PyFVCOM is a collection of various tools and utilities which can be used to extract, analyse and plot input and output files from FVCOM.
Easiest way is to install with pip/pip3:
pip install PyFVCOM-
Python. This has been written against Python 2.7.11 and tentatively against Python 3.4.3, so in principle anything newer than those should be OK.
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numpy, again, this has been tested with numpy version 1.4.1 to 1.10.4.
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scipy, versions 0.7.2 to 0.14.1.
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matplotlib, versions 1.0.1 to 1.5.1.
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netCDF4, version 0.9.9 to 1.1.5.
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jdcal, version 1.0 to 1.2.
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pyshp, version 1.2.3.
Optionally:
- iPython, version 0.10.2 to 3.2.1. This makes for a good development environment, particularly when invoked with the -pylab argument, which automatically imports matplotlib.pylab and numpy, amongst others.
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buoy_tools - read data from an SQLite3 database of BODC buoy data.
- get_buoy_metadata
- get_buoy_data
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cst_tools - create coastline files for SMS from shapefiles or DHI MIKE arcs.
- read_ESRI_shapefile
- read_arc_MIKE
- read_CST
- write_CST
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ctd_tools - interrogate an SQLite data base of CTD casts.
- get_CTD_metadata
- get_CTD_data
- get_ferrybox_data
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current_tools - convert from vector components to scalars and back.
- scalar2vector
- vector2scalar
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grid_tools - tools to parse SMS, DHI MIKE and FVCOM unstructured grids. Also provides functionality to add coasts and clip triangulations to a given domain. Functions to parse FVCOM river files are also included, as is a function to resample an unstructured grid onto a regular grid (without interpolation, simply finding the nearest point within a threshold distance).
- read_sms_mesh
- read_fvcom_mesh
- read_mike_mesh
- read_gmsh_mesh
- write_sms_mesh
- write_sms_bathy
- write_mike_mesh
- find_nearest_point
- element_side_lengths
- fix_coordinates
- clip_triangulation
- get_river_config
- get_rivers
- mesh2grid
- line_sample
- OSGB36_to_WGS84
- connectivity
- clip_domain
- surrounders
- get_area
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ll2utm - convert from spherical to cartesian UTM coordinates and back. Available from http://robotics.ai.uiuc.edu/~hyoon24/LatLongUTMconversion.py.
- LL_to_UTM
- UTM_to_LL
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ocean_tools - a number of routines to convert between combinations of temperature, salinity, pressure, depth and density.
- pressure2depth
- depth2pressure
- dT_adiab_sw
- theta_sw
- cp_sw
- sw_smow
- sw_dens0
- sw_seck
- sw_dens
- sw_svan
- sw_sal78
- sw_sal80
- sw_salinity
- dens_jackett
- cond2salt
- vorticity (currently empty)
- zbar
- pea
- simpsonhunter
- mixedlayerdepth
- stokes
- dissipation
- calculate_rhum
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plot - plotting class for FVCOM outputs.
- Plotter.plot_field
- Plotter.plot_quiver
- Plotter.plot_lines
- Plotter.remove_line_plots
- Plotter.plot_scatter
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process_results - perform some analyses on FVCOM data read in using read_FVCOM_results.
- calculate_total_CO2
- calculate_CO2_leak_budget
- data_average
- unstructured_grid_volume
- residual_flow
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read_results - parse the netCDF model output and extract a subset of the variables.
- ncwrite
- ncread
- read_probes
- write_probes
- elems2nodes
- nodes2elems
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stats_tools - some basic statistics tools.
- calculate_regression
- calculate_polyfit
- coefficient_of_determination
- fix_range
- rmse
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tidal_ellipse - Python version of the Tidal Ellipse MATLAB toolbox http://woodshole.er.usgs.gov/operations/sea-mat/tidal_ellipse-html/index.html.
- ap2ep
- ep2ap
- cBEpm
- get_BE
- sub2ind
- plot_ell
- do_the_plot
- prep_plot
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tide_tools - tools to use and abuse tidal data from an SQLite database of tidal time series.
- julian_day
- gregorian_date
- add_harmonic_results
- get_observed_data
- get_observed_metadata
- clean_observed_data
- parse_TAPPY_XML
- get_harmonics
- read_POLPRED
- grid_POLPRED
- get_harmonics_POLPRED
The examples directory includes some Jupyter notebooks of some brief examples of how to use PyFVCOM. There are also sample scripts of those notebooks.