Show/Hide data repr

xarray.Dataset

Dimensions:
- time: 5
Coordinates: (1)
- time
  (time)
  float64
  3.677e+09 3.677e+09 ... 3.677e+09
  axis :
  T
  calendar :
  gregorian
  long_name :
  time
  standard_name :
  time
  units :
  seconds since 1900-01-01 0:0:0
```
array([3.676839e+09, 3.676839e+09, 3.676840e+09, 3.676841e+09, 3.676841e+09])
```

Data variables: (17)

battery_voltage_lithium

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Lithium Battery Voltage
precision :: 1
units :: V





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

battery_voltage_main

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Main Battery Voltage
precision :: 1
units :: V





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

deployment

(time)

int32

dask.array<chunksize=(5,), meta=np.ndarray>

long_name :: Deployment Number
name :: deployment





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  int32  numpy.ndarray

driver_timestamp

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

comment :: Driver timestamp, UTC
long_name :: Driver Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

ext_v01_current

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Current From External Voltage Sensors 0 & 1
precision :: 1
units :: mA





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

ingestion_timestamp

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

comment :: The NTP Timestamp for when the granule was ingested
long_name :: Ingestion Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

internal_timestamp

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

comment :: Internal timestamp, UTC
long_name :: Internal Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

mem_free

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Available Memory
precision :: 0
units :: bytes





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

num_events

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Events
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

num_samples

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Samples
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

operational_current

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Operational Current
precision :: 1
units :: mA





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

port_timestamp

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

comment :: Port timestamp, UTC
long_name :: Port Timestamp, UTC
units :: seconds since 1900-01-01





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

profiles

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Profiles
units :: counts





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

pump_current

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Pump Current
precision :: 1
units :: mA





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

sample_length

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Bytes Per Sample
precision :: 0
units :: bytes





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

samples_free

(time)

float64

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Number of Samples Free
precision :: 0
units :: counts





  
      Array  Chunk 
  
  
     Bytes  40 B   40 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

serial_current

(time)

float32

dask.array<chunksize=(5,), meta=np.ndarray>

coordinates :: time lat lon
long_name :: Auxiliary Serial Instrument Current
precision :: 1
units :: mA





  
      Array  Chunk 
  
  
     Bytes  20 B   20 B 
     Shape  (5,)   (5,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

Attributes: (53)
Conventions :
CF-1.6
Metadata_Conventions :
Unidata Dataset Discovery v1.0
Notes :
This netCDF product is a copy of the data on the University of Washington AWS Cloud Infrastructure.
Owner :
University of Washington Cabled Array Value Add Team.
cdm_data_type :
Point
collection_method :
streamed
comment :
Some of the metadata of this dataset has been modified to be CF-1.6 compliant.
creator_name :
Ocean Observatories Initiative
creator_url :
http://oceanobservatories.org/
date_created :
2020-08-11T10:29:39.814143
date_downloaded :
2020-09-23T15:26:37.097457
date_modified :
2020-08-11T10:29:39.814146
date_processed :
2020-09-23T15:26:51.657038
featureType :
point
geospatial_lat_max :
44.52897
geospatial_lat_min :
44.52897
geospatial_lat_resolution :
0.1
geospatial_lat_units :
degrees_north
geospatial_lon_max :
-125.38966
geospatial_lon_min :
-125.38966
geospatial_lon_resolution :
0.1
geospatial_lon_units :
degrees_east
geospatial_vertical_positive :
down
geospatial_vertical_resolution :
0.1
geospatial_vertical_units :
meters
history :
2020-08-11T10:29:39.814083 generated from Stream Engine
id :
RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_optode_status
infoUrl :
http://oceanobservatories.org/
institution :
Ocean Observatories Initiative
keywords :
keywords_vocabulary :
lat :
44.52897
license :
lon :
-125.38966
naming_authority :
org.oceanobservatories
nodc_template_version :
NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1
node :
PC01A
processing_level :
L2
project :
Ocean Observatories Initiative
publisher_email :
publisher_name :
Ocean Observatories Initiative
publisher_url :
http://oceanobservatories.org/
references :
More information can be found at http://oceanobservatories.org/
sensor :
4A-CTDPFA103
source :
RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_optode_status
sourceUrl :
http://oceanobservatories.org/
standard_name_vocabulary :
NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table 29
stream :
ctdpf_optode_status
subsite :
RS01SBPS
summary :
Dataset Generated by Stream Engine from Ocean Observatories Initiative
time_coverage_end :
2016-07-07T00:45:56.484014
time_coverage_start :
2016-07-07T00:10:42.126752
title :
Data produced by Stream Engine version 1.15.0 for RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_optode_status