Using datastore shapes with echoSMs

This section is a work in progress

Here is an example of getting model shapes from the datastore and estimating the target strength using an echoSMs model.

import echosms
import requests
import numpy as np
import matplotlib.pyplot as plt

# The current location of the echoSMs datastore server
baseURI = 'https://echosms-data-store-app-ogogm.ondigitalocean.app/'

# Create an instance of the echoSMs KRM model for use below
m = echosms.KRMModel()

# Get all the datastore organisms from the CLAY_HORNE dataset.
# This returns the metadata about the specimens but no shape information.
r = requests.get(baseURI + 'v2/specimens/?dataset_id=CLAY_HORNE')

for o in r.json():
    print(f'Processing specimen {o["specimen_id"]} from the {o["dataset_id"]} dataset')

    # Get the organism data (including the shape) from the datastore
    r = requests.get(baseURI + 'v2/specimen/' + o['id'] + '/data')
    if r.status_code != 200:
        print(f'Request for data from specimen {o["id"]} failed - skipping')
        continue

    # Get the model data out of the requests object
    s = r.json()

    # Assemble the echoSMs model parameters
    p = {'medium_c': 1500,  # [m/s]
         'medium_rho': 1024,  # [kg/m^3]
         'theta': 90.0,  # [deg] dorsal aspect
         'f': np.arange(10, 201, 1)*1e3,  # [Hz]
         'organism': echosms.krmorganism_from_datastore(s['shapes'])}

    # Calculate the TS using those parameters
    ts = m.calculate_ts(p)

    # Add to a plot of all the TS results
    plt.plot(p['f']*1e-3, ts, label=s['specimen_id'])

plt.legend(title='Specimens')
plt.title('Dataset ' + s['dataset_id'])
plt.xlabel('Frequency [kHz]')
plt.ylabel('TS [dB re 1 m$^2$]')
plt.show()