LinePPlan

LinePPlan.py

import numpy as np
import matplotlib.pyplot as plt
import seawater
%matplotlib widget
import pooch
import xarray as xr
import pandas

"""
eg 

Station Lat Latmin Lon Lonmin depth activity
P1 48 34.5 125 30.0 120 CTD
P2 48 36.0 126 00.0 114 Rosette/Bongo
P3 48 37.5 126 20.0 750 CTD
"""
df = pandas.read_csv('LinePStations.txt', delimiter=' ', header='infer', index_col=0)
df['dlat'] = df.Lat + df.Latmin / 60
df['dlon'] = -df.Lon - df.Lonmin / 60
along, head = seawater.dist(df.dlat, df.dlon, units='nm')
df['along'] = np.cumsum(np.concatenate([[0], along]))

# make time series from StationTimes.txt

t0 = np.datetime64('2024-01-27T12:43')
lat0 = 49 + 2.6/60
lon0 = -131 - 23.65/60

"""
eg 
# Station, sampling [h], speed to station [kts]
P26, 12.0, 12.0
P25, 1.5, 12.0
P24, 1.5, 12.0
P23, 1.5, 12.0
"""

ts = [[],[], [], []]

for nn, plan in enumerate(['StationTimes12there8back.txt', 
                           'StationTimes8there12back.txt',
                          'StationTimes12there12back.txt',
                          'StationTimes12there8back36Papa.txt',
                          ]):
    station_data = pandas.read_csv(plan, delimiter=',', names=['station', 'sampletime', 'speed'],
                                    comment='#')
    ts[nn]={}    
    Nstations = len(station_data)
    
    time = np.zeros(2*Nstations+1, dtype='datetime64[s]')
    tslat = np.zeros(2*Nstations+1, dtype='float')
    tslon = np.zeros(2*Nstations+1, dtype='float')
    
    # need a start...
    time[0] = t0
    tslat[0] = lat0
    tslon[0] = lon0
    num = 0
    for i in range(0, Nstations):
        # each station has an arrive time, and a depart time.
        station = station_data.iloc[i]
        stname = station['station']
        # arrive
        speed = station['speed']
        num += 1
        tslat[num] = df.loc[stname].dlat
        tslon[num] = df.loc[stname].dlon
        dist, ang = seawater.dist(tslat[num-1:num+1], tslon[num-1:num+1], units='nm')
        time[num] = time[num-1] + np.timedelta64(int(dist / speed * 3600) , 's')

        # leave
        num += 1
        
        stationtime = np.timedelta64(int(station['sampletime'] * 3600), 's')
        time[num] = time[num-1] + stationtime
        tslat[num] = df.loc[stname].dlat
        tslon[num] = df.loc[stname].dlon

    ts[nn]['time'] = time
    ts[nn]['lon'] = tslon
    ts[nn]['lat'] = tslat