polyadcirc.pyADCIRC package¶

Submodules¶

polyadcirc.pyADCIRC.basic module¶

This module contains a set of simple classes for use by

• polyadcirc.pyADCIRC.fort14_management
• polyadcirc.pyADCIRC.fort15_management
• polyadcirc.run_framework.domain
• polyadcirc.run_framework.random_manningsn
• polyadcirc.pyGriddata.gridObject

class polyadcirc.pyADCIRC.basic.MPI_for_no_mpi4py¶

Bases: object

A stand in class for when mpi4py is not installed

class polyadcirc.pyADCIRC.basic.comm_for_no_mpi4py¶

Bases: object

A set of stand ins for when mpi4py is not installed

Get_rank()¶

Return type:	int
Returns:	0

Get_size()¶

Return type:	int
Returns:	1

allgather(val)¶

Parameters:	val (object) – object to allgather
Return type:	object
Returns:	val

allreduce(val1, op=None)¶

Parameters:	val1 (object) – object to allreduce op – operation
Return type:	object
Returns:	val1

bcast(val, root=0)¶

Parameters:	val (object) – object to broadcast
Return type:	object
Returns:	val

class polyadcirc.pyADCIRC.basic.location(x, y)¶

Bases: polyadcirc.pyADCIRC.basic.pickleable

Store x, y coordinates

class polyadcirc.pyADCIRC.basic.node(x, y, bathymetry)¶

Bases: polyadcirc.pyADCIRC.basic.location

Stores data specific to a single node

class polyadcirc.pyADCIRC.basic.pickleable¶

Bases: object

Class that makes objects easily pickleable via a dict

class polyadcirc.pyADCIRC.basic.time(dt, statim, rnday, dramp)¶

Bases: polyadcirc.pyADCIRC.basic.pickleable

Stores time data specific to ADCIRC model runs from the users and fort.15 input file

polyadcirc.pyADCIRC.convert_fort14_to_fort13 module¶

A set of methods for converting a fort.14 formatted file to a fort.13 formatted file.

exception polyadcirc.pyADCIRC.convert_fort14_to_fort13.Error¶

Bases: exceptions.Exception

Base class for exceptions in this module.

exception polyadcirc.pyADCIRC.convert_fort14_to_fort13.InputError(expr, msg)¶

Bases: polyadcirc.pyADCIRC.convert_fort14_to_fort13.Error

Exception raised for errors in the input.

polyadcirc.pyADCIRC.convert_fort14_to_fort13.convert(source, keep_flags=0, target='fort.13')¶

Reads in a fort5...14 file and produces a fort5...13 file. By default all remaining flagged nodes are removed. If the user desires to keep the flagged nodes, keep_flags should be set to 1.

Parameters:

source (string) – the fort5...14 file name, this is used to determine the nodal manningsn values target (string) – the fort.13 files, this is used to determine the default manningsn value and relevant header information keep_flags (int) – _noflags – creates a fort.13 formatted file and removes remaining flags for Griddata _flags – creates a fort.13 formatted file with remainings flags for Griddata intact _fillins – creates a fort.13 formatted file and fills in remiaing flags from Griddata with data from source if data is present _color – creates a fort.13 formatted file and color codes the data based on wheter or not is is a default value or not

polyadcirc.pyADCIRC.convert_fort14_to_fort13.convert_go(grid, folder_name=None, keep_flags=0)¶

See convert() where source is the final *.14 file produced by the bash script associated with grid in folder_name

Parameters:

grid – gridInfo object folder_name (string) – folder containing the fort5...14 file keep_flags (int) – _noflags – creates a fort.13 formatted file and removes remaining flags for Griddata _flags – creates a fort.13 formatted file with remainings flags for Griddata intact _fillins – creates a fort.13 formatted file and fills in remiaing flags from Griddata with data from source if data is present _color – creates a fort.13 formatted file and color codes the data based on wheter or not is is a default value or not

polyadcirc.pyADCIRC.flag_fort14 module¶

Flags all of the nodes in a grid file accordining to the flagging scheme for Griddata_v1.32.F90

1. Averaging Flag_value: -999.0 (x1), -950.0 (x2), -960.0 (x4), -970.0 (x8) This scheme evaluate the average to count the GIS database points which are inside of Grid scale. And this scheme can use different Grid scale size classified by flag_value.
2. Highest point Flag_value: -888.0 This scheme pick up the highest point of GIS database inside of Grid_scale.
3. Nearest point Flag_value: -777.0 This scheme pick up the nearest point of GIS database inside of Grid_scale.

polyadcirc.pyADCIRC.flag_fort14.flag_fort14(grid_file_name='fort.14', avg_scheme=2)¶

Modifiy grid_file_name so that all of the nodes are flagged appropriately for Griddata program and save to flagged_grid_file_name.

Parameters:	grid_file_name (string) – name of fort.14 formatted file avg_scheme (int) – flag to choose which averaging scheme to use
Return type:	string
Returns:	flagged file path

polyadcirc.pyADCIRC.flag_fort14.flag_fort14_go(grid, avg_scheme=2)¶

Given a gridInfo object create a flagged version of the grid.file_name and save to grid.file_name

Parameters:	grid – polyadcirc.pyGriddata.gridInfo.gridObject avg_scheme (int) – flag to choose which averaging scheme to use

See flag_fort14()

Return type:	string
Returns:	flagged file path

polyadcirc.pyADCIRC.fort13_management module¶

This module fort13_management handles the reading/writing of fort.13 formatted files.

polyadcirc.pyADCIRC.fort13_management.read_default(data, path=None, file_name='fort.13')¶

Read in default manningsn from a *.13 file and update data accordingly

Parameters:	data (polyadcirc.run_framework.domain) – object in which to store default value path (string or None) – directory containing file_name file_name (string) – file name
Return type:	polyadcirc.run_framework.domain
Returns:	a reference to the polyadcirc.run_framework.domain object containing the default value

polyadcirc.pyADCIRC.fort13_management.read_manningsn(fid)¶

Reads in a node value line from fid

Parameters:	fid (file) – the file object to be read from we might want to re write this as the fromstring method returns an array :rtype: numpy.ndarray
Returns:	Returns an array([node, value])

polyadcirc.pyADCIRC.fort13_management.read_nodal_attr(data, path=None, file_name='fort.13', nums=None)¶

Load in nodal attributes from a *.13 file (only does Manning’s n for now) and return a dictonary (like a MATLAB struct) with these attributes).

Parameters:	data (polyadcirc.run_framework.domain) – the polyadcirc.run_framework.domain to which the nodal attribute information will be added :type path: string or None path – the directory containing the fort.13 to be read in file_name (string) – the name of the fort.13 formatted file nums (list) – list of nodes to read
Return type:	dict
Returns:	dictionary of Manning’s n values

polyadcirc.pyADCIRC.fort13_management.read_nodal_attr_dict(path=None, file_name='fort.13')¶

Load in nodal attributes from a *.13 file (only does Manning’s n for now) and return a dictonary (like a MATLAB struct) with these attributes).

Parameters:	path (string or None) – the directory containing the fort.13 to be read in file_name (string) – the name of the fort.13 formatted file
Return type:	dict
Returns:	dictionary of Manning’s n

polyadcirc.pyADCIRC.fort13_management.read_node_num(path=None, file_name='fort.13')¶

Read in the number of nodes in the mesh from a *.13 file

Parameters:	path (string or None) – directory containing file_name file_name (string) – file name
Return type:	int
Returns:	number of nodes in the mesh

polyadcirc.pyADCIRC.fort13_management.update_mann(data, path=None, default=None, file_name='fort.13')¶

Write out fort.13 to path with the attributes contained in Data.

Parameters:	data (numpy.ndarray or dict) – containing the nodal attribute information path (string or None) – the directory to which the fort.13 file will be written default (None or float) – default value file_name (string) – the name of the fort.13 formatted file

polyadcirc.pyADCIRC.fort13_management.write_manningsn(fid, node, value)¶

Write out a formated node value line to fid

Parameters:	fid (file) – the file object to be written to node (int) – the node number value (float) – the nodal value
Return type:	string
Returns:	formatted string for a line in a fort.13 formatted file

polyadcirc.pyADCIRC.fort14_management module¶

This module, fort14_management handles the reading/writing of fort.14 formatted files.

polyadcirc.pyADCIRC.fort14_management.clean(grid_object, folder_name=None)¶

Removes all except for the most recent *.14 files in folder_name or the current working direcory

Parameters:	grid_object – gridInfo folder_name (string) – folder to clean
Return type:	list
Returns:	list of fort.14 files in folder_name

polyadcirc.pyADCIRC.fort14_management.flag(grid_file_name='fort.14', avg_scheme=2)¶

Modifiy grid_file_name so that all of the nodes are flagged appropriately for Griddata program and save to flagged_grid_file_name.

Parameters:	grid_file_name (string) – name of fort.14 formatted file avg_scheme (int) – averaging scheme flag

See flag_fort14()

polyadcirc.pyADCIRC.fort14_management.flag_go(grid, avg_scheme=2)¶

Given a gridInfo object create a flagged version of the grid.file_name[8:] and save to grid.file_name

Parameters:	grid – gridInfo avg_scheme (int) – averaging scheme flag

See flag_fort14()

Return type:	string
Returns:	flagged file name

polyadcirc.pyADCIRC.fort14_management.is_flagged(grid)¶

Parameters:	grid – gridInfo
Return type:	bool
Returns:	true if flagged_grid_file_name exists and false if it doesn’t exist

polyadcirc.pyADCIRC.fort14_management.read_spatial_grid(data, path=None, make_domain_map=False)¶

Reads in a fort.14 file in path and updates data

Parameters:	data (polyadcirc.run_framework.domain) – python object to save the fort.14 data to path (string or None) – path to the``fort.14`` fortmatted file make_domain_map (bool) – flag for whether or not to make a node to element map
Returns:	reference to data

polyadcirc.pyADCIRC.fort14_management.read_spatial_grid_header(data, path=None)¶

Reads in the the number of nodes and elements from the fort.14 file in path and updates data

Parameters:	data (polyadcirc.run_framework.domain) – python object to save the fort.14 data to path (string or None) – path to the``fort.14`` fortmatted file
Returns:	reference to data

polyadcirc.pyADCIRC.fort14_management.update(data, bathymetry=None, path=None, file_name='fort.14')¶

Write out bathymetry in data to fort.14 formated file, by updating path/file_name accordingly

Parameters:	data (polyadcirc.run_framework.domain) – python object to save the fort.14 data to bathymetry (array or None) – if None then use the bathymetry in data path (string or None) – path to the``fort.14`` fortmatted file file_name (string) – file name

polyadcirc.pyADCIRC.fort15_management module¶

This module, fort15_management, handles the reading/writing of fort.15 formatted files.

polyadcirc.pyADCIRC.fort15_management.array_to_loc_list(station_array)¶

Convert a numpy.ndarray into a list of location.

Parameters:	station_array (numpy.ndarray) – an array of shape (n, 2) where n is the number of station locations
Return type:	list
Returns:	list of location

polyadcirc.pyADCIRC.fort15_management.fake_stations(domain, num_stat)¶

Given a domain and a number of stations creates a grid of stations with num_stat stations in the x and y directions.

Parameters:	domain (domain) – physical domain used to define the minimum and maximum extent of the grid of stations to be created num_stat (int or iterable of length 2) – number of stations in the x and y directions
Return type:	list
Returns:	list of location

polyadcirc.pyADCIRC.fort15_management.loc_list_to_array(station_list)¶

Convert a list of station locations to an array of x and y values.

Parameters:	station_list (list) – list of location
Return type:	numpy.ndarray of shape (n, 2)
Returns:	array of station locations

polyadcirc.pyADCIRC.fort15_management.read_recording_data(data, path=None)¶

Reads in fort.15 and stores the following in data as a time object (DT, STATIM, RNDAY, DRAMP)

Calulcates and stores:

• recording[key] = (meas_locs, total_obs, irtype)
• stations[key] = list() of locations

Parameters:	data (domain) – object to store reference to time path (string or None) – directory containing fort.15 file
Returns:	reference to data.recording and data.stations
Return type:	time

polyadcirc.pyADCIRC.fort15_management.set_ihot(ihot, path=None)¶

Set the hot start parameter to ihot

Parameters:	ihot (int) – Hot start paramter, fort.## file to read hot start dtat from

polyadcirc.pyADCIRC.fort15_management.set_write_hot(nhstar, nhsinc, path=None)¶

Set the hot start file generation paramters to nhstar and nhsinc

Parameters:	nhstar (int) – Type of hot start file to write nhsinc (int) – Frequency in timesteps to write data out to the hotstart file

polyadcirc.pyADCIRC.fort15_management.subdomain(fulldomain_path, subdomain_path)¶

Create a modifed fort.15 for the subdomain at subdomain_path.

• Reduce RNDAY by 0.05%
• Set NBFR to 0
• Remove periodic forcing boundary frequencies
• Remove recording stations outside of the subdomain grid and update the number of stations accordingly

Parameters:	flag (int) – type of subdomain 0 - ellipse, 1 - circle fulldomain_path (string) – fulldomain dir containing fort.15 file subdomain_path (string) – subdomain dir containing fort.15 file

polyadcirc.pyADCIRC.fort15_management.trim_locations(flag, subdomain_path, locs)¶

Remove locations outside of the subdomain from locs

Parameters:	flag (int) – type of subdomain 0 - ellipse, 1 - circle subdomain_path (string) – subdomain dir containing fort.15 file locs (list) – list of location objects
Return type:	list
Returns:	list of locations inside the subdomain

polyadcirc.pyADCIRC.fort15_management.trim_locations_circle(subdomain_path, locs)¶

Remove locations outside of the circular subdomain from locs

Parameters:	subdomain_path (string) – subdomain dir containing fort.15 file locs (list) – list of location objects
Return type:	list
Returns:	list of locations inside the subdomain

polyadcirc.pyADCIRC.fort15_management.trim_locations_ellipse(subdomain_path, locs)¶

Remove locations outside of the elliptical subdomain from locs

Parameters:	subdomain_path (string) – subdomain dir containing fort.15 file locs (list) – list of location objects
Return type:	list
Returns:	list of locations inside the subdomain

polyadcirc.pyADCIRC.fort1920_management module¶

This module is for the manipulation and creation of fort.19 and fort.20 files.

polyadcirc.pyADCIRC.fort1920_management.sin_wave(t_start, t_finish, amplitude, nnodes, time, periods=0.5, shift=0, timinc=None)¶

Creates data for a sine wave for forcing over the simulation time evert timinc.

Parameters:	t_start (float) – starting time of sine shaped wave in days t_finish (float) – ending time of the sine shaped wave in days amplitude (float) – amplitude of the sine shaped wave nnodes (int) – number of nodes for this BC time (time) – container for information from the fort.15 periods (float) – number of periods to include in the wave shift (float) – number of periods to shift the wave timinc (int) – time increment (secs) between consecutive sets of data
Return type:	tuple of (numpy.ndarray, numpy.ndarray, int)
Returns:	(times, values at times, timinc)

polyadcirc.pyADCIRC.fort1920_management.step_wave(t_start, t_finish, amplitude, nnodes, time, timinc=None)¶

Creates data for a square wave for forcing over the simulation time evert timinc.

Parameters:	t_start (float) – starting time of sine shaped wave in days t_finish (float) – ending time of the step shaped wave in days amplitude (float) – amplitude of the step shaped wave nnodes (int) – number of nodes for this BC time (time) – container for information from the fort.15 timinc (int) – time increment (secs) between consecutive sets of data
Return type:	tuple of (numpy.ndarray, numpy.ndarray, int)
Returns:	(times, values at times, timinc)

polyadcirc.pyADCIRC.fort1920_management.write_fort19(etiminc, esbin, file_name=None)¶

Write out a fort.19 formatted file to file_name

neta = total number of elevation specified boundary nodes

Parameters:	etimic – time increment (secs) between consecutive sets of elevation specified bounadry condition values esbin (numpy.ndarray of shape (k, neta)) – elevation at specfied elevation nodes k

See also

ADCIRC Non-periodic Elevation Boundary Condition File

polyadcirc.pyADCIRC.fort1920_management.write_fort20(ftiminc, qnin, file_name=None)¶

Write out a fort.20 formatted file to file_name

nflbn = total number of normal flow specified boundary nodes

Parameters:	ftiminc (numpy.ndarray of shape (nflbn,)) – time increment (secs) between consecutive sets of normal flow specified bounadry condition values qnin (numpy.ndarray of shape (k, nflbn)) – normal flow/unit width at specified nomarl flow node k

See also

ADCIRC Non-periodic Normal Flow Boundary Condition File

polyadcirc.pyADCIRC.output module¶

This module provides methods for retrieving data from ASCII ADCIRC formatted timeseries and non-timeseries data files and returning that data as numpy arrays.

polyadcirc.pyADCIRC.output.get_data_nts(kk, path, data, nts_data, file_names=['tinun.63'])¶

Retrieves data from a nontimeseries formatted files in path and adds data to nts_data

Parameters:	kk (int) – run number path (string) – RF_directory_* path data – domain nts_data (dict) – reference to dict() to store data to file_names (list) – list of ADCIRC output files to retrieve data from

polyadcirc.pyADCIRC.output.get_data_ts(kk, path, ts_data, time_obs, file_names=['fort.61'], timesteps=None, ihot=None)¶

Retrieves data from a timeseries formatted files in path and adds data to ts_data

Parameters:	kk (int) – run number path (string) – RF_directory_* path ts_data (dict) – reference to dict() to store data to time_obs (dict) – reference to dict() to store time data to file_names (list) – list of ADCIRC output files to ihot (int) – hotstart flag (0, 67, 68) timesteps (int) – number of timesteps to read

polyadcirc.pyADCIRC.output.get_nts_sr(path, data, file_name)¶

Retrieves data from a nontimeseries formatted file in path and adds data to nts_data

Parameters:	path (string) – RF_directory_* path data – domain file_name (string) – ADCIRC output file to retrieve data from
Return type:	numpy.ndarray
Returns:	array of dimensions (data.node_num,)

polyadcirc.pyADCIRC.output.get_ts_sr(path, file_name, get_time=False, timesteps=None, ihot=None)¶

Retrieves data from a timeseries formatted file in path and adds data to ts_data

Parameters:	path (string) – RF_directory_* path file_name (string) – ADCIRC output file to retrieve data from bool – flag for whether or not to record times of recordings timesteps (int) – number of timesteps to read ihot (int) – hotstart flag (0, 67, 68)
Return type:	numpy.ndarray
Returns:	array of dimensions (data.node_num,)

polyadcirc.pyADCIRC.plotADCIRC module¶

A set of functions for plotting data from runSet

polyadcirc.pyADCIRC.plotADCIRC.add_2d_axes_labels(fig=None, ics=1)¶

Add 2D axes labels for either cartesian or polar coordinates

Parameters:	fig (figure) – matplotlib.pyplot.figure object ics (int) – polar coordinate option (1 = cart coords, 2 = polar)

polyadcirc.pyADCIRC.plotADCIRC.basis_functions(domain, bv_array, path=None, save=True, show=False, ics=1, ext='.png', cmap=<matplotlib.colors.LinearSegmentedColormap object>)¶

Given a bv_array containing basis functions, plot them

Parameters:	domain – domain bv_array (:classnp.array`) – array of basis vectors based on land classification path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.bathymetry(domain, path=None, save=True, show=False, mesh=False, contour=False, ics=1, ext='.png', title=False)¶

Given a domain, plot the bathymetry

Parameters:	domain – domain path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots mesh (bool) – flag for whether or not to show mesh contour (bool) – use tripcolor() or tricontour() ics (int) – coordinate system (1 cartisian, 2 polar) ext (string) – file extesion

polyadcirc.pyADCIRC.plotADCIRC.colorbar(mappable=None)¶

Add a colorbar to the current figure/plot/subfigure/axes

Parameters:	mappable – See matplotlib

polyadcirc.pyADCIRC.plotADCIRC.field(domain, z, title, clim=None, path=None, save=True, show=False, ics=1, ext='.png', cmap=<matplotlib.colors.LinearSegmentedColormap object>)¶

Given a domain, plot the nodal value z

Parameters:	domain – domain z – numpy.ndarray title (string) – plot title clim – numpy.clim path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar coords) ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.get_Triangulation(domain, path=None, save=True, show=False, ics=1, ext='.png', title=False)¶

Parameters:	domain – domain path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – coordinate system (1 cartisian, 2 polar) ext (string) – file extesion
Return type:	matplotlib.tri.Triangulation
Returns:	triangulation of domain

polyadcirc.pyADCIRC.plotADCIRC.load_fig_gen_cmap()¶

Todo

Color map to match FigureGen

polyadcirc.pyADCIRC.plotADCIRC.mean_field(domain, points, bv_dict, path=None, save=True, show=False, ics=1, ext='.png')¶

Given a bv_dict a set of random points, plot the r_fields generated in random_manningsn.runSet.run_points

Parameters:

domain – domain points (numpy.ndarray) – weights for points at which the random domain was sampled bv_dict (list of dict) – list of basis vectors based on land classification path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar coords) ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.nts_contour(nts_data, domain, keys=None, points=None, path=None, save=True, show=False, ics=1, ext='.png')¶

Plot the non timeseries data in nts_data as a set of 2D contour plots. To plot only a subset of this data list which ADCIRC Output types to plot in keys, and which runs in points.

Note

This only applies to 1D nts data (irtype = 1)

Parameters:	nts_data (dict) – nts_data from runSet domain – domain keys (list) – list of types of ADCIRC output data to plot points (list) – list of runs to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.nts_line_data(nts_data, keys=None, path=None, save=True, show=False, ext='.png')¶

Plot the non timeseries data in data with points as the x axis. To plot only a subset of this data list which ADCIRC Output types to plot in keys.

Note

This only applies to 1D nts data (irtype = 1)

Parameters:	nts_data (dict) – nts_data from runSet keys (list) – list of types of ADCIRC output data to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.nts_pcolor(nts_data, domain, keys=None, points=None, path=None, save=True, show=False, ics=1, ext='.png')¶

Plot the non timeseries data in nts_data as a set of 2D color plots. To plot only a subset of this data list which ADCIRC Output types to plot in keys, and which runs in points.

Note

This only applies to 1D nts data (irtype = 1)

Parameters:

nts_data (:class:dict) – nts_data from :class:~polyadcirc.run_framework.random_manningsn.runSet domain – domain keys (list) – list of types of ADCIRC output data to plot points (list) – list of runs to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.random_fields(domain, points, bv_dict, path=None, save=True, show=False, ics=1, ext='.png', cmap=<matplotlib.colors.LinearSegmentedColormap object>)¶

Given a bv_dict a set of random points, plot the r_fields generated in run_points()

Parameters:

domain – domain points (numpy.ndarray) – weights for points at which the random domain was sampled bv_dict (list of dict) – list of basis vectors based on land classification path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar coords) ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.save_show(full_name, save, show, ext)¶

Save or show the current figure

Parameters:	full_name (string) – path to save the figure save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.station_data(ts_data, time_obs, keys=None, stations=None, path=None, save=True, show=False, ext='.png')¶

Plot the station data in ts_data with time_obs as the x axis. To plot only a subset of this data list which ADCIRC Output types to plot in keys.

Parameters:	ts_data (dict) – ts_data from runSet time_obs (dict) – time_obs from runSet keys (list) – list of types of ADCIRC output data to plot stations (dict) – dictonary of lists of stations to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.station_locations(domain, path=None, bathy=False, save=True, show=False, ics=1, ext='.png', station_markers=None)¶

Given a domain, plot the observation stations

Parameters:	domain – domain path (string or None) – directory to store plots bathy (bool) – flat for whether or not to show bathymetry save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – coordinate system (1 cartisian, 2 polar) ext (string) – file extesion

polyadcirc.pyADCIRC.plotADCIRC.ts_pcolor(ts_data, time_obs, domain, keys=None, points=None, path=None, save=True, show=False, ics=1, ext='.png')¶

Plot the timeseries data in ts_data as a series of 2D color plots. To plot only a subset of this data list which ADCIRC Output types to plot in keys and which runs in points.

Note

This only applies to 1D nts data (irtype = 1)

Parameters:

ts_data (dict) – ts_data from runSet time_obs (:class:dict) – time_obs from runSet domain – domain keys (list) – list of types of ADCIRC output data to plot points (list) – list of runs or points to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar) ext (string) – file extension

polyadcirc.pyADCIRC.plotADCIRC.ts_quiver(ts_data, time_obs, domain, keys=None, points=None, path=None, save=True, show=False, ics=1, ext='.png')¶

Plot the timeseries data in ts_data as a series of 2D quiver plots. To plot only a subset of this data list which ADCIRC Output types to plot in keys and which runs in points.

Note

This only applies to 2D nts data (irtype = 2)

Parameters:

ts_data (dict) – ts_data from runSet time_obs (dict) – time_obs from runSet domain – domain keys (list) – list of types of ADCIRC output data to plot points (list) – list of runs or points to plot path (string or None) – directory to store plots save (bool) – flag for whether or not to save plots show (bool) – flag for whether or not to show plots ics (int) – polar coordinate option (1 = cart coords, 2 = polar ext (string) – file extension

Todo

maybe add plt.streamplot, but this requires a regularly spaced grid and is therefore more expenseive to do

polyadcirc.pyADCIRC.post_management module¶

This module controls the automatic writing of in.post* files

polyadcirc.pyADCIRC.post_management.post_script_ALL(path)¶

Write out a bash scrip to run adcpost with in.postALL and and save it to path

Parameters:	path (string) – folder to save postALL.sh to

polyadcirc.pyADCIRC.post_management.post_script_n(path, n)¶

Write out a bash scrip to run adcpost with in.postn and save it to path

Parameters:	path (string) – folder to save postn.sh to

polyadcirc.pyADCIRC.post_management.post_script_sub(path)¶

Write out a bash scrip to run adcpost with in.postsub and and save it to path

Parameters:	path (string) – folder to save postsub.sh to

polyadcirc.pyADCIRC.post_management.write_ALL(path, hotfiles=False)¶

Write out a in.postALL file and save it to path

Parameters:	path (string) – folder to save in.postALL to hotfiles (bool) – flag whether or not to post process hot start files

polyadcirc.pyADCIRC.post_management.write_multi(path, nums, hotfiles=False)¶

Write out a in.postmulti file and save it to path

Parameters:	path (string) – folder to save in.postn to nums (list) – list of ADCPOST file type codes hotfiles (bool) – flag whether or not to post process hot start files

polyadcirc.pyADCIRC.post_management.write_n(path, n, hotfiles=False)¶

Write out a in.postn file and save it to path

Parameters:	path (string) – folder to save in.postn to n (int) – ADCPOST file type code hotfiles (bool) – flag whether or not to post process hot start files

polyadcirc.pyADCIRC.post_management.write_sub(path, hotfiles=False)¶

Write out a in.postsub file and save it to path

Parameters:	path (string) – folder to save in.postsub to hotfiles (bool) – flag whether or not to post process hot start files

polyadcirc.pyADCIRC.prep_management module¶

This module controls the automatic writing of in.prep* files

polyadcirc.pyADCIRC.prep_management.prep_script_12(path)¶

Write out a bash scrip to run adcprep with in.prep1 and in.prep2 and save it to path

Parameters:	path (string) – folder to save prep12.sh to

polyadcirc.pyADCIRC.prep_management.prep_script_n(path, n)¶

Write out a bash scrip to run adcprep with in.prepn and save it to path

Parameters:	path (string) – folder to save prepn.sh to

polyadcirc.pyADCIRC.prep_management.write_1(path, nprocs=12, nfile='fort.14')¶

Write out a in.prep1 file for nfile and save it to path

Parameters:	path (string) – folder to save in.prep1 to nprocs (int) – number of processors a single PADCIRC run will be run on nfile (string) – name of fort.14 formatted file

polyadcirc.pyADCIRC.prep_management.write_2(path, nprocs=12)¶

Write out a in.prep2 file for nfile and save it to path

Parameters:	path (string) – folder to save in.prep2 to nprocs (int) – number of processors a single PADCIRC run will be run on

polyadcirc.pyADCIRC.prep_management.write_5(path, nprocs=12, nfile='fort.13')¶

Write out a in.prep5 file for nfile and save it to path

Parameters:	path (string) – folder to save in.prep5 to nprocs (int) – number of processors a single PADCIRC run will be run on nfile (string) – name of fort.13 formatted file

polyadcirc.pyADCIRC.prep_management.write_n(path, n, nprocs=12, nfile=None)¶

Write out a in.prepn file for nfile and save it to path

Parameters:	path (string) – folder to save in.prepn to n (int) – number of the in.prepn file nprocs (int) – number of processors a single PADCIRC run will be run on nfile (string) – name of fort.nn formatted file

polyadcirc.pyADCIRC.volume module¶

This module contains methods used in calculating the volume of water present in an ADCIRC simulation.

polyadcirc.pyADCIRC.volume.element_volume(domain, element, elevation)¶

Calculates the volume of water contained an element with a given sea surface elevation at each of the nodes.

Parameters:	domain – domain element (array_like) – list of nodes defining an element elevation – eta, sea surface height (NOT WATER COLUMN HEIGHT)
Return type:	double
Returns:	volume

polyadcirc.pyADCIRC.volume.side(domain, element, side_num, elevation)¶

Calculates dot(x, n*A) where x is the barycenter, n is the normal vector to the surface defined by z and the element verticies, and A is the area of the surface defined by z and the element vertices.

Parameters:	domain – domain element (array_like) – list of nodes defining an element elevation – eta, sea surface height (NOT WATER COLUMN HEIGHT)
Return type:	double
Returns:	dot(x, n*A)

polyadcirc.pyADCIRC.volume.sub_volume(domain, elevation, elements)¶

Calculates the total volume of water contained in an ADCIRC simulation for a given set of elements with sea surface height given by elevation.

Parameters:	domain – domain elevation – eta, sea surface height (NOT WATER COLUMN HEIGHT) elements – list of element numbers to calcuate volumes for
Return type:	tuple
Returns:	total volume, element-wise volume

polyadcirc.pyADCIRC.volume.total_volume(domain, elevation)¶

Calculates the total volume of water contained in an ADCIRC simulation with sea surface height given by elevation.

Parameters:	domain – domain elevation – eta, sea surface height (NOT WATER COLUMN HEIGHT)
Return type:	tuple
Returns:	total volume, element-wise volume

polyadcirc.pyADCIRC.volume.triangle(domain, element, z, norm_dir=1.0)¶

Calculates dot(x, n*A) where x is the barycenter, n is the normal vector to the surface defined by z and the element verticies, and A is the area of the surface defined by z and the element vertices.

Parameters:	domain – domain element (array_like) – list of nodes defining an element z (numpy.ndarray) – z-coordinate relative to the geiod, z = eta OR z = -h norm_dir (double) – 1.0 up, -1.0 down, direction of the normal vector
Return type:	double
Returns:	dot(x, n*A)

Module contents¶

This subpackage contains

• the class pickleable;
• the module basic a set of classes for container objectd used by the run_framework;
• the modules fort13_management, fort14_management, and fort15_management, fort1920_management, a set of methods for manipulation and reading of ADCIRC fort.## files for use by the run_framework and pyGriddata modules;
• the module prep_management is used to generate input files to ADCPREP.
• plotADCIRC a set of functions for plotting simulation outputs
• post_management is used the generate input files to ADCPOST.