize=(150, 13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 5.99 GiB 12.20 MiB
      Shape (150, 6540, 6560) (150, 13, 6560)
      Count 1632 Tasks 544 Chunks
      Type bool numpy.ndarray
      6560 6540 150
    • depth
      (z, y, x)
      float32
      dask.array<chunksize=(150, 13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 23.97 GiB 48.80 MiB
      Shape (150, 6540, 6560) (150, 13, 6560)
      Count 1632 Tasks 544 Chunks
      Type float32 numpy.ndarray
      6560 6540 150
    • vosaline
      (t, z, y, x)
      float32
      dask.array<chunksize=(1, 150, 13, 6560), meta=np.ndarray>
      cell_methods :
      time: mean (interval: 40 s)
      interval_operation :
      40 s
      interval_write :
      1 d
      long_name :
      salinity
      online_operation :
      average
      standard_name :
      sea_water_practical_salinity
      units :
      1e-3
      Array Chunk
      Bytes 743.18 GiB 48.80 MiB
      Shape (31, 150, 6540, 6560) (1, 150, 13, 6560)
      Count 34272 Tasks 16864 Chunks
      Type float32 numpy.ndarray
      31 1 6560 6540 150
    • votemper
      (t, z, y, x)
      float32
      dask.array<chunksize=(1, 150, 13, 6560), meta=np.ndarray>
      cell_methods :
      time: mean (interval: 40 s)
      interval_operation :
      40 s
      interval_write :
      1 d
      long_name :
      temperature
      online_operation :
      average
      standard_name :
      sea_water_potential_temperature
      units :
      degC
      Array Chunk
      Bytes 743.18 GiB 48.80 MiB
      Shape (31, 150, 6540, 6560) (1, 150, 13, 6560)
      Count 34272 Tasks 16864 Chunks
      Type float32 numpy.ndarray
      31 1 6560 6540 150
  • 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]
    DOMAIN_number :
    0
    DOMAIN_number_total :
    544
    DOMAIN_position_first :
    [1, 1]
    DOMAIN_position_last :
    [6560, 13]
    DOMAIN_size_global :
    [6560, 6540]
    DOMAIN_size_local :
    [6560, 13]
    DOMAIN_type :
    box
    NCO :
    netCDF Operators version 4.9.1 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)
    description :
    ocean T grid variables
    history :
    Tue Jan 18 17:23:11 2022: ncks -4 -L 1 SEDNA-DELTA_1d_gridS_201201-201201_NOZIP_0000.nc /ccc/scratch/cont003/gen7420/talandel/SEDNA/SEDNA-DELTA-S/SPLIT/1d/2012/01/SEDNA-DELTA_1d_gridS_201201-201201_0000.nc Tue Jan 18 17:22:45 2022: ncrcat -n 31,2,1 SEDNA-DELTA_1d_gridS_0000_01.nc SEDNA-DELTA_1d_gridS_201201-201201_NOZIP_0000.nc
    ibegin :
    0
    jbegin :
    0
    name :
    /ccc/scratch/cont003/ra5563/talandel/ONGOING-RUNS/SEDNA-DELTA-XIOS.46/SEDNA-DELTA_1d_gridS
    ni :
    6560
    nj :
    13
    output_frequency :
    1d
    start_date :
    20090101
    timeStamp :
    2022-Jan-17 19:00:16 GMT
    title :
    ocean T grid variables
    uuid :
    d8db76f6-a436-451a-9ab1-72dc892753af
In [6]:
%%time
monitor.auto(df,data,savefig,daskreport,outputpath,file_exp='SEDNA'
            )
#calc= True
#save= True
#plot= False
Value='AW_maxtemp_depth'
Zone='ALL'
Plot='AWTD_map'
cmap='jet'
clabel='m'
clim= (0, 800)
outputpath='../results/SEDNA_DELTA_MONITOR/'
nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/'
filename='SEDNA_AWTD_map_ALL_AW_maxtemp_depth'
data=monitor.optimize_dataset(data)
#3 Start computing 
data= calc.AWTD4(data)
monitor.optimize_dataset(data)
add optimise here once otimise can recognise
<xarray.Dataset>
Dimensions:        (t: 31, y: 6540, x: 6560)
Coordinates:
    time_centered  (t) object dask.array<chunksize=(1,), meta=np.ndarray>
  * t              (t) object 2012-01-01 12:00:00 ... 2012-01-31 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
    mask2d         (y, x) bool dask.array<chunksize=(13, 6560), meta=np.ndarray>
    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>
Data variables:
    AWT            (t, y, x) float32 dask.array<chunksize=(1, 13, 6560), meta=np.ndarray>
    AWD            (t, y, x) float32 dask.array<chunksize=(1, 13, 6560), meta=np.ndarray>
xarray.Dataset
    • t: 31
    • y: 6540
    • x: 6560
    • time_centered
      (t)
      object
      dask.array<chunksize=(1,), meta=np.ndarray>
      bounds :
      time_centered_bounds
      long_name :
      Time axis
      standard_name :
      time
      time_origin :
      1900-01-01 00:00:00
      Array Chunk
      Bytes 248 B 8 B
      Shape (31,) (1,)
      Count 189 Tasks 31 Chunks
      Type object numpy.ndarray
      31 1
    • t
      (t)
      object
      2012-01-01 12:00:00 ... 2012-01-...
      array([cftime.DatetimeNoLeap(2012, 1, 1, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 2, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 3, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 4, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 5, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 6, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 7, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 8, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 9, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 10, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 11, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 12, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 13, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 14, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 15, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 16, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 17, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 18, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 19, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 20, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 21, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 22, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 23, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 24, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 25, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 26, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 27, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 28, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 29, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 30, 12, 0, 0, 0, has_year_zero=True),
             cftime.DatetimeNoLeap(2012, 1, 31, 12, 0, 0, 0, has_year_zero=True)],
            dtype=object)
    • y
      (y)
      int64
      1 2 3 4 5 ... 6537 6538 6539 6540
      array([   1,    2,    3, ..., 6538, 6539, 6540])
    • x
      (x)
      int64
      1 2 3 4 5 ... 6557 6558 6559 6560
      array([   1,    2,    3, ..., 6558, 6559, 6560])
    • mask2d
      (y, x)
      bool
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 40.91 MiB 83.28 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type bool numpy.ndarray
      6560 6540
    • nav_lat
      (y, x)
      float32
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 163.66 MiB 333.12 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type float32 numpy.ndarray
      6560 6540
    • nav_lon
      (y, x)
      float32
      dask.array<chunksize=(13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 163.66 MiB 333.12 kiB
      Shape (6540, 6560) (13, 6560)
      Count 1632 Tasks 544 Chunks
      Type float32 numpy.ndarray
      6560 6540
    • AWT
      (t, y, x)
      float32
      dask.array<chunksize=(1, 13, 6560), meta=np.ndarray>
      long_name :
      AWT
      Array Chunk
      Bytes 4.95 GiB 333.12 kiB
      Shape (31, 6540, 6560) (1, 13, 6560)
      Count 171904 Tasks 16864 Chunks
      Type float32 numpy.ndarray
      6560 6540 31
    • AWD
      (t, y, x)
      float32
      dask.array<chunksize=(1, 13, 6560), meta=np.ndarray>
      Array Chunk
      Bytes 4.95 GiB 333.12 kiB
      Shape (31, 6540, 6560) (1, 13, 6560)
      Count 342176 Tasks 16864 Chunks
      Type float32 numpy.ndarray
      6560 6540 31
#4 Saving  SEDNA_AWTD_map_ALL_AW_maxtemp_depth
data=save.datas(data,plot=Plot,path=nc_outputpath,filename=filename)
start saving data
saving data in a file
t (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
slice(0, 1, None)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
2022-08-04 11:42:09,376 - distributed.worker - ERROR - Worker stream died during communication: tcp://127.0.0.1:44081
Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/tcp.py", line 264, in write
    async def write(self, msg, serializers=None, on_error="message"):
asyncio.exceptions.CancelledError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 418, in wait_for
    return fut.result()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 329, in connect
    await asyncio.wait_for(comm.write(local_info), time_left())
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 420, in wait_for
    raise exceptions.TimeoutError() from exc
asyncio.exceptions.TimeoutError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 1983, in gather_dep
    response = await get_data_from_worker(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2725, in get_data_from_worker
    return await retry_operation(_get_data, operation="get_data_from_worker")
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 383, in retry_operation
    return await retry(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 368, in retry
    return await coro()
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2702, in _get_data
    comm = await rpc.connect(worker)
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1371, in connect
    return await connect_attempt
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1307, in _connect
    comm = await connect(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 333, in connect
    raise OSError(
OSError: Timed out during handshake while connecting to tcp://127.0.0.1:44081 after 30 s
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
2022-08-04 11:42:09,903 - distributed.worker - ERROR - Worker stream died during communication: tcp://127.0.0.1:34486
Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/tcp.py", line 264, in write
    async def write(self, msg, serializers=None, on_error="message"):
asyncio.exceptions.CancelledError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 418, in wait_for
    return fut.result()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 329, in connect
    await asyncio.wait_for(comm.write(local_info), time_left())
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 420, in wait_for
    raise exceptions.TimeoutError() from exc
asyncio.exceptions.TimeoutError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 1983, in gather_dep
    response = await get_data_from_worker(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2725, in get_data_from_worker
    return await retry_operation(_get_data, operation="get_data_from_worker")
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 383, in retry_operation
    return await retry(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 368, in retry
    return await coro()
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2702, in _get_data
    comm = await rpc.connect(worker)
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1371, in connect
    return await connect_attempt
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1307, in _connect
    comm = await connect(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 333, in connect
    raise OSError(
OSError: Timed out during handshake while connecting to tcp://127.0.0.1:34486 after 30 s
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
2022-08-04 11:42:10,145 - distributed.worker - ERROR - Worker stream died during communication: tcp://127.0.0.1:46614
Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/tcp.py", line 264, in write
    async def write(self, msg, serializers=None, on_error="message"):
asyncio.exceptions.CancelledError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 418, in wait_for
    return fut.result()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 329, in connect
    await asyncio.wait_for(comm.write(local_info), time_left())
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 420, in wait_for
    raise exceptions.TimeoutError() from exc
asyncio.exceptions.TimeoutError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 1983, in gather_dep
    response = await get_data_from_worker(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2725, in get_data_from_worker
    return await retry_operation(_get_data, operation="get_data_from_worker")
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 383, in retry_operation
    return await retry(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 368, in retry
    return await coro()
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2702, in _get_data
    comm = await rpc.connect(worker)
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1371, in connect
    return await connect_attempt
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1307, in _connect
    comm = await connect(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 333, in connect
    raise OSError(
OSError: Timed out during handshake while connecting to tcp://127.0.0.1:46614 after 30 s
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
2022-08-04 11:42:11,147 - distributed.worker - ERROR - Worker stream died during communication: tcp://127.0.0.1:44988
Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/tcp.py", line 264, in write
    async def write(self, msg, serializers=None, on_error="message"):
asyncio.exceptions.CancelledError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 418, in wait_for
    return fut.result()
asyncio.exceptions.CancelledError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 329, in connect
    await asyncio.wait_for(comm.write(local_info), time_left())
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/asyncio/tasks.py", line 420, in wait_for
    raise exceptions.TimeoutError() from exc
asyncio.exceptions.TimeoutError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 1983, in gather_dep
    response = await get_data_from_worker(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2725, in get_data_from_worker
    return await retry_operation(_get_data, operation="get_data_from_worker")
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 383, in retry_operation
    return await retry(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/utils_comm.py", line 368, in retry
    return await coro()
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/worker.py", line 2702, in _get_data
    comm = await rpc.connect(worker)
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1371, in connect
    return await connect_attempt
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/core.py", line 1307, in _connect
    comm = await connect(
  File "/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/distributed/comm/core.py", line 333, in connect
    raise OSError(
OSError: Timed out during handshake while connecting to tcp://127.0.0.1:44988 after 30 s
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
slice(1, 2, None)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
slice(2, 3, None)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
slice(3, 4, None)
slice(4, 5, None)
/ccc/cont003/home/ra5563/ra5563/monitor/lib/python3.10/site-packages/dask/array/reductions.py:608: RuntimeWarning: All-NaN slice encountered
  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)
slice(5, 6, None)
slice(6, 7, None)
slice(7, 8, None)
slice(8, 9, None)
slice(9, 10, None)
slice(10, 11, None)
slice(11, 12, None)
slice(12, 13, None)
slice(13, 14, None)
slice(14, 15, None)
2022-08-04 11:48:29,091 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(15, 16, None)
2022-08-04 11:48:40,257 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:48:43,244 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:48:54,996 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(16, 17, None)
2022-08-04 11:49:06,541 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:49:09,611 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)
2022-08-04 11:49:19,526 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(17, 18, None)
2022-08-04 11:49:32,508 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:49:35,558 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:49:44,689 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(18, 19, None)
2022-08-04 11:49:57,690 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:50:00,712 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:50:09,388 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(19, 20, None)
2022-08-04 11:50:23,256 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:50:26,454 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:50:33,984 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
slice(20, 21, None)
2022-08-04 11:50:48,929 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:50:52,022 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:50:58,923 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(21, 22, None)
2022-08-04 11:51:15,192 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:51:18,573 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:51:21,513 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
slice(22, 23, None)
2022-08-04 11:51:39,277 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:51:45,327 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:51:47,249 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
slice(23, 24, None)
2022-08-04 11:52:02,580 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:52:10,858 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:52:12,654 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:52:27,523 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(24, 25, None)
2022-08-04 11:52:35,349 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:52:38,134 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:52:52,877 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
slice(25, 26, None)
2022-08-04 11:53:02,853 - distributed.utils_perf - WARNING - full garbage collections took 12% CPU time recently (threshold: 10%)
2022-08-04 11:53:04,776 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:53:20,886 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(26, 27, None)
2022-08-04 11:53:29,235 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:53:31,936 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:53:46,630 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(27, 28, None)
2022-08-04 11:53:55,043 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:53:57,689 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:54:12,401 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(28, 29, None)
2022-08-04 11:54:20,790 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:54:23,594 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:54:40,528 - distributed.utils_perf - WARNING - full garbage collections took 10% CPU time recently (threshold: 10%)
slice(29, 30, None)
2022-08-04 11:54:48,282 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:54:51,531 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:55:04,839 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
slice(30, 31, None)
2022-08-04 11:55:13,913 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:55:16,780 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
2022-08-04 11:55:33,759 - distributed.utils_perf - WARNING - full garbage collections took 11% CPU time recently (threshold: 10%)
CPU times: user 11min 59s, sys: 2min 14s, total: 14min 13s
Wall time: 16min 59s