natcap.invest.finfish_aquaculture package

Submodules

natcap.invest.finfish_aquaculture.finfish_aquaculture module

inVEST finfish aquaculture filehandler for biophysical and valuation data

natcap.invest.finfish_aquaculture.finfish_aquaculture.execute(args)

Finfish Aquaculture.

This function will take care of preparing files passed into the finfish aquaculture model. It will handle all files/inputs associated with biophysical and valuation calculations and manipulations. It will create objects to be passed to the aquaculture_core.py module. It may write log, warning, or error messages to stdout.

Parameters:
  • workspace_dir (string) – The directory in which to place all result files.
  • ff_farm_loc (string) – URI that points to a shape file of fishery locations
  • farm_ID (string) – column heading used to describe individual farms. Used to link GIS location data to later inputs.
  • g_param_a (float) – Growth parameter alpha, used in modeling fish growth, should be an int or float.
  • g_param_b (float) – Growth parameter beta, used in modeling fish growth, should be an int or float.
  • g_param_tau (float) – Growth parameter tau, used in modeling fish growth, should be an int or float
  • (boolean) (use_uncertainty) –
  • g_param_a_sd (float) – (description)
  • g_param_b_sd (float) – (description)
  • num_monte_carlo_runs (int) –
  • water_temp_tbl (string) – URI to a CSV table where daily water temperature values are stored from one year
  • farm_op_tbl (string) – URI to CSV table of static variables for calculations
  • outplant_buffer (int) – This value will allow the outplanting start day to be flexible plus or minus the number of days specified here.
  • do_valuation (boolean) – Boolean that indicates whether or not valuation should be performed on the aquaculture model
  • p_per_kg (float) – Market price per kilogram of processed fish
  • frac_p (float) – Fraction of market price that accounts for costs rather than profit
  • discount (float) – Daily market discount rate

Example Args Dictionary:

{
    'workspace_dir': 'path/to/workspace_dir',
    'ff_farm_loc': 'path/to/shapefile',
    'farm_ID': 'FarmID'
    'g_param_a': 0.038,
    'g_param_b': 0.6667,
    'g_param_tau': 0.08,
    'use_uncertainty': True,
    'g_param_a_sd': 0.005,
    'g_param_b_sd': 0.05,
    'num_monte_carlo_runs': 1000,
    'water_temp_tbl': 'path/to/water_temp_tbl',
    'farm_op_tbl': 'path/to/farm_op_tbl',
    'outplant_buffer': 3,
    'do_valuation': True,
    'p_per_kg': 2.25,
    'frac_p': 0.3,
    'discount': 0.000192,
}
natcap.invest.finfish_aquaculture.finfish_aquaculture.format_ops_table(op_path, farm_ID, ff_aqua_args)

Takes in the path to the operating parameters table as well as the keyword to look for to identify the farm number to go with the parameters, and outputs a 2D dictionary that contains all parameters by farm and description. The outer key is farm number, and the inner key is a string description of the parameter.

Input:

op_path: URI to CSV table of static variables for calculations farm_ID: The string to look for in order to identify the column in

which the farm numbers are stored. That column data will become the keys for the dictionary output.
ff_aqua_args: Dictionary of arguments being created in order to be
passed to the aquaculture core function.
Output:
ff_aqua_args[‘farm_op_dict’]: A dictionary that is built up to store
the static parameters for the aquaculture model run. This is a 2D dictionary, where the outer key is the farm ID number, and the inner keys are strings of parameter names.

Returns nothing.

natcap.invest.finfish_aquaculture.finfish_aquaculture.format_temp_table(temp_path, ff_aqua_args)

This function is doing much the same thing as format_ops_table- it takes in information from a temperature table, and is formatting it into a 2D dictionary as an output.

Input:
temp_path: URI to a CSV file containing temperature data for 365 days
for the farms on which we will look at growth cycles.
ff_aqua_args: Dictionary of arguments that we are building up in order
to pass it to the aquaculture core module.
Output:
ff_aqua_args[‘water_temp_dict’]: A 2D dictionary containing temperature
data for 365 days. The outer keys are days of the year from 0 to 364 (we need to be able to check the day modulo 365) which we manually shift down by 1, and the inner keys are farm ID numbers.

Returns nothing.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core module

Implementation of the aquaculture calculations, and subsequent outputs. This will pull from data passed in by finfish_aquaculture.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.calc_farm_cycles(outplant_buffer, a, b, tau, water_temp_dict, farm_op_dict, dur)
Input:
outplant_buffer: The number of days surrounding the outplant day during
which the fish growth cycle can still be started.
a: Growth parameter alpha. Float used as a scaler in the fish growth
equation.
b: Growth paramater beta. Float used as an exponential multiplier in
the fish growth equation.
water_temp_dict: 2D dictionary which contains temperature values for
farms. The outer keys are calendar days as strings, and the inner are farm numbers as strings.
farm_op_dict: 2D dictionary which contains individual operating
parameters for each farm. The outer key is farm number as a string, and the inner is string descriptors of each parameter.
dur: Float which describes the length for the growth simulation to run
in years.

Returns cycle_history where:

cycle_history: Dictionary which contains mappings from farms to a

history of growth for each cycle completed on that farm. These entries are formatted as follows...

Farm->List of Type (day of outplanting,day of harvest, fish weight
(grams))
natcap.invest.finfish_aquaculture.finfish_aquaculture_core.calc_hrv_weight(farm_op_dict, frac, mort, cycle_history)
Input:
farm_op_dict: 2D dictionary which contains individual operating
parameters for each farm. The outer key is farm number as a string, and the inner is string descriptors of each parameter.
frac: A float representing the fraction of the fish that remains after
processing.
mort: A float referring to the daily mortality rate of fishes on an
aquaculture farm.
cycle_history: Farm->List of Type (day of outplanting,
day of harvest, fish weight (grams))
Returns a tuple (curr_cycle_totals,indiv_tpw_totals) where:
curr_cycle_totals_: dictionary which will hold a mapping from every
farm (as identified by farm_ID) to the total processed weight of each farm
indiv_tpw_totals: dictionary which will hold a farm->list mapping,
where the list holds the individual tpw for all cycles that the farm completed
natcap.invest.finfish_aquaculture.finfish_aquaculture_core.compute_uncertainty_data(args, output_dir)

Does uncertainty analysis via a Monte Carlo simulation.

Returns a tuple with two 2D dicts. -a dict containing relative file paths to produced histograms -a dict containining statistical results (mean and std deviation) Each dict has farm IDs as outer keys, and result types (e.g. ‘value’, ‘weight’, and ‘cycles’) as inner keys.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.create_HTML_table(output_dir, args, cycle_history, sum_hrv_weight, hrv_weight, farms_npv, value_history, histogram_paths, uncertainty_stats)
Inputs:
output_dir: The directory in which we will be creating our .html file
output.
cycle_history: dictionary mapping farm ID->list of tuples, each of
which contains 3 things- (day of outplanting, day of harvest,
harvest weight of a single fish in grams)
sum_hrv_weight: dictionary which holds a mapping from farm ID->total
processed weight of each farm
hrv_weight: dictionary which holds a farm->list mapping, where the list
holds the individual tpw for all cycles that the farm completed
do_valuation: boolean variable that says whether or not valuation is
desired
farms_npv: dictionary with a farm-> float mapping, where each float is
the net processed value of the fish processed on that farm, in $1000s of dollars.
value_history: dictionary which holds a farm->list mapping, where the
list holds tuples containing (Net Revenue, Net Present Value) for each cycle completed by that farm
Output:
HTML file: contains 3 tables that summarize inputs and outputs for the

duration of the model. - Input Table: Farm Operations provided data, including Farm ID #,

Cycle Number, weight of fish at start, weight of fish at harvest, number of fish in farm, start day for growing, and length of fallowing period
  • Output Table 1: Farm Harvesting data, including a summary table

    for each harvest cycle of each farm. Will show Farm ID, cycle number, days since outplanting date, harvested weight, net revenue, outplant day, and year.

  • Output Table 2: Model outputs for each farm, including Farm ID,

    net present value, number of completed harvest cycles, and total volume harvested.

Returns nothing.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.do_monte_carlo_simulation(args)

Performs a Monte Carlo simulation and returns the results.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.execute(args)

‘ Runs the biophysical and valuation parts of the finfish aquaculture model. This will output: 1. a shape file showing farm locations w/ addition of # of harvest cycles,

total processed weight at that farm, and if valuation is true, total discounted net revenue at each farm location.
  1. Three HTML tables summarizing all model I/O- summary of user-provided

    data, summary of each harvest cycle, and summary of the outputs/farm

  2. A .txt file that is named according to the date and time the model is

    run, which lists the values used during that run

Data in args should include the following: –Biophysical Arguments– args: a python dictionary containing the following data: args[‘workspace_dir’]- The directory in which to place all result files. args[‘ff_farm_file’]- An open shape file containing the locations of

individual fisheries
args[‘farm_ID’]- column heading used to describe individual farms. Used to
link GIS location data to later inputs.
args[‘g_param_a’]- Growth parameter alpha, used in modeling fish growth,
should be int or a float.
args[‘g_param_b’]- Growth parameter beta, used in modeling fish growth,
should be int or a float.
args[‘water_temp_dict’]- A dictionary which links a specific date to the

farm numbers, and their temperature values on that day. (Note: in this case, the outer keys 1 and 2 are calendar days out of 365, starting with January 1 (day 0), and the inner 1, 2, and 3 are farm numbers.)

Format: {‘0’: ‘{‘1’: ‘8.447, ‘2’: ‘8.447’, ‘3’:‘8.947’, ...}’ ,
‘1’: ‘{‘1’: ‘8.406, ‘2’: ‘8.406’, ‘3’:‘8.906’, ...}’ ,

. . . . . . . . . }

args[‘farm_op_dict’]- Dictionary which links a specific farm ID # to

another dictionary containing operating parameters mapped to their value for that particular farm (Note: in this case, the 1 and 2 are farm ID’s, not dates out of 365.)

Format: {‘1’: ‘{‘Wt of Fish’: ‘0.06’, ‘Tar Weight’: ‘5.4’, ...}’,
‘2’: ‘{‘Wt of Fish’: ‘0.06’, ‘Tar Weight’: ‘5.4’, ...}’, . . . . . . . . . }
args[‘frac_post_process’]- the fraction of edible fish left after
processing is done to remove undesirable parts
args[‘mort_rate_daily’]- mortality rate among fish in a year, divided by
365

args[‘duration’]- duration of the simulation, in years args[‘outplant_buffer’] - This value will allow the outplant start day to

be flexible plus or minus the number of days specified here.

–Valuation arguments– args[‘do_valuation’]- boolean indicating whether or not to run the

valuation process

args[‘p_per_kg’]: Market price per kilogram of processed fish args[‘frac_p’]: Fraction of market price that accounts for costs rather

than profit

args[‘discount’]: Daily market discount rate

returns nothing

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.make_histograms(farm, results, output_dir, total_num_runs)

Makes a histogram for the given farm and data.

Returns a dict mapping type (e.g. ‘value’, ‘weight’) to the relative file path for the respective histogram.

natcap.invest.finfish_aquaculture.finfish_aquaculture_core.valuation(price_per_kg, frac_mrkt_price, discount, hrv_weight, cycle_history)

This performs the valuation calculations, and returns tuple containing a dictionary with a farm-> float mapping, where each float is the net processed value of the fish processed on that farm, in $1000s of dollars, and a dictionary containing a farm-> list mapping, where each entry in the list is a tuple of (Net Revenue, Net Present Value) for every cycle on that farm.

Inputs:
price_per_kg: Float representing the price per kilogram of finfish for
valuation purposes.
frac_mrkt_price: Float that represents the fraction of market price
that is attributable to costs.

discount: Float that is the daily market discount rate. cycle_hisory: Farm->List of Type (day of outplanting,

day of harvest, fish weight (grams))

hrv_weight: Farm->List of TPW for each cycle (kilograms)

Returns a tuple (val_history, valuations):
val_history: dictionary which will hold a farm->list mapping, where the
list holds tuples containing (Net Revenue, Net Present Value) for each cycle completed by that farm
valuations: dictionary with a farm-> float mapping, where each float is
the net processed value of the fish processed on that farm

Module contents