s100py 0.5.1

This python package provides utilities for encoding hydrographic datasets in the International Hydrographic Organization (IHO) S-100 format

s100py

Python Utilities for Working with IHO S-100 Data Formats

Overview

This python package provides utilities for encoding hydrographic datasets in the International Hydrographic Organization (IHO) S-100 format.

Background

The IHO S-100 standard is a data framework for digital products and services for hydrographic, maritime, and GIS communities, comprised of multiple data encoding formats designed for interoperability with Electronic Navigational Charts (ENCs).

The initial focus of this package is on two of the S-100 encoding formats:

• S-104 Water Level Information for Surface Navigation
• S-111 Surface Currents

However, support for additional formats will likely be added in the future.

For further information about S-100 formats, see the IHO website.

Features

• Create and modify S-111 compliant HDF5 files in all four data coding formats:

  1.  Time-series at fixed station
  2.  Regularly-gridded arrays
  3.  Ungeorectified gridded arrays (i.e. irregular grid)
  4.  Time series for moving platform
  

• Chop output into multiple subgrids (i.e. tiles), each written to a distinct S-111 file, to reduce file sizes

• Create and modify HDF5 S-100/S-111 metadata

Requirements

This codebase is written for Python 3 and relies on the following python packages:

• h5py
• numpy
• thyme

Installation

This package relies on thyme, which requires the GDAL Python bindings be present, so it usually can't just be installed using pip install gdal. We recommend installing GDAL either through a package manager (e.g. conda, apt, yum, pacman) or by compiling from scratch. Miniconda is probably the easiest method.

Once gdal has been installed, s100py can be installed using pip:

pip install s100py

Example Usage

Create an S-111 File (Type 1):

from s100py import s111

data_coding_format = 1

# meters below sea surface (0 = at/near surface)
current_depth = 0

file_metadata = s111.S111Metadata(
        "Gulf of Mexico",  # region
        "harmonic_current_predictions",  # product description
        3,  # current type code for astronomical prediction
        "US",  # producer code
        "station1234",  # station id
        None)  # model identifier

input_data = [s111.S111TimeSeries(
            longitude,  # 1D `numpy.ndarray` containing longitude values
            latitude,  # 1D `numpy.ndarray` containing latitude values
            speed,  # 1D `numpy.ndarray` containing speed values in knots
            direction,  # 1D `numpy.ndarray` containing Direction values in arc-degrees
            datetime_values)]  # List containing a `datetime.datetime` for each observation in the series

s111.time_series_to_s111(
        input_data,
        '/path/to/s111_directory',
        file_metadata,
        data_coding_format,
        current_depth)

Create an S-111 File (Type 2)

NOS Chesapeake Bay Operational Forecast System file valid at 7/9/2019 0000 UTC:

import datetime
from s100py import s111
from thyme.model import roms

data_coding_format = 2
target_cellsize = 500 # meters

# meters below sea surface (0 = at/near surface), default = 4.5 m
target_depth = 0

file_metadata = s111.S111Metadata(
        "Chesapeake Bay",  # region
        "ROMS_Hydrodynamic_Model_Forecasts",  # product type description
        6,  # current data type for hydrodynamic forecast
        "US",  # producer code
        None,  # station id
        "CBOFS")  # model identifier

native_model_file = roms.ROMSFile('/path/to/nos.cbofs.fields.f001.20190709.t00z.nc')
model_index_file = roms.ROMSIndexFile('/path/to/create/index_file.nc')

try:
    native_model_file.open()
    model_index_file.open()
    model_index_file.init_nc(native_model_file, target_cellsize, 'my_roms_model', '/path/to/shoreline_shapefile.shp')

finally:
    model_index_file.close()
    native_model_file.close()

s111.model_to_s111(
        model_index_file,
        [native_model_file],
        '/path/to/s111_directory',
        datetime.datetime(2019, 7, 9, 0, 0),
        file_metadata,
        data_coding_format,
        target_depth)

Create an S-111 File (Type 3)

NOS Chesapeake Bay Operational Forecast System file valid at 7/9/2019 0000 UTC:

import datetime
from s100py import s111
from thyme.model import roms

data_coding_format = 3

# meters below sea surface (0 = at/near surface), default = 4.5 m
target_depth = 0

file_metadata = s111.S111Metadata(
        "Chesapeake Bay",  # region
        "ROMS_Hydrodynamic_Model_Forecasts",  # product type description
        6,  # current data type for hydrodynamic forecast
        "US",  # producer code
        None,  # station id
        "CBOFS")  # model identifier

native_model_file = roms.ROMSFile('/path/to/nos.cbofs.fields.f001.20190709.t00z.nc')

s111.model_to_s111(
        None,
        [native_model_file],
        '/path/to/s111_directory',
        datetime.datetime(2019, 7, 9, 0, 0),
        file_metadata,
        data_coding_format,
        target_depth)

Create an S-111 file (Type 4):

from s100py import s111

data_coding_format = 4

# meters below sea surface (0 = at/near surface)
current_depth = 15

file_metadata = s111.S111Metadata(
        "Western_N_Pacific_Ocean_Philippine_Sea",  # region
        "argos_lagrangian_drifter_12hr_interpolated",  # product type description
        4,  # current type code for analysis or hybrid method
        "US",  # producer code
        None,  # station id
        None)  # model identifier

input_data = [s111.S111TimeSeries(
            longitude,  # 1D `numpy.ndarray` containing longitude values
            latitude,  # 1D `numpy.ndarray` containing latitude values
            speed,  # 1D `numpy.ndarray` containing speed values in knots
            direction,  # 1D `numpy.ndarray` containing Direction values in arc-degrees
            datetime_values)]  # List containing a `datetime.datetime` for each observation in the series

s111.time_series_to_s111(
        input_data,
        '/path/to/s111_directory',
        file_metadata,
        data_coding_format,
        current_depth)

Authors

• Erin Nagel (UCAR), [e-mail]
• Jason Greenlaw (ERT), [e-mail]

License

This work, as a whole, is licensed under the BSD 2-Clause License (see LICENSE), however it contains major contributions from the U.S. National Oceanic and Atmospheric Administration (NOAA), 2017 - 2019, which are individually dedicated to the public domain.

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an 'as is' basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.

Acknowledgments

This software has been developed by the National Oceanic and Atmospheric Administration (NOAA)/National Ocean Service (NOS)/Office of Coast Survey (OCS)/Coast Survey Development Lab (CSDL) for use by the scientific and oceanographic communities.

CSDL wishes to thank the following entities for their assistance:

• NOAA/NOS/Center for Operational Oceanographic Products and Services (CO-OPS)
• Canadian Hydrographic Service (CHS)
• Teledyne CARIS