import intake
import hvplot.pandas
import hvplot.xarray
import cook_inlet_catalogs as cic
import holoviews as hv

CTD Transect (CMI UAF): from East Foreland Lighthouse¶

Seasonality of Boundary Conditions for Cook Inlet, Alaska: Transect (3) at East Foreland Lighthouse.

9 CTD profiles at stations across 10 cruises in (approximately) the same locations. Approximately monthly for summer months, 2004 and 2005.

Part of the project:

Seasonality of Boundary Conditions for Cook Inlet, Alaska Steve Okkonen Principal Investigator Co-principal Investigators: Scott Pegau Susan Saupe Final Report OCS Study MMS 2009-041 August 2009 Report: https://researchworkspace.com/files/39885971/2009_041.pdf

cat = intake.open_catalog(cic.utils.cat_path("ctd_transects_cmi_uaf"))

Plot all datasets in catalog¶

dd, ddlabels = cic.utils.combine_datasets_for_map(cat)
dd.hvplot(**cat.metadata["map"]) * ddlabels.hvplot(**cat.metadata["maplabels"])

List available datasets in the catalog¶

dataset_ids = list(cat)
dataset_ids

['Cruise-01',
 'Cruise-02',
 'Cruise-03',
 'Cruise-04',
 'Cruise-05',
 'Cruise-06',
 'Cruise-07',
 'Cruise-08',
 'Cruise-09',
 'Cruise-10']

Select one dataset to investigate¶

try:
    dataset_id = dataset_ids[2]
except:
    dataset_id = dataset_ids[0]
print(dataset_id)

dd = cat[dataset_id].read()
dd

Cruise-03

	Cruise	Station	Longitude	Latitude	Depth [m]	Temperature	Salinity	flag	datetime	distance [km]
0	3	1	-151.417	60.718	1	15.3663	21.0780	5	2004-08-08 07:55:00	0.000000
1	3	1	-151.417	60.718	2	15.3543	21.1053	5	2004-08-08 07:55:00	0.000000
2	3	1	-151.417	60.718	3	15.3437	21.1434	5	2004-08-08 07:55:00	0.000000
3	3	1	-151.417	60.718	4	15.3313	21.1376	5	2004-08-08 07:55:00	0.000000
4	3	1	-151.417	60.718	5	15.3144	21.1778	5	2004-08-08 07:55:00	0.000000
...	...	...	...	...	...	...	...	...	...	...
331	3	9	-151.683	60.716	6	14.0800	22.1400	5	2004-08-08 09:20:00	14.534355
332	3	9	-151.683	60.716	7	14.0800	22.1400	5	2004-08-08 09:20:00	14.534355
333	3	9	-151.683	60.716	8	14.0800	22.1400	5	2004-08-08 09:20:00	14.534355
334	3	9	-151.683	60.716	9	14.0800	22.1361	5	2004-08-08 09:20:00	14.534355
335	3	9	-151.683	60.716	10	14.0800	22.1323	5	2004-08-08 09:20:00	14.534355

336 rows × 10 columns

Plot one dataset¶

keys = list(cat[dataset_id].metadata["plots"].keys())
print(keys)

plots = []
for key in keys:
    plot_kwargs = cat[dataset_id].metadata["plots"][key]
    if "clim" in plot_kwargs and isinstance(plot_kwargs["clim"], list):
        plot_kwargs["clim"] = tuple(plot_kwargs["clim"])
    if "dynamic" in plot_kwargs:
        plot_kwargs["dynamic"] = False
    plots.append(cat[dataset_id].ToHvPlot(**plot_kwargs).read())
hv.Layout(plots).cols(1)

['salt', 'temp']