Error in 'usage [-h] [--load LOAD] ocean'

[deborarodriguesp]

Hello!

I was so happy to finally have someone using Pyfes! I tried to use the past weeks, and it simply does not work for me! Could you help me, please?

I found this error, repeatedly:

usage: fes_compute_tide.py [-h] [--load LOAD] ocean
fes_compute_tide.py: error: the following arguments are required: ocean

But I am using a .ini file, as you are also using in fes.ini... I will show the first block:

TIDE_2N2_FILE         = D:/DOUTORAMENTO/Tide/FES2014/ocean_tide_extrapolated/2n2.nc
TIDE_2N2_LATITUDE     = lat
TIDE_2N2_LONGITUDE    = lon
TIDE_2N2_AMPLITUDE    = amplitude
TIDE_2N2_PHASE        = phase

I will past here my code, which I followed your guide, but I don't need the grid interpolation part:

import argparse
import numpy as np
import pandas as pd
import pyfes
import os
import sys
import pickle

def usage():
    """
    Command syntax
    """
    parser = argparse.ArgumentParser(
        description='Program example using the Python API for FES.')
    parser.add_argument('ocean',
                        help='Path to the configuration file that contains '
                             'the definition of grids to use to compute the '
                             'ocean tide',
                        type=str)
    parser.add_argument('--load',
                        help='Path to the configuration file that contains '
                             'the definition of grids to use to compute the '
                             'load tide',
                        type=str)
    return parser.parse_args()

def compute_dates(start_date, end_date, step):
    period = [start_date]
    date_i = start_date
    while date_i < end_date:
        date_i += np.timedelta64(step, 'm')
        period.append(date_i)
    return period

def main():
    # study location
    location = 'Pará_Centro'
    lon_study = -47.782969
    lat_study = -0.093179

    # dates
    start_date = np.datetime64('2012-11-01 00:00')
    end_date = np.datetime64('2014-01-01 00:00')
    step = 60 # expressed in minutes
    period = compute_dates(start_date, end_date, step)

    args = usage()
    visu = False

    # Create handler
    short_tide = pyfes.Handler('ocean', 'memory', 'ocean_tide_extrapolation.ini')
    sys.exit()

    # Calculate tide
    tide_results = {}
    tide_results['tide_from_fes'] = []
    tide_results['dates'] = period

    for date in period:
        print(date)
        dates.fill(date)

        tide, lp, _ = short_tide.calculate(lon_study.ravel(), lat_study.ravel(), dates.ravel())
        tide, lp = tide.reshape(shape), lp.reshape(shape)

        # Convert tide to cm and to a 2d numpy masked array
        geo_tide = (tide + lp) * 0.01
        geo_tide = geo_tide.reshape(grid_lons.shape)
        geo_tide = np.ma.masked_where(np.isnan(geo_tide), geo_tide)

        # Extract tide at study location
        tide_extract, lon_extract, lat_extract = get_fes_wl_at_extraction_point(lons, lats, lon_study, lat_study, geo_tide)

        # save tide results in dictionnary
        tide_results['tide_from_fes'].append(tide_extract)

if __name__ == '__main__':
    main()

If you could help me, I would be extremely grateful, thank you!

[deborarodriguesp]

Hello!

I was so happy to finally have someone using Pyfes! I tried to use the past weeks, and it simply does not work for me! Could you help me, please?

I found this error, repeatedly:

usage: fes_compute_tide.py [-h] [--load LOAD] ocean
fes_compute_tide.py: error: the following arguments are required: ocean

But I am using a .ini file, as you are also using in fes.ini... I will show the first block:

TIDE_2N2_FILE         = D:/DOUTORAMENTO/Tide/FES2014/ocean_tide_extrapolated/2n2.nc
TIDE_2N2_LATITUDE     = lat
TIDE_2N2_LONGITUDE    = lon
TIDE_2N2_AMPLITUDE    = amplitude
TIDE_2N2_PHASE        = phase

I will past here my code, which I followed your guide, but I don't need the grid interpolation part:

import argparse
import numpy as np
import pandas as pd
import pyfes
import os
import sys
import pickle

def usage():
    """
    Command syntax
    """
    parser = argparse.ArgumentParser(
        description='Program example using the Python API for FES.')
    parser.add_argument('ocean',
                        help='Path to the configuration file that contains '
                             'the definition of grids to use to compute the '
                             'ocean tide',
                        type=str)
    parser.add_argument('--load',
                        help='Path to the configuration file that contains '
                             'the definition of grids to use to compute the '
                             'load tide',
                        type=str)
    return parser.parse_args()

def compute_dates(start_date, end_date, step):
    period = [start_date]
    date_i = start_date
    while date_i < end_date:
        date_i += np.timedelta64(step, 'm')
        period.append(date_i)
    return period

def main():
    # study location
    location = 'Pará_Centro'
    lon_study = -47.782969
    lat_study = -0.093179

    # dates
    start_date = np.datetime64('2012-11-01 00:00')
    end_date = np.datetime64('2014-01-01 00:00')
    step = 60 # expressed in minutes
    period = compute_dates(start_date, end_date, step)

    args = usage()
    visu = False

    # Create handler
    short_tide = pyfes.Handler('ocean', 'memory', 'ocean_tide_extrapolation.ini')
    sys.exit()

    # Calculate tide
    tide_results = {}
    tide_results['tide_from_fes'] = []
    tide_results['dates'] = period

    for date in period:
        print(date)
        dates.fill(date)

        tide, lp, _ = short_tide.calculate(lon_study.ravel(), lat_study.ravel(), dates.ravel())
        tide, lp = tide.reshape(shape), lp.reshape(shape)

        # Convert tide to cm and to a 2d numpy masked array
        geo_tide = (tide + lp) * 0.01
        geo_tide = geo_tide.reshape(grid_lons.shape)
        geo_tide = np.ma.masked_where(np.isnan(geo_tide), geo_tide)

        # Extract tide at study location
        tide_extract, lon_extract, lat_extract = get_fes_wl_at_extraction_point(lons, lats, lon_study, lat_study, geo_tide)

        # save tide results in dictionnary
        tide_results['tide_from_fes'].append(tide_extract)

if __name__ == '__main__':
    main()

If you could help me, I would be extremely grateful, thank you!

okay, I understand my problem now, I need to use this in conda: python fes_compute_tide.py D:/DOUTORAMENTO/Tide/Tide-main/ocean_tide_extrapolation.ini --load D:/DOUTORAMENTO/Tide/Tide-main/ocean_tide_extrapolation.ini

[fournifl]

Hello, I am happy that you found the solution of your problem. I hope you can do what you want with pyfes. Florent