Skip to main content

processing of ship campaign data

Project description

shipspy: ship campaign data processing and standardisation

With shipspy, data from ship campaigns can be processed and standardised. A number of instruments are included.

Setup

Install shipspy:

pip install shipspy

Using shipspy

The following processing options are available.

DShip

With the dship subcommand, data from the ship integrated system can be processed. For an exemplary order to download underway data, see [1]. The following steps are done:

  • Fixing time stamps
  • Averaging to minutely time stamps
  • Removing unphysical values
  • Renaming variables, changing units, and adding attributes
  • Converting to netCDF

To process dship data run

shipspy dship -i <input file> -o <output file> -a <attribute dictionary> -s <ship>

with

  • input file: downloaded data from BSH or GEOMAR (or directly from the ship) as txt or dat file with unix time stamp (seconds since 1970-01-01)
  • output file: file name of netCDF output file
  • attribute dictionary: yaml dictionary with variable names and attribute. For example dictionaries for the different research vessels see rv_information
  • ship: name of the ship. Options are Merian, Sonne, Polarstern, Meteor, and Test.

Renaming

The rename command can be used to

  • fix the time stamps
  • rename variables and add attributes
  • convert units to SI
  • remove unphysical values
  • Convert and save the file as netCDF

To rename a data file run

shipspy rename -i <input file> -o <output file> -a <attribute dictionary> -d <instrument>

with

  • input file: input file, file format depends on the instrument
  • output file: file name of netCDF output file
  • attribute dictionary: yaml dictionary with variable names and attribute. For examples see [1]
  • instrument: instrument name. Options are calitoo, ceilometer, ctd, hatpro, microtops, radiosondes, test, uav

Sections

The section command adds a new coordinate and specifies the time period of the campaign. To use it run

shipspy sections -i <input file> -o <output file> -s <section file> -t <time dimension name> -a <global attribute dictionary>

with

  • input file: input netCDF file
  • output file: file name of netCDF output file
  • section file: txt file specifying the campaign dates (start, end, break) and the sections in which it should be divided. For an example, see [1].
  • time dimension name: name of the time dimension. Default is time but sometimes it can be something like start_time.
  • global attribute dictionary: yaml file with global attributes if wanted. For example files see [1].

The repository [1] with the settings for the ARC and additional scripts can serve as a template.

PAMOS

The pamos command can be used to process data from the instrument PAMOS (Portable Atmospheric Measurement box On Sea) which is particularly developed for (commercial) vessels. To you it run

shipspy pamos -i <input directory> -o <output file> -a <attribute dictionary> -c <header file> -f <quality flag dictionary> -e <additional attribute dictionary>

with

  • input directory: input directory, where the raw data files are stored
  • output file: file name of netCDF output file
  • attribute dictionary: yaml dictionary with variable names and attribute.
  • header file: text file which defines the columns of the raw data files. For an example, see [2].
  • quality flag dictionary: optional yaml dictionary to be used to assess the quality flags. For an example see [2].
  • additional attribute dictionary: optional yaml dictionary with extra variables like quality and pump flags.

The repository [2] with the settings for PAMOS on the MS Fridtjof Nansen can serve as a template.

References

[1] Köhler, L. (2023). ARC: Processing of atmospheric and oceanographic measurements (Version v1.0.0) [Computer software]. https://github.com/LauraKoehler/arc_processing

[2] Köhler, L. (2025). PAMOS processing (Version 1.0.0) [Computer software]. https://github.com/LauraKoehler/pamos_processing

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

shipspy-1.1.0.tar.gz (14.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

shipspy-1.1.0-py3-none-any.whl (16.1 kB view details)

Uploaded Python 3

File details

Details for the file shipspy-1.1.0.tar.gz.

File metadata

  • Download URL: shipspy-1.1.0.tar.gz
  • Upload date:
  • Size: 14.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for shipspy-1.1.0.tar.gz
Algorithm Hash digest
SHA256 e3bed866d4d4e8f6c1397279e0b73ff728be34700188f492ac4e29775785e34d
MD5 1fcd538c0afbe7478cfcde9ceb6e64aa
BLAKE2b-256 a2e86846b52abc817324a6c6e8881a1a107e8b6d8434a4a57bec4eb9608a3a8c

See more details on using hashes here.

File details

Details for the file shipspy-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: shipspy-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 16.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for shipspy-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f1f15cabc649f71e7b39ba76499bcba4610ffb4383f22b6f3e9d4af966a44228
MD5 367622ebcd128e72af8db88487673680
BLAKE2b-256 aa8d7a19fe5390d8346db42377a754cb46b56c8b602f94516976f7dd21fff6cf

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page