%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, 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

%%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= irene4197.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  irene4197.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= 02  outputpath= ../results/SEDNA_DELTA_MONITOR/ daskreport= ../results/dask/6419119irene4197.c-irene.mg1.tgcc.ccc.cea.fr_SEDNA_DELTA_MONITOR_02M_Ice_quantities/
CPU times: user 3.72 s, sys: 736 ms, total: 4.45 s
Wall time: 1min 35s

Client

Client-bc7e6e98-13da-11ed-9f06-080038b930bb

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

Cluster Info

LocalCluster

41350510

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-595fd87a-bffe-4b40-8664-700b7e6679a8

Comm: tcp://127.0.0.1:46024	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://127.0.0.1:41918	Total threads: 4
Dashboard: http://127.0.0.1:34985/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:44348
Local directory: /tmp/dask-worker-space/worker-_r76d7bs

Worker: 1

Comm: tcp://127.0.0.1:40636	Total threads: 4
Dashboard: http://127.0.0.1:32854/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35604
Local directory: /tmp/dask-worker-space/worker-1rpbwv4q

Worker: 2

Comm: tcp://127.0.0.1:39670	Total threads: 4
Dashboard: http://127.0.0.1:37025/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33118
Local directory: /tmp/dask-worker-space/worker-kihx7_ww

Worker: 3

Comm: tcp://127.0.0.1:38966	Total threads: 4
Dashboard: http://127.0.0.1:44825/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43091
Local directory: /tmp/dask-worker-space/worker-ih_rmxx2

Worker: 4

Comm: tcp://127.0.0.1:33092	Total threads: 4
Dashboard: http://127.0.0.1:38464/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42563
Local directory: /tmp/dask-worker-space/worker-w9v8uwb1

Worker: 5

Comm: tcp://127.0.0.1:39638	Total threads: 4
Dashboard: http://127.0.0.1:44014/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36487
Local directory: /tmp/dask-worker-space/worker-0gv5nxw5

Worker: 6

Comm: tcp://127.0.0.1:34090	Total threads: 4
Dashboard: http://127.0.0.1:43689/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38406
Local directory: /tmp/dask-worker-space/worker-py1vvfmh

Worker: 7

Comm: tcp://127.0.0.1:42973	Total threads: 4
Dashboard: http://127.0.0.1:44075/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42375
Local directory: /tmp/dask-worker-space/worker-l8ilrww4

Worker: 8

Comm: tcp://127.0.0.1:35384	Total threads: 4
Dashboard: http://127.0.0.1:43722/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36221
Local directory: /tmp/dask-worker-space/worker-rkpskif5

Worker: 9

Comm: tcp://127.0.0.1:37211	Total threads: 4
Dashboard: http://127.0.0.1:40147/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41664
Local directory: /tmp/dask-worker-space/worker-1pb86bai

Worker: 10

Comm: tcp://127.0.0.1:43645	Total threads: 4
Dashboard: http://127.0.0.1:42924/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36318
Local directory: /tmp/dask-worker-space/worker-a2u6ml30

Worker: 11

Comm: tcp://127.0.0.1:37557	Total threads: 4
Dashboard: http://127.0.0.1:35914/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35251
Local directory: /tmp/dask-worker-space/worker-osz9m5hz

Worker: 12

Comm: tcp://127.0.0.1:37712	Total threads: 4
Dashboard: http://127.0.0.1:39216/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33645
Local directory: /tmp/dask-worker-space/worker-mdg6_qc1

Worker: 13

Comm: tcp://127.0.0.1:39773	Total threads: 4
Dashboard: http://127.0.0.1:44716/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33561
Local directory: /tmp/dask-worker-space/worker-0yx8az4i

Worker: 14

Comm: tcp://127.0.0.1:35538	Total threads: 4
Dashboard: http://127.0.0.1:34388/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33845
Local directory: /tmp/dask-worker-space/worker-7704bph1

Worker: 15

Comm: tcp://127.0.0.1:35676	Total threads: 4
Dashboard: http://127.0.0.1:33002/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:46509
Local directory: /tmp/dask-worker-space/worker-kahhyrkr

Worker: 16

Comm: tcp://127.0.0.1:36896	Total threads: 4
Dashboard: http://127.0.0.1:35252/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41166
Local directory: /tmp/dask-worker-space/worker-f1i2stdw

Worker: 17

Comm: tcp://127.0.0.1:34256	Total threads: 4
Dashboard: http://127.0.0.1:40878/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41856
Local directory: /tmp/dask-worker-space/worker-6ayxczr1

Worker: 18

Comm: tcp://127.0.0.1:39902	Total threads: 4
Dashboard: http://127.0.0.1:34020/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:46523
Local directory: /tmp/dask-worker-space/worker-jsaoi3cq

Worker: 19

Comm: tcp://127.0.0.1:39603	Total threads: 4
Dashboard: http://127.0.0.1:36917/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40186
Local directory: /tmp/dask-worker-space/worker-bmefl3oh

Worker: 20

Comm: tcp://127.0.0.1:46873	Total threads: 4
Dashboard: http://127.0.0.1:39746/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:38337
Local directory: /tmp/dask-worker-space/worker-df7lmmkl

Worker: 21

Comm: tcp://127.0.0.1:33729	Total threads: 4
Dashboard: http://127.0.0.1:42403/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:44563
Local directory: /tmp/dask-worker-space/worker-5ds9vx3d

Worker: 22

Comm: tcp://127.0.0.1:46470	Total threads: 4
Dashboard: http://127.0.0.1:39032/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43248
Local directory: /tmp/dask-worker-space/worker-sm1hzgm3

Worker: 23

Comm: tcp://127.0.0.1:36931	Total threads: 4
Dashboard: http://127.0.0.1:39307/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41783
Local directory: /tmp/dask-worker-space/worker-ufjiym45

Worker: 24

Comm: tcp://127.0.0.1:45688	Total threads: 4
Dashboard: http://127.0.0.1:35246/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35789
Local directory: /tmp/dask-worker-space/worker-f_6ag13e

Worker: 25

Comm: tcp://127.0.0.1:36751	Total threads: 4
Dashboard: http://127.0.0.1:35467/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36600
Local directory: /tmp/dask-worker-space/worker-q1uwj3tk

Worker: 26

Comm: tcp://127.0.0.1:46660	Total threads: 4
Dashboard: http://127.0.0.1:33278/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41656
Local directory: /tmp/dask-worker-space/worker-_mh4qp9v

Worker: 27

Comm: tcp://127.0.0.1:42976	Total threads: 4
Dashboard: http://127.0.0.1:44341/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43188
Local directory: /tmp/dask-worker-space/worker-8lo0juvo

Worker: 28

Comm: tcp://127.0.0.1:46701	Total threads: 4
Dashboard: http://127.0.0.1:40583/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42091
Local directory: /tmp/dask-worker-space/worker-0tb3y1wr

Worker: 29

Comm: tcp://127.0.0.1:40873	Total threads: 4
Dashboard: http://127.0.0.1:44750/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35839
Local directory: /tmp/dask-worker-space/worker-m53wqlp8

Worker: 30

Comm: tcp://127.0.0.1:34657	Total threads: 4
Dashboard: http://127.0.0.1:45115/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33205
Local directory: /tmp/dask-worker-space/worker-u6jgxqzp

Worker: 31

Comm: tcp://127.0.0.1:33892	Total threads: 4
Dashboard: http://127.0.0.1:41828/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37545
Local directory: /tmp/dask-worker-space/worker-kr6c_gg2

Worker: 32

Comm: tcp://127.0.0.1:46334	Total threads: 4
Dashboard: http://127.0.0.1:39013/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:32963
Local directory: /tmp/dask-worker-space/worker-n5y79ni5

Worker: 33

Comm: tcp://127.0.0.1:36407	Total threads: 4
Dashboard: http://127.0.0.1:33351/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42538
Local directory: /tmp/dask-worker-space/worker-zlfcorvt

Worker: 34

Comm: tcp://127.0.0.1:38283	Total threads: 4
Dashboard: http://127.0.0.1:38789/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40840
Local directory: /tmp/dask-worker-space/worker-en8lhe4y

Worker: 35

Comm: tcp://127.0.0.1:37898	Total threads: 4
Dashboard: http://127.0.0.1:42865/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39872
Local directory: /tmp/dask-worker-space/worker-0d8b8piv

Worker: 36

Comm: tcp://127.0.0.1:45697	Total threads: 4
Dashboard: http://127.0.0.1:43255/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35170
Local directory: /tmp/dask-worker-space/worker-h2pfsu3o

Worker: 37

Comm: tcp://127.0.0.1:41342	Total threads: 4
Dashboard: http://127.0.0.1:39448/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42452
Local directory: /tmp/dask-worker-space/worker-asxj20fc

Worker: 38

Comm: tcp://127.0.0.1:32865	Total threads: 4
Dashboard: http://127.0.0.1:36408/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39077
Local directory: /tmp/dask-worker-space/worker-mjasb3iv

Worker: 39

Comm: tcp://127.0.0.1:41454	Total threads: 4
Dashboard: http://127.0.0.1:45035/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39686
Local directory: /tmp/dask-worker-space/worker-uiazyrf_

Worker: 40

Comm: tcp://127.0.0.1:42795	Total threads: 4
Dashboard: http://127.0.0.1:33853/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41644
Local directory: /tmp/dask-worker-space/worker-wheioj1f

Worker: 41

Comm: tcp://127.0.0.1:35401	Total threads: 4
Dashboard: http://127.0.0.1:33940/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:41399
Local directory: /tmp/dask-worker-space/worker-opnbajfe

Worker: 42

Comm: tcp://127.0.0.1:34390	Total threads: 4
Dashboard: http://127.0.0.1:40739/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35649
Local directory: /tmp/dask-worker-space/worker-805yw11x

Worker: 43

Comm: tcp://127.0.0.1:45869	Total threads: 4
Dashboard: http://127.0.0.1:33468/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42728
Local directory: /tmp/dask-worker-space/worker-03m5n734

Worker: 44

Comm: tcp://127.0.0.1:33674	Total threads: 4
Dashboard: http://127.0.0.1:38333/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43627
Local directory: /tmp/dask-worker-space/worker-5sgwo2rb

Worker: 45

Comm: tcp://127.0.0.1:42316	Total threads: 4
Dashboard: http://127.0.0.1:43391/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37476
Local directory: /tmp/dask-worker-space/worker-n0lhrtea

Worker: 46

Comm: tcp://127.0.0.1:34211	Total threads: 4
Dashboard: http://127.0.0.1:34703/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42942
Local directory: /tmp/dask-worker-space/worker-mpyfzqjc

Worker: 47

Comm: tcp://127.0.0.1:40671	Total threads: 4
Dashboard: http://127.0.0.1:33101/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45328
Local directory: /tmp/dask-worker-space/worker-quit5ybx

Worker: 48

Comm: tcp://127.0.0.1:46823	Total threads: 4
Dashboard: http://127.0.0.1:36740/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:35088
Local directory: /tmp/dask-worker-space/worker-bbjhwsof

Worker: 49

Comm: tcp://127.0.0.1:41930	Total threads: 4
Dashboard: http://127.0.0.1:43611/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45293
Local directory: /tmp/dask-worker-space/worker-pcwmgdtb

Worker: 50

Comm: tcp://127.0.0.1:44517	Total threads: 4
Dashboard: http://127.0.0.1:33049/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37642
Local directory: /tmp/dask-worker-space/worker-_ygt18kl

Worker: 51

Comm: tcp://127.0.0.1:37923	Total threads: 4
Dashboard: http://127.0.0.1:38253/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39595
Local directory: /tmp/dask-worker-space/worker-mjgfm50j

Worker: 52

Comm: tcp://127.0.0.1:46673	Total threads: 4
Dashboard: http://127.0.0.1:39185/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:36017
Local directory: /tmp/dask-worker-space/worker-w9g3rp_f

Worker: 53

Comm: tcp://127.0.0.1:38886	Total threads: 4
Dashboard: http://127.0.0.1:38754/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:43047
Local directory: /tmp/dask-worker-space/worker-wlvypgq1

Worker: 54

Comm: tcp://127.0.0.1:41587	Total threads: 4
Dashboard: http://127.0.0.1:35691/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45023
Local directory: /tmp/dask-worker-space/worker-et04nclm

Worker: 55

Comm: tcp://127.0.0.1:35350	Total threads: 4
Dashboard: http://127.0.0.1:35770/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39324
Local directory: /tmp/dask-worker-space/worker-_azw0x73

Worker: 56

Comm: tcp://127.0.0.1:42057	Total threads: 4
Dashboard: http://127.0.0.1:42923/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40954
Local directory: /tmp/dask-worker-space/worker-5n93ekrw

Worker: 57

Comm: tcp://127.0.0.1:40972	Total threads: 4
Dashboard: http://127.0.0.1:35372/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:42962
Local directory: /tmp/dask-worker-space/worker-i0o66db1

Worker: 58

Comm: tcp://127.0.0.1:41864	Total threads: 4
Dashboard: http://127.0.0.1:41201/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:45961
Local directory: /tmp/dask-worker-space/worker-41_2zeug

Worker: 59

Comm: tcp://127.0.0.1:35126	Total threads: 4
Dashboard: http://127.0.0.1:39287/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:40691
Local directory: /tmp/dask-worker-space/worker-xqya5kdc

Worker: 60

Comm: tcp://127.0.0.1:42977	Total threads: 4
Dashboard: http://127.0.0.1:38734/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:39346
Local directory: /tmp/dask-worker-space/worker-4b36gma8

Worker: 61

Comm: tcp://127.0.0.1:40992	Total threads: 4
Dashboard: http://127.0.0.1:35438/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:37193
Local directory: /tmp/dask-worker-space/worker-fx0lfzc9

Worker: 62

Comm: tcp://127.0.0.1:40877	Total threads: 4
Dashboard: http://127.0.0.1:42875/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:44437
Local directory: /tmp/dask-worker-space/worker-uwpnybp6

Worker: 63

Comm: tcp://127.0.0.1:43724	Total threads: 4
Dashboard: http://127.0.0.1:44439/status	Memory: 3.92 GiB
Nanny: tcp://127.0.0.1:33013
Local directory: /tmp/dask-worker-space/worker-ocpm6zgc

read plotting information from a csv file

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
	Ice_quantities	param.e1te2t,icemod.sivelo,icemod.sivolu,icemo...	calc.Ice_quant(data)	ALL	Ice_intquant	None	(0,20)	cm s^(-1)	I-2

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

%%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= False df.Inputs != nothing True lazy= True
CPU times: user 462 µs, sys: 0 ns, total: 462 µs
Wall time: 466 µs

0

%%time
monitor.auto(df,data,savefig,daskreport,outputpath,file_exp='SEDNA'
            )

#calc= False
#save= False
#plot= True
Value='Ice_quantities'
Zone='ALL'
Plot='Ice_intquant'
cmap='None'
clabel='cm s^(-1)'
clim= (0, 20)
outputpath='../results/SEDNA_DELTA_MONITOR/'
nc_outputpath='../nc_results/SEDNA_DELTA_MONITOR/'
filename='SEDNA_Ice_intquant_ALL_Ice_quantities'
#3 no computing , loading starts
data=save.load_data(plot=Plot,path=nc_outputpath,filename=filename)
start saving data
load 1Dnc file from ../nc_results/SEDNA_DELTA_MONITOR/../*/SEDNA_Ice_intquant_ALL_Ice_quantities*.nc
load computed data completed

<xarray.Dataset>
Dimensions:        (t: 90)
Coordinates:
  * t              (t) object 2012-01-01 12:00:00 ... 2012-01-31 12:00:00
    time_centered  (t) object dask.array<chunksize=(31,), meta=np.ndarray>
Data variables:
    Ice volume     (t) float64 dask.array<chunksize=(31,), meta=np.ndarray>
    Ice area       (t) float64 dask.array<chunksize=(31,), meta=np.ndarray>
    Ice extent     (t) float64 dask.array<chunksize=(31,), meta=np.ndarray>
    Ice drift      (t) float64 dask.array<chunksize=(31,), meta=np.ndarray>

xarray.Dataset

• Dimensions:
  • t: 90
• Coordinates: (2)
  • t
    (t)
    object
    2012-01-01 12:00:00 ... 2012-01-...

    axis :

    T

    standard_name :

    time

    long_name :

    Time axis

    time_origin :

    1900-01-01 00:00:00

    bounds :

    time_counter_bounds

    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),
           cftime.DatetimeNoLeap(2012, 2, 1, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 2, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 3, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 4, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 5, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 6, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 7, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 8, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 9, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 10, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 11, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 12, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 13, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 14, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 15, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 16, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 17, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 18, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 19, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 20, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 21, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 22, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 23, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 24, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 25, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 26, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 27, 12, 0, 0, 0, has_year_zero=True),
           cftime.DatetimeNoLeap(2012, 2, 28, 12, 0, 0, 0, has_year_zero=True),
           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)

  • time_centered
    (t)
    object
    dask.array<chunksize=(31,), meta=np.ndarray>

    standard_name :

    time

    long_name :

    Time axis

    time_origin :

    1900-01-01 00:00:00

    bounds :

    time_centered_bounds

    Array Chunk Bytes 720 B 248 B Shape (90,) (31,) Count 9 Tasks 3 Chunks Type object numpy.ndarray

• Data variables: (4)
  • Ice volume
    (t)
    float64
    dask.array<chunksize=(31,), meta=np.ndarray>

    Array Chunk Bytes 720 B 248 B Shape (90,) (31,) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray

  • Ice area
    (t)
    float64
    dask.array<chunksize=(31,), meta=np.ndarray>

    Array Chunk Bytes 720 B 248 B Shape (90,) (31,) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray

  • Ice extent
    (t)
    float64
    dask.array<chunksize=(31,), meta=np.ndarray>

    Array Chunk Bytes 720 B 248 B Shape (90,) (31,) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray

  • Ice drift
    (t)
    float64
    dask.array<chunksize=(31,), meta=np.ndarray>

    Array Chunk Bytes 720 B 248 B Shape (90,) (31,) Count 9 Tasks 3 Chunks Type float64 numpy.ndarray

• Attributes: (0)

#5 Plotting
filename= plots.Ice_intquant(data,path=outputpath,filename=filename,save=savefig,cmap=cmap,clim=clim,clabel=clabel)
../results/SEDNA_DELTA_MONITOR/SEDNA_Ice_intquant_ALL_Ice_quantities_20120101-20120228.html starts plotting

WARNING:param.CurvePlot02009: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend.
WARNING:param.CurvePlot02018: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend.
WARNING:param.CurvePlot02025: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend.
WARNING:param.CurvePlot02032: Converting cftime.datetime from a non-standard calendar (noleap) to a standard calendar for plotting. This may lead to subtle errors in formatting dates, for accurate tick formatting switch to the matplotlib backend.

plotting ../results/SEDNA_DELTA_MONITOR/SEDNA_Ice_intquant_ALL_Ice_quantities_20120101-20120228.html
../results/SEDNA_DELTA_MONITOR/SEDNA_Ice_intquant_ALL_Ice_quantities_20120101-20120228.html created

CPU times: user 4.83 s, sys: 2.3 s, total: 7.13 s
Wall time: 22.4 s