diff --git a/book/chapters/data2.ipynb b/book/chapters/data2.ipynb
index 2fc6d62..92d1ead 100755
--- a/book/chapters/data2.ipynb
+++ b/book/chapters/data2.ipynb
@@ -2,29 +2,19 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 25,
"id": "8aa370ef-3ab8-4cf3-bf13-96a783e342f9",
- "metadata": {},
- "outputs": [
- {
- "ename": "ModuleNotFoundError",
- "evalue": "No module named 'netcdf4'",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnetcdf4\u001b[39;00m\n",
- "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'netcdf4'"
- ]
- }
- ],
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
"source": [
- "import netcdf4"
+ "import netCDF4"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 26,
"id": "2228ec14-bbdb-429b-b19a-49d273c67dbd",
"metadata": {
"tags": []
@@ -47,9 +37,11 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 27,
"id": "c57ef9be-6c75-4d0f-8c9a-a554283e2185",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"fs = s3fs.S3FileSystem(anon=True)"
@@ -57,12 +49,102 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 40,
"id": "61658874-bc3f-45b0-918e-4eef06312e17",
- "metadata": {},
- "outputs": [],
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Full stream name: ooi-data/CE04OSPS-SF01B-2A-CTDPFA107-streamed-ctdpf_sbe43_sample\n",
+ "\n",
+ "Field breakout: CE 04 OS PS SF 01 B 2A CTDPF A 107 ctdpf_sbe43_sample\n",
+ "\n",
+ "The first field has CE for Coastal Endurance or RS for Regional Cabled Array.\n",
+ "Fields 5, 6 and 7 give us shallow profiler site and choice of profiler or platform.\n",
+ "\n",
+ " PC 01 B --> Oregon Offshore 200m Platform\n",
+ " SF 01 B --> Oregon Offshore Profiler\n",
+ " SF 01 A --> Oregon Slope Base Profiler\n",
+ " PC 03 A --> Axial Base 200m Platform\n",
+ " SF 03 A --> Axial Base Profiler\n",
+ "\n",
+ "Non-shallow-profiler examples:\n",
+ " DP O3 A is the Axial Base Deep Profiler\n",
+ " LJ 01 A is the Oregon Slope Base Seafloor\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "streamlist = fs.listdir('ooi-data', detail = False)\n",
+ "\n",
+ "def InstrumentBreakout(s):\n",
+ " print('Field breakout:', s[9:11], s[11:13], s[13:15], s[15:17], s[18:20], s[20:22], s[22:23], s[24:26], \\\n",
+ " s[27:32], s[32:33], s[33:36], s[46:])\n",
+ "\n",
+ "stream_choice = 15\n",
+ "print()\n",
+ "print('Full stream name:', streamlist[stream_choice])\n",
+ "print()\n",
+ "InstrumentBreakout(streamlist[stream_choice])\n",
+ "print()\n",
+ "print('The first field has CE for Coastal Endurance or RS for Regional Cabled Array.')\n",
+ "print('Fields 5, 6 and 7 give us shallow profiler site and choice of profiler or platform.')\n",
+ "print()\n",
+ "indenter = 4\n",
+ "print(' '*indenter + 'PC 01 B --> Oregon Offshore 200m Platform')\n",
+ "print(' '*indenter + 'SF 01 B --> Oregon Offshore Profiler')\n",
+ "print(' '*indenter + 'SF 01 A --> Oregon Slope Base Profiler')\n",
+ "print(' '*indenter + 'PC 03 A --> Axial Base 200m Platform')\n",
+ "print(' '*indenter + 'SF 03 A --> Axial Base Profiler')\n",
+ "print()\n",
+ "print('Non-shallow-profiler examples:')\n",
+ "print(' DP O3 A is the Axial Base Deep Profiler')\n",
+ "print(' LJ 01 A is the Oregon Slope Base Seafloor')\n",
+ "print()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "id": "e2f40d77-b640-4f7b-9d7b-48ea8c977ad1",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ooi-data/RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample\n",
+ "ooi-data/RS01SBPS-SF01A-2D-PHSENA101-streamed-phsen_data_record\n",
+ "ooi-data/RS01SBPS-SF01A-3A-FLORTD101-streamed-flort_d_data_record\n",
+ "ooi-data/RS01SBPS-SF01A-3B-OPTAAD101-streamed-optaa_sample\n",
+ "ooi-data/RS01SBPS-SF01A-3C-PARADA101-streamed-parad_sa_sample\n",
+ "ooi-data/RS01SBPS-SF01A-3D-SPKIRA101-streamed-spkir_data_record\n",
+ "ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_dark_sample\n",
+ "ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_sample\n",
+ "ooi-data/RS01SBPS-SF01A-4B-VELPTD102-streamed-velpt_velocity_data\n",
+ "ooi-data/RS01SBPS-SF01A-4F-PCO2WA101-streamed-pco2w_a_sami_data_record\n",
+ "\n",
+ "ooi-data/RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample\n",
+ "\n"
+ ]
+ }
+ ],
"source": [
- "fs.listdir('ooi-data', detail = False)"
+ "osb_profiler_streams = [sname for sname in streamlist if 'SF01A' in sname]\n",
+ "for s in osb_profiler_streams: \n",
+ " print(s)\n",
+ " if 'ctdpf' in s: osb_sp_ctd = s\n",
+ "print()\n",
+ "print(osb_sp_ctd)\n",
+ "print()"
]
},
{
@@ -77,112 +159,3553 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 48,
"id": "a56bc2c6-e16d-49ee-b3cc-8166935f0c42",
"metadata": {
"tags": []
},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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+ "
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+ "Dimensions: (time: 220548447)\n",
+ "Coordinates:\n",
+ " * time (time) datetime64[ns] ...\n",
+ "Data variables: (12/39)\n",
+ " conductivity (time) float64 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ " corrected_dissolved_oxygen (time) float64 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ " corrected_dissolved_oxygen_qartod_executed (time) <U2 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ " corrected_dissolved_oxygen_qartod_results (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " corrected_dissolved_oxygen_qc_executed (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " corrected_dissolved_oxygen_qc_results (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " ... ...\n",
+ " sea_water_temperature (time) float64 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ " sea_water_temperature_qartod_executed (time) <U2 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ " sea_water_temperature_qartod_results (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " sea_water_temperature_qc_executed (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " sea_water_temperature_qc_results (time) uint8 dask.array<chunksize=(100000000,), meta=np.ndarray>\n",
+ " temperature (time) float64 dask.array<chunksize=(12000000,), meta=np.ndarray>\n",
+ "Attributes: (12/62)\n",
+ " AssetManagementRecordLastModified: 2024-06-27T13:16:21.544000\n",
+ " AssetUniqueID: ATAPL-66662-00008\n",
+ " Conventions: CF-1.6\n",
+ " Description: CTD Profiler: CTDPF Series A\n",
+ " FirmwareVersion: Not specified.\n",
+ " Manufacturer: Sea-Bird Electronics\n",
+ " ... ...\n",
+ " stream: ctdpf_sbe43_sample\n",
+ " subsite: RS01SBPS\n",
+ " summary: Dataset Generated by Stream Engine fr...\n",
+ " time_coverage_end: 2024-06-28T11:13:24.862212608\n",
+ " time_coverage_start: 2014-10-06T22:05:23.269171200\n",
+ " title: Data produced by Stream Engine versio... Dimensions:
Coordinates: (1)
Data variables: (39)
conductivity
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Unprocessed conductivity data that are output directly from the sensor. Seawater conductivity refers to the ability of seawater to conduct electricity. The presence of ions in the seawater, such as salt, increases the electrical conducting ability of seawater. As such, conductivity can be used as a proxy for determining the quantity of salt in a sample of seawater. coordinates : lat depth lon time data_product_identifier : CONDWAT_L0 long_name : Unprocessed (L0) Seawater Conductivity precision : 0 units : counts \n",
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corrected_dissolved_oxygen
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
ancillary_variables : corrected_dissolved_oxygen_qartod_results corrected_dissolved_oxygen_qartod_executed corrected_dissolved_oxygen comment : Dissolved Oxygen (DO) Concentration from the Fast Response (Fastrep) DO Instrument is a measure of the concentration of gaseous oxygen mixed in seawater. This Instrument measures dissolved oxygen concentrations on shallow coastal profilers through rapid oxygen gradients. This data product is corrected for salinity, temperature, and depth from a collocated CTD. coordinates : lat depth lon time long_name : Dissolved Oxygen - Pressure Temp Sal Corrected (CTD) precision : 4 units : umol kg-1 \n",
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corrected_dissolved_oxygen_qartod_executed
(time)
<U2
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : lat depth lon time long_name : Dissolved Oxygen - Pressure Temp Sal Corrected (CTD) Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : corrected_dissolved_oxygen status_flag tests_executed : gross_range_test, climatology_test \n",
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corrected_dissolved_oxygen_qartod_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : lat depth lon time flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Dissolved Oxygen - Pressure Temp Sal Corrected (CTD) QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : corrected_dissolved_oxygen status_flag \n",
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corrected_dissolved_oxygen_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
coordinates : lat depth lon time long_name : QC Checks Executed \n",
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corrected_dissolved_oxygen_qc_results
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dask.array<chunksize=(100000000,), meta=np.ndarray>
coordinates : lat depth lon time long_name : QC Checks Results \n",
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deployment
(time)
int32
dask.array<chunksize=(25000000,), meta=np.ndarray>
coordinates : lat depth lon time long_name : Deployment Number name : deployment \n",
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do_fast_sample-corrected_dissolved_oxygen
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Dissolved Oxygen (DO) Concentration from the Fast Response (Fastrep) DO Instrument is a measure of the concentration of gaseous oxygen mixed in seawater. This Instrument measures dissolved oxygen concentrations on shallow coastal profilers through rapid oxygen gradients. This data product is corrected for salinity, temperature, and depth from a collocated CTD. coordinates : lat depth lon time data_product_identifier : DOCONCF_L2 instrument : RS01SBPS-SF01A-2A-DOFSTA102 long_name : Dissolved Oxygen - Pressure Temp Sal Corrected (CTD) precision : 4 standard_name : moles_of_oxygen_per_unit_mass_in_sea_water stream : do_fast_sample units : umol kg-1 \n",
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+ " 91.55 MiB \n",
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+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
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+ " 19 chunks in 2 graph layers \n",
+ " \n",
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+ " Data type \n",
+ " float64 numpy.ndarray \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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+ " \n",
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driver_timestamp
(time)
datetime64[ns]
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Driver timestamp, UTC coordinates : lat depth lon time long_name : Driver Timestamp, UTC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " datetime64[ns] numpy.ndarray \n",
+ " \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
ext_volt0
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : SBE43 voltage reading coordinates : lat depth lon time long_name : External Voltage Reading From Oxygen Sensor units : counts \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
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+ "
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
ingestion_timestamp
(time)
datetime64[ns]
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : The NTP Timestamp for when the granule was ingested coordinates : lat depth lon time long_name : Ingestion Timestamp, UTC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " datetime64[ns] numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
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+ " \n",
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+ " \n",
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+ " \n",
+ " \n",
+ " \n",
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+ " \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
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+ "\n",
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+ " \n",
+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
internal_timestamp
(time)
datetime64[ns]
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Internal timestamp, UTC coordinates : lat depth lon time long_name : Internal Timestamp, UTC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " datetime64[ns] numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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+ " \n",
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port_timestamp
(time)
datetime64[ns]
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Port timestamp, UTC coordinates : lat depth lon time long_name : Port Timestamp, UTC \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " datetime64[ns] numpy.ndarray \n",
+ " \n",
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+ "
\n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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pressure
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Unprocessed pressure data that are output directly from the sensor. Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. coordinates : lat depth lon time data_product_identifier : PRESWAT_L0 long_name : Unprocessed (L0) Seawater Pressure precision : 0 units : counts \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
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+ "
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
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pressure_temp
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Unprocessed temperature from the pressure sensor (inside the housing, but isolated from housing and the electronics) used to calculate CTD output parameters. coordinates : lat depth lon time long_name : Internal Pressure Sensor Temperature precision : 0 units : counts \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
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+ "
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+ " 220548447 \n",
+ " 1 \n",
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sea_water_density
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : density ancillary_variables : sea_water_pressure sea_water_practical_salinity sea_water_temperature comment : Seawater Density is defined as mass per unit volume and is calculated from the conductivity, temperature and depth of a seawater sample using the TEOS-10 equation. coordinates : lat depth lon time data_product_identifier : DENSITY_L2 long_name : Seawater Density precision : 3 standard_name : sea_water_density units : kg m-3 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
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+ "
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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+ " \n",
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sea_water_density_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : density_qc_executed coordinates : lat depth lon time long_name : QC Checks Executed \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (100000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 3 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " uint8 numpy.ndarray \n",
+ " \n",
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+ "
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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+ "
sea_water_density_qc_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : density_qc_results coordinates : lat depth lon time long_name : QC Checks Results \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (100000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 3 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " uint8 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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+ " \n",
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sea_water_electrical_conductivity
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : seawater_conductivity ancillary_variables : seawater_conductivity_qartod_results seawater_conductivity_qartod_executed sea_water_pressure sea_water_temperature conductivity comment : Seawater conductivity refers to the ability of seawater to conduct electricity. The presence of ions in the seawater, such as salt, increases the electrical conducting ability of seawater. As such, conductivity can be used as a proxy for determining the quantity of salt in a sample of seawater. coordinates : lat depth lon time data_product_identifier : CONDWAT_L1 long_name : Seawater Conductivity precision : 6 standard_name : sea_water_electrical_conductivity units : S m-1 \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " float64 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
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+ " \n",
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+ "\n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
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sea_water_electrical_conductivity_qartod_executed
(time)
<U1
dask.array<chunksize=(25000000,), meta=np.ndarray>
alternate_parameter_name : seawater_conductivity_qartod_executed comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : lat depth lon time long_name : Seawater Conductivity Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_electrical_conductivity status_flag tests_executed : gross_range_test \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 841.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (25000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 9 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
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+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
sea_water_electrical_conductivity_qartod_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_conductivity_qartod_results comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : lat depth lon time flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Conductivity QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_electrical_conductivity status_flag \n",
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+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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sea_water_electrical_conductivity_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_conductivity_qc_executed coordinates : lat depth lon time long_name : QC Checks Executed \n",
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+ " \n",
+ " \n",
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+ " \n",
+ " \n",
+ " \n",
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+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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sea_water_electrical_conductivity_qc_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_conductivity_qc_results coordinates : lat depth lon time long_name : QC Checks Results \n",
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+ " \n",
+ " \n",
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+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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sea_water_practical_salinity
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : practical_salinity ancillary_variables : practical_salinity_qartod_results practical_salinity_qartod_executed sea_water_pressure sea_water_electrical_conductivity sea_water_temperature comment : Salinity is generally defined as the concentration of dissolved salt in a parcel of seawater. Practical Salinity is a more specific unitless quantity calculated from the conductivity of seawater and adjusted for temperature and pressure. It is approximately equivalent to Absolute Salinity (the mass fraction of dissolved salt in seawater) but they are not interchangeable. coordinates : lat depth lon time data_product_identifier : PRACSAL_L2 long_name : Practical Salinity precision : 4 standard_name : sea_water_practical_salinity units : 1 \n",
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+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
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+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
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+ " 19 chunks in 2 graph layers \n",
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+ " float64 numpy.ndarray \n",
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+ " 220548447 \n",
+ " 1 \n",
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sea_water_practical_salinity_qartod_executed
(time)
<U2
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : practical_salinity_qartod_executed comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : lat depth lon time long_name : Practical Salinity Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_practical_salinity status_flag tests_executed : gross_range_test, climatology_test \n",
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+ " \n",
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+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
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+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
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+ " 19 chunks in 2 graph layers \n",
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+ " 1 \n",
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sea_water_practical_salinity_qartod_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : practical_salinity_qartod_results comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : lat depth lon time flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Practical Salinity QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_practical_salinity status_flag \n",
+ " \n",
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+ " \n",
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+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
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+ " 3 chunks in 2 graph layers \n",
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+ " Data type \n",
+ " uint8 numpy.ndarray \n",
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+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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sea_water_practical_salinity_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : practical_salinity_qc_executed coordinates : lat depth lon time long_name : QC Checks Executed \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
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+ " \n",
+ " \n",
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+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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+ " 220548447 \n",
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sea_water_practical_salinity_qc_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : practical_salinity_qc_results coordinates : lat depth lon time long_name : QC Checks Results \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
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+ " \n",
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+ " 3 chunks in 2 graph layers \n",
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+ " Data type \n",
+ " uint8 numpy.ndarray \n",
+ " \n",
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+ "
\n",
+ " \n",
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+ " \n",
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sea_water_pressure
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : seawater_pressure ancillary_variables : seawater_pressure_qartod_results seawater_pressure_qartod_executed pressure pressure_temp comment : Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. coordinates : lat depth lon time data_product_identifier : PRESWAT_L1 long_name : Seawater Pressure precision : 3 standard_name : sea_water_pressure units : dbar \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (12000000,) \n",
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+ " Dask graph \n",
+ " 19 chunks in 2 graph layers \n",
+ " \n",
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+ " Data type \n",
+ " float64 numpy.ndarray \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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sea_water_pressure_qartod_executed
(time)
<U1
dask.array<chunksize=(25000000,), meta=np.ndarray>
alternate_parameter_name : seawater_pressure_qartod_executed comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : lat depth lon time long_name : Seawater Pressure Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_pressure status_flag tests_executed : gross_range_test \n",
+ " \n",
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+ " \n",
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+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 841.33 MiB \n",
+ " 95.37 MiB \n",
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+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (25000000,) \n",
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+ " Dask graph \n",
+ " 9 chunks in 2 graph layers \n",
+ " \n",
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+ " Data type \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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sea_water_pressure_qartod_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_pressure_qartod_results comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : lat depth lon time flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Pressure QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_pressure status_flag \n",
+ " \n",
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+ " \n",
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+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (100000000,) \n",
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+ " 3 chunks in 2 graph layers \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
+ " \n",
+ "
sea_water_pressure_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_pressure_qc_executed coordinates : lat depth lon time long_name : QC Checks Executed \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
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+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (100000000,) \n",
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+ " 3 chunks in 2 graph layers \n",
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+ " Data type \n",
+ " uint8 numpy.ndarray \n",
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+ " \n",
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+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
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sea_water_pressure_qc_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_pressure_qc_results coordinates : lat depth lon time long_name : QC Checks Results \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
+ " \n",
+ " \n",
+ " \n",
+ " Shape \n",
+ " (220548447,) \n",
+ " (100000000,) \n",
+ " \n",
+ " \n",
+ " Dask graph \n",
+ " 3 chunks in 2 graph layers \n",
+ " \n",
+ " \n",
+ " Data type \n",
+ " uint8 numpy.ndarray \n",
+ " \n",
+ " \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ " 220548447 \n",
+ " 1 \n",
+ " \n",
+ " \n",
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+ "
sea_water_temperature
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : seawater_temperature ancillary_variables : seawater_temperature_qartod_results seawater_temperature_qartod_executed temperature comment : Seawater temperature near the sensor. coordinates : lat depth lon time data_product_identifier : TEMPWAT_L1 long_name : Seawater Temperature precision : 4 standard_name : sea_water_temperature units : degrees_Celsius \n",
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+ " 1.64 GiB \n",
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+ " (220548447,) \n",
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sea_water_temperature_qartod_executed
(time)
<U2
dask.array<chunksize=(12000000,), meta=np.ndarray>
alternate_parameter_name : seawater_temperature_qartod_executed comment : Individual QARTOD test flags. For each datum, flags are listed in a string matching the order of the tests_executed attribute. Flags should be interpreted using the standard QARTOD mapping: [1: pass, 2: not_evaluated, 3: suspect_or_of_high_interest, 4: fail, 9: missing_data]. coordinates : lat depth lon time long_name : Seawater Temperature Individual QARTOD Flags references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_temperature status_flag tests_executed : gross_range_test, climatology_test \n",
+ " \n",
+ " \n",
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+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Bytes \n",
+ " 1.64 GiB \n",
+ " 91.55 MiB \n",
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sea_water_temperature_qartod_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_temperature_qartod_results comment : Summary QARTOD test flags. For each datum, the flag is set to the most significant result of all QARTOD tests run for that datum. coordinates : lat depth lon time flag_meanings : pass not_evaluated suspect_or_of_high_interest fail missing_data flag_values : 1,2,3,4,9 long_name : Seawater Temperature QARTOD Summary Flag references : https://ioos.noaa.gov/project/qartod https://github.com/ioos/ioos_qc standard_name : sea_water_temperature status_flag \n",
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+ " Chunk \n",
+ " \n",
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+ " Bytes \n",
+ " 210.33 MiB \n",
+ " 95.37 MiB \n",
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+ " (220548447,) \n",
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sea_water_temperature_qc_executed
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_temperature_qc_executed coordinates : lat depth lon time long_name : QC Checks Executed \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
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+ " Chunk \n",
+ " \n",
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sea_water_temperature_qc_results
(time)
uint8
dask.array<chunksize=(100000000,), meta=np.ndarray>
alternate_parameter_name : seawater_temperature_qc_results coordinates : lat depth lon time long_name : QC Checks Results \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " Array \n",
+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
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+ " 210.33 MiB \n",
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temperature
(time)
float64
dask.array<chunksize=(12000000,), meta=np.ndarray>
comment : Unprocessed seawater temperature measurement in counts. coordinates : lat depth lon time data_product_identifier : TEMPWAT_L0 long_name : Unprocessed (L0) Seawater Temperature precision : 0 units : counts \n",
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+ " Chunk \n",
+ " \n",
+ " \n",
+ " \n",
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+ " 1.64 GiB \n",
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Indexes: (1)
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+ " dtype='datetime64[ns]', name='time', length=220548447, freq=None)) Attributes: (62)
AssetManagementRecordLastModified : 2024-06-27T13:16:21.544000 AssetUniqueID : ATAPL-66662-00008 Conventions : CF-1.6 Description : CTD Profiler: CTDPF Series A FirmwareVersion : Not specified. Manufacturer : Sea-Bird Electronics Metadata_Conventions : Unidata Dataset Discovery v1.0 Mobile : False ModelNumber : SBE 16plus V2 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. RemoteResources : [] SerialNumber : 16-50115 ShelfLifeExpirationDate : Not specified. SoftwareVersion : Not specified. 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 : 2024-06-28T11:13:52.756554 date_downloaded : 2024-06-28T11:13:28.350669 date_modified : 2024-06-28T11:13:52.756556 date_processed : 2024-06-28T11:18:35.798576 featureType : point geospatial_lat_max : 44.515161 geospatial_lat_min : 44.515161 geospatial_lat_resolution : 0.1 geospatial_lat_units : degrees_north geospatial_lon_max : -125.389899 geospatial_lon_min : -125.389899 geospatial_lon_resolution : 0.1 geospatial_lon_units : degrees_east geospatial_vertical_positive : down geospatial_vertical_resolution : 0.1 geospatial_vertical_units : meters history : 2024-06-28T11:13:52.756522 generated from Stream Engine id : RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample infoUrl : http://oceanobservatories.org/ institution : Ocean Observatories Initiative keywords : keywords_vocabulary : license : naming_authority : org.oceanobservatories nodc_template_version : NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1 node : SF01A 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 : 2A-CTDPFA102 source : RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample sourceUrl : http://oceanobservatories.org/ standard_name_vocabulary : NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table 29 stream : ctdpf_sbe43_sample subsite : RS01SBPS summary : Dataset Generated by Stream Engine from Ocean Observatories Initiative time_coverage_end : 2024-06-28T11:13:24.862212608 time_coverage_start : 2014-10-06T22:05:23.269171200 title : Data produced by Stream Engine version 1.20.8 for RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample "
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+ "text/plain": [
+ "\n",
+ "Dimensions: (time: 220548447)\n",
+ "Coordinates:\n",
+ " * time (time) datetime64[ns] ...\n",
+ "Data variables: (12/39)\n",
+ " conductivity (time) float64 dask.array\n",
+ " corrected_dissolved_oxygen (time) float64 dask.array\n",
+ " corrected_dissolved_oxygen_qartod_executed (time) \n",
+ " corrected_dissolved_oxygen_qartod_results (time) uint8 dask.array\n",
+ " corrected_dissolved_oxygen_qc_executed (time) uint8 dask.array\n",
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+ " sea_water_temperature (time) float64 dask.array\n",
+ " sea_water_temperature_qartod_executed (time) \n",
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+ "Attributes: (12/62)\n",
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+ " AssetUniqueID: ATAPL-66662-00008\n",
+ " Conventions: CF-1.6\n",
+ " Description: CTD Profiler: CTDPF Series A\n",
+ " FirmwareVersion: Not specified.\n",
+ " Manufacturer: Sea-Bird Electronics\n",
+ " ... ...\n",
+ " stream: ctdpf_sbe43_sample\n",
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+ " time_coverage_end: 2024-06-28T11:13:24.862212608\n",
+ " time_coverage_start: 2014-10-06T22:05:23.269171200\n",
+ " title: Data produced by Stream Engine versio..."
+ ]
+ },
+ "execution_count": 48,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "siteData = loadData(zarrFile)\n",
+ "siteData = loadData(osb_sp_ctd)\n",
"siteData"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 49,
"id": "6d82a0a7-c1a0-48dc-ae14-f32a41356e99",
- "metadata": {},
- "outputs": [],
+ "metadata": {
+ "tags": []
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+ "execution_count": 52,
+ "id": "63311817-6642-4b2e-bd19-d22074072a99",
+ "metadata": {
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+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(\n",
+ " array('2022-01-01T00:00:00.097717760', dtype='datetime64[ns]')\n",
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+ " time datetime64[ns] 2022-01-01T00:00:00.097717760\n",
+ " Attributes:\n",
+ " axis: T\n",
+ " long_name: time\n",
+ " standard_name: time,\n",
+ " \n",
+ " array('2022-01-31T23:59:59.066327552', dtype='datetime64[ns]')\n",
+ " Coordinates:\n",
+ " time datetime64[ns] 2022-01-31T23:59:59.066327552\n",
+ " Attributes:\n",
+ " axis: T\n",
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+ " standard_name: time)"
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+ "execution_count": 52,
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+ "source": [
+ "t0, t1 = '2022-01-01T00', '2022-01-31T23'\n",
+ "ds = siteData.sel(time=slice(t0, t1))\n",
+ "ds.time[0], ds.time[-1]"
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{
"cell_type": "markdown",
"id": "6b15a656-09fa-4a70-b3d6-434ecd8e1fc3",
"metadata": {},
"source": [
"```\n",
- "['ooi-data/CE02SHBP-LJ01D-05-ADCPTB104-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/CE02SHBP-LJ01D-06-CTDBPN106-streamed-ctdbp_no_sample',\r\n",
- " 'ooi-data/CE02SHBP-LJ01D-07-VEL3DC108-streamed-vel3d_cd_velocity_data',\r\n",
- " 'ooi-data/CE02SHBP-LJ01D-09-PCO2WB103-streamed-pco2w_b_sami_data_record',\r\n",
- " 'ooi-data/CE02SHBP-LJ01D-10-PHSEND103-streamed-phsen_data_record',\r\n",
- " 'ooi-data/CE04OSBP-LJ01C-05-ADCPSI103-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/CE04OSBP-LJ01C-06-CTDBPO108-streamed-ctdbp_no_sample',\r\n",
- " 'ooi-data/CE04OSBP-LJ01C-07-VEL3DC107-streamed-vel3d_cd_velocity_data',\r\n",
- " 'ooi-data/CE04OSBP-LJ01C-09-PCO2WB104-streamed-pco2w_b_sami_data_record',\r\n",
- " 'ooi-data/CE04OSBP-LJ01C-10-PHSEND107-streamed-phsen_data_record',\r\n",
- " 'ooi-data/CE04OSPS-PC01B-4A-CTDPFA109-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/CE04OSPS-PC01B-4A-CTDPFA109-streamed-ctdpf_sbe43_sample',\r\n",
- " 'ooi-data/CE04OSPS-PC01B-4B-PHSENA106-streamed-phsen_data_record',\r\n",
- " 'ooi-data/CE04OSPS-PC01B-4D-PCO2WA105-streamed-pco2w_a_sami_data_record',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-2A-CTDPFA107-streamed-ctdpf_sbe43_sample',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-2B-PHSENA108-streamed-phsen_data_record',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-3A-FLORTD104-streamed-flort_d_data_record',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-3C-PARADA102-streamed-parad_sa_sample',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-3D-SPKIRA102-streamed-spkir_data_record',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-4A-NUTNRA102-streamed-nutnr_a_dark_sample',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-4A-NUTNRA102-streamed-nutnr_a_sample',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-4B-VELPTD106-streamed-velpt_velocity_data',\r\n",
- " 'ooi-data/CE04OSPS-SF01B-4F-PCO2WA102-streamed-pco2w_a_sami_data_record',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-05-ADCPTD102-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-06-VADCPA101-streamed-vadcp_velocity_beam',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-06-VADCPA101-streamed-vadcp_velocity_beam_5',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_sbe43_sample',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-4B-PHSENA102-streamed-phsen_data_record',\r\n",
- " 'ooi-data/RS01SBPS-PC01A-4C-FLORDD103-streamed-flort_d_data_record',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-2D-PHSENA101-streamed-phsen_data_record',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-3A-FLORTD101-streamed-flort_d_data_record',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-3C-PARADA101-streamed-parad_sa_sample',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-3D-SPKIRA101-streamed-spkir_data_record',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_dark_sample',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_sample',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-4B-VELPTD102-streamed-velpt_velocity_data',\r\n",
- " 'ooi-data/RS01SBPS-SF01A-4F-PCO2WA101-streamed-pco2w_a_sami_data_record',\r\n",
- " 'ooi-data/RS01SLBS-LJ01A-05-HPIESA101-streamed-echo_sounding',\r\n",
- " 'ooi-data/RS01SLBS-LJ01A-10-ADCPTE101-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/RS01SLBS-LJ01A-12-CTDPFB101-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS01SLBS-MJ01A-06-PRESTA101-streamed-prest_real_time',\r\n",
- " 'ooi-data/RS01SLBS-MJ01A-12-VEL3DB101-streamed-vel3d_b_sample',\r\n",
- " 'ooi-data/RS01SUM1-LJ01B-12-VEL3DB104-streamed-vel3d_b_sample',\r\n",
- " 'ooi-data/RS01SUM2-MJ01B-12-ADCPSK101-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/RS03ASHS-MJ03B-07-TMPSFA301-streamed-tmpsf_sample',\r\n",
- " 'ooi-data/RS03ASHS-MJ03B-09-BOTPTA304-streamed-botpt_nano_sample_15s',\r\n",
- " 'ooi-data/RS03ASHS-MJ03B-10-CTDPFB304-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS03AXBS-LJ03A-05-HPIESA301-streamed-echo_sounding',\r\n",
- " 'ooi-data/RS03AXBS-LJ03A-10-ADCPTE303-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/RS03AXBS-LJ03A-11-OPTAAC303-streamed-optaa_sample',\r\n",
- " 'ooi-data/RS03AXBS-LJ03A-12-CTDPFB301-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS03AXBS-MJ03A-06-PRESTA301-streamed-prest_real_time',\r\n",
- " 'ooi-data/RS03AXBS-MJ03A-12-VEL3DB301-streamed-vel3d_b_sample',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-05-ADCPTD302-streamed-adcp_velocity_beam',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-06-VADCPA301-streamed-vadcp_velocity_beam',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-06-VADCPA301-streamed-vadcp_velocity_beam_5',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-4A-CTDPFA303-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-4B-PHSENA302-streamed-phsen_data_record',\r\n",
- " 'ooi-data/RS03AXPS-PC03A-4C-FLORDD303-streamed-flort_d_data_record',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-2A-CTDPFA302-streamed-ctdpf_sbe43_sample',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-2D-PHSENA301-streamed-phsen_data_record',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-3A-FLORTD301-streamed-flort_d_data_record',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-3B-OPTAAD301-streamed-optaa_sample',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-3C-PARADA301-streamed-parad_sa_sample',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-3D-SPKIRA301-streamed-spkir_data_record',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-4A-NUTNRA301-streamed-nutnr_a_dark_sample',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-4A-NUTNRA301-streamed-nutnr_a_sample',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-4B-VELPTD302-streamed-velpt_velocity_data',\r\n",
- " 'ooi-data/RS03AXPS-SF03A-4F-PCO2WA301-streamed-pco2w_a_sami_data_record',\r\n",
- " 'ooi-data/RS03CCAL-MJ03F-12-CTDPFB305-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS03ECAL-MJ03E-12-CTDPFB306-streamed-ctdpf_optode_sample',\r\n",
- " 'ooi-data/RS03INT1-MJ03C-07-D1000A301-streamed-d1000_sample',\r\n",
- " 'ooi-data/RS03INT1-MJ03C-09-TRHPHA302-streamed-trhph_sample',\r\n",
- " 'ooi-data/RS03INT1-MJ03C-10-TRHPHA301-streamed-trhph_sample',\r\n",
- " 'ooi-data/RS03INT2-MJ03D-12-VEL3DB304-streamed-vel3d_b_sample',\r\n",
- " 'ooi-data/annotations',\r\n",
- " 'ooi-data/index.json',\r\n",
+ "['ooi-data/CE02SHBP-LJ01D-05-ADCPTB104-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/CE02SHBP-LJ01D-06-CTDBPN106-streamed-ctdbp_no_sample',\n",
+ " 'ooi-data/CE02SHBP-LJ01D-07-VEL3DC108-streamed-vel3d_cd_velocity_data',\n",
+ " 'ooi-data/CE02SHBP-LJ01D-09-PCO2WB103-streamed-pco2w_b_sami_data_record',\n",
+ " 'ooi-data/CE02SHBP-LJ01D-10-PHSEND103-streamed-phsen_data_record',\n",
+ " 'ooi-data/CE04OSBP-LJ01C-05-ADCPSI103-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/CE04OSBP-LJ01C-06-CTDBPO108-streamed-ctdbp_no_sample',\n",
+ " 'ooi-data/CE04OSBP-LJ01C-07-VEL3DC107-streamed-vel3d_cd_velocity_data',\n",
+ " 'ooi-data/CE04OSBP-LJ01C-09-PCO2WB104-streamed-pco2w_b_sami_data_record',\n",
+ " 'ooi-data/CE04OSBP-LJ01C-10-PHSEND107-streamed-phsen_data_record',\n",
+ " 'ooi-data/CE04OSPS-PC01B-4A-CTDPFA109-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/CE04OSPS-PC01B-4A-CTDPFA109-streamed-ctdpf_sbe43_sample',\n",
+ " 'ooi-data/CE04OSPS-PC01B-4B-PHSENA106-streamed-phsen_data_record',\n",
+ " 'ooi-data/CE04OSPS-PC01B-4D-PCO2WA105-streamed-pco2w_a_sami_data_record',\n",
+ " 'ooi-data/CE04OSPS-SF01B-2A-CTDPFA107-streamed-ctdpf_sbe43_sample',\n",
+ " 'ooi-data/CE04OSPS-SF01B-2B-PHSENA108-streamed-phsen_data_record',\n",
+ " 'ooi-data/CE04OSPS-SF01B-3A-FLORTD104-streamed-flort_d_data_record',\n",
+ " 'ooi-data/CE04OSPS-SF01B-3C-PARADA102-streamed-parad_sa_sample',\n",
+ " 'ooi-data/CE04OSPS-SF01B-3D-SPKIRA102-streamed-spkir_data_record',\n",
+ " 'ooi-data/CE04OSPS-SF01B-4A-NUTNRA102-streamed-nutnr_a_dark_sample',\n",
+ " 'ooi-data/CE04OSPS-SF01B-4A-NUTNRA102-streamed-nutnr_a_sample',\n",
+ " 'ooi-data/CE04OSPS-SF01B-4B-VELPTD106-streamed-velpt_velocity_data',\n",
+ " 'ooi-data/CE04OSPS-SF01B-4F-PCO2WA102-streamed-pco2w_a_sami_data_record',\n",
+ " 'ooi-data/RS01SBPS-PC01A-05-ADCPTD102-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/RS01SBPS-PC01A-06-VADCPA101-streamed-vadcp_velocity_beam',\n",
+ " 'ooi-data/RS01SBPS-PC01A-06-VADCPA101-streamed-vadcp_velocity_beam_5',\n",
+ " 'ooi-data/RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS01SBPS-PC01A-4A-CTDPFA103-streamed-ctdpf_sbe43_sample',\n",
+ " 'ooi-data/RS01SBPS-PC01A-4B-PHSENA102-streamed-phsen_data_record',\n",
+ " 'ooi-data/RS01SBPS-PC01A-4C-FLORDD103-streamed-flort_d_data_record',\n",
+ " 'ooi-data/RS01SBPS-SF01A-2A-CTDPFA102-streamed-ctdpf_sbe43_sample',\n",
+ " 'ooi-data/RS01SBPS-SF01A-2D-PHSENA101-streamed-phsen_data_record',\n",
+ " 'ooi-data/RS01SBPS-SF01A-3A-FLORTD101-streamed-flort_d_data_record',\n",
+ " 'ooi-data/RS01SBPS-SF01A-3C-PARADA101-streamed-parad_sa_sample',\n",
+ " 'ooi-data/RS01SBPS-SF01A-3D-SPKIRA101-streamed-spkir_data_record',\n",
+ " 'ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_dark_sample',\n",
+ " 'ooi-data/RS01SBPS-SF01A-4A-NUTNRA101-streamed-nutnr_a_sample',\n",
+ " 'ooi-data/RS01SBPS-SF01A-4B-VELPTD102-streamed-velpt_velocity_data',\n",
+ " 'ooi-data/RS01SBPS-SF01A-4F-PCO2WA101-streamed-pco2w_a_sami_data_record',\n",
+ " 'ooi-data/RS01SLBS-LJ01A-05-HPIESA101-streamed-echo_sounding',\n",
+ " 'ooi-data/RS01SLBS-LJ01A-10-ADCPTE101-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/RS01SLBS-LJ01A-12-CTDPFB101-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS01SLBS-MJ01A-06-PRESTA101-streamed-prest_real_time',\n",
+ " 'ooi-data/RS01SLBS-MJ01A-12-VEL3DB101-streamed-vel3d_b_sample',\n",
+ " 'ooi-data/RS01SUM1-LJ01B-12-VEL3DB104-streamed-vel3d_b_sample',\n",
+ " 'ooi-data/RS01SUM2-MJ01B-12-ADCPSK101-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/RS03ASHS-MJ03B-07-TMPSFA301-streamed-tmpsf_sample',\n",
+ " 'ooi-data/RS03ASHS-MJ03B-09-BOTPTA304-streamed-botpt_nano_sample_15s',\n",
+ " 'ooi-data/RS03ASHS-MJ03B-10-CTDPFB304-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS03AXBS-LJ03A-05-HPIESA301-streamed-echo_sounding',\n",
+ " 'ooi-data/RS03AXBS-LJ03A-10-ADCPTE303-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/RS03AXBS-LJ03A-11-OPTAAC303-streamed-optaa_sample',\n",
+ " 'ooi-data/RS03AXBS-LJ03A-12-CTDPFB301-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS03AXBS-MJ03A-06-PRESTA301-streamed-prest_real_time',\n",
+ " 'ooi-data/RS03AXBS-MJ03A-12-VEL3DB301-streamed-vel3d_b_sample',\n",
+ " 'ooi-data/RS03AXPS-PC03A-05-ADCPTD302-streamed-adcp_velocity_beam',\n",
+ " 'ooi-data/RS03AXPS-PC03A-06-VADCPA301-streamed-vadcp_velocity_beam',\n",
+ " 'ooi-data/RS03AXPS-PC03A-06-VADCPA301-streamed-vadcp_velocity_beam_5',\n",
+ " 'ooi-data/RS03AXPS-PC03A-4A-CTDPFA303-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS03AXPS-PC03A-4B-PHSENA302-streamed-phsen_data_record',\n",
+ " 'ooi-data/RS03AXPS-PC03A-4C-FLORDD303-streamed-flort_d_data_record',\n",
+ " 'ooi-data/RS03AXPS-SF03A-2A-CTDPFA302-streamed-ctdpf_sbe43_sample',\n",
+ " 'ooi-data/RS03AXPS-SF03A-2D-PHSENA301-streamed-phsen_data_record',\n",
+ " 'ooi-data/RS03AXPS-SF03A-3A-FLORTD301-streamed-flort_d_data_record',\n",
+ " 'ooi-data/RS03AXPS-SF03A-3B-OPTAAD301-streamed-optaa_sample',\n",
+ " 'ooi-data/RS03AXPS-SF03A-3C-PARADA301-streamed-parad_sa_sample',\n",
+ " 'ooi-data/RS03AXPS-SF03A-3D-SPKIRA301-streamed-spkir_data_record',\n",
+ " 'ooi-data/RS03AXPS-SF03A-4A-NUTNRA301-streamed-nutnr_a_dark_sample',\n",
+ " 'ooi-data/RS03AXPS-SF03A-4A-NUTNRA301-streamed-nutnr_a_sample',\n",
+ " 'ooi-data/RS03AXPS-SF03A-4B-VELPTD302-streamed-velpt_velocity_data',\n",
+ " 'ooi-data/RS03AXPS-SF03A-4F-PCO2WA301-streamed-pco2w_a_sami_data_record',\n",
+ " 'ooi-data/RS03CCAL-MJ03F-12-CTDPFB305-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS03ECAL-MJ03E-12-CTDPFB306-streamed-ctdpf_optode_sample',\n",
+ " 'ooi-data/RS03INT1-MJ03C-07-D1000A301-streamed-d1000_sample',\n",
+ " 'ooi-data/RS03INT1-MJ03C-09-TRHPHA302-streamed-trhph_sample',\n",
+ " 'ooi-data/RS03INT1-MJ03C-10-TRHPHA301-streamed-trhph_sample',\n",
+ " 'ooi-data/RS03INT2-MJ03D-12-VEL3DB304-streamed-vel3d_b_sample',\n",
+ " 'ooi-data/annotations',\n",
+ " 'ooi-data/index.json',\n",
" 'ooi-data/stats.json']\n",
"```"
]
@@ -228,7 +3751,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.3"
+ "version": "3.11.4"
}
},
"nbformat": 4,
diff --git a/book/chapters/documentation.ipynb b/book/chapters/documentation.ipynb
index 54e4527..121e4a6 100644
--- a/book/chapters/documentation.ipynb
+++ b/book/chapters/documentation.ipynb
@@ -8,7 +8,7 @@
"# Documentation\n",
"\n",
"\n",
- "GeoSMART Oceanography Jupyter Book notes \n",
+ "GeoSMART Oceanography Jupyter Book: Some assembly required, and here is how to deal with these technical details. \n",
"\n",
"\n",
"\n",
@@ -16,13 +16,7 @@
"- 1 [Technical Elements](#Technical-Elements)\n",
"- 2 [Other Data Resources](#Other-Data-Resources)\n",
"- 3 [Computing Infrastructure](#Computing-Infrastructure)\n",
- "\n",
- "\n",
- "\n",
- "## JupyterBook To Do\n",
- "\n",
- "- Shallow profiler dataset rebuild from Zarr / Cloud resources\n",
- "- Refactor the contents "
+ "\n"
]
},
{
@@ -353,7 +347,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "0ed45d5d-0d15-4894-bc0b-2629205c0cde",
"metadata": {
"tags": []
@@ -371,7 +365,7 @@
""
]
},
- "execution_count": 1,
+ "execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@@ -406,7 +400,7 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 3,
"id": "15435601-0c8b-4fdc-a4d3-1f26f3a10ab1",
"metadata": {
"tags": []
@@ -428,10 +422,10 @@
" "
],
"text/plain": [
- ""
+ ""
]
},
- "execution_count": 40,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -2134,7 +2128,7 @@
" - numpy\n",
" - pandas\n",
" - matplotlib\n",
- " - netcdf4\n",
+ " - netCDF4\n",
" - xarray\n",
" - ffmpeg\n",
"```\n",