Package index • framrsquared

Connecting to FRAM database

Functions to connect a disconnect to a FRAM database

connect_fram_db(): This is a connection object to a FRAM database. Returns a list used throughout the rest of this package which carries meta data.

disconnect_fram_db(): Safely disconnect from FRAM database

Importing FRAM tables

Functions to import a FRAM database table into R

fetch_table(): Fetches a complete table from a FRAM database. Returns a cleaned tibble.

fetch_table_bkchin(): Safely fetch Chinook BackwardsFRAM table

FRAM filtering

Functions to filter FRAM tables by fishery

filter_ak(): Filters a dataframe to Alaska fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_bc(): Filters a dataframe to Canadian (BC) fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_ca(): Filters a dataframe to California fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_coast(): Filters a dataframe to Coastal fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_flag(): NA's all the information in the FisheryScalers that's not being used e.g Flag 1 only NS Scalers will be returned

filter_marine(): Filters a dataframe to marine fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_net(): Filters a dataframe to net fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_or(): Filters a dataframe to Oregon fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_puget_sound(): Filters a dataframe to Puget Sound fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_sport(): Filters a dataframe to sport fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

filter_wa(): Filters a dataframe to Washington State fisheries. Will automatically detect whether it's working with a Chinook or Coho dataset if the tables were generated within this package. Requires a fishery_id column name.

Comparing FRAM runs

Functions that compare two FRAM runs within the same database

compare_databases(): Compare tables in two equivalent FRAM databases

compare_fishery_input_flags(): Compares the fishery flags of two runs

compare_fishery_inputs(): Compares the fishery inputs of two runs

compare_inputs(): Generates a dataframe that compares fishery scalers table for two runs identified by run_id's

compare_inputs_chart(): Generates a heat map of changed between two run inputs. Can be a very busy chart if not filtered down. Consider using a filter.

compare_non_retention_input_flags(): Compares the non retention flags of two runs

compare_non_retention_inputs(): Compares the non retention inputs of two runs

compare_recruits(): Compares the recruit scalers of two runs

compare_runs(): Generates a report to the console of changes to inputs between two runs

compare_stock_fishery_rate_scalers(): Compares the stock fishery rate scalers of two runs

FRAM Screen Reports

Functions that replicate FRAM UI screen reports

msf_encounters(): Produces the MSF screen report numbers for encounters. Returns different format depending database.

msf_encounters_chinook_(): Returns a tibble matching the MSF screen report encounters for Chinook. This is specific for Chinook and in most cases msf_encounters() is preferable.

msf_encounters_coho_(): Returns a tibble matching the MSF screen report encounters for Coho This is specific for Coho and in most cases msf_encounters() is preferable.

msf_landed_catch(): Produces the MSF screen report numbers for landed catch. Returns different format depending database.

msf_landed_catch_chinook_(): Returns a tibble matching the MSF screen report landed catch for Chinook. This is specific for Chinook and in most cases msf_landed_catch() is preferable.

msf_landed_catch_coho_(): Returns a tibble matching the MSF screen report landed catch for Coho This is specific for Coho and in most cases msf_landed_catch() is preferable.

msf_mortalities(): Produces the MSF screen report numbers for mortalities. Returns different format depending database.

msf_mortalities_chinook_(): Returns a tibble matching the MSF screen report mortalities for Chinook. This is specific for Chinook and in most cases msf_mortalities() is preferable.

msf_mortalities_coho_(): Returns a tibble matching the MSF screen report mortalities for Coho This is specific for Coho and in most cases msf_mortalities() is preferable.

population_statistics(): Returns a tibble matching the Population Statistics screen.

fishery_mortality(): Returns a tibble matching the Fishery Mortality screen.

stock_mortality(): Returns a tibble matching the Fishery Mortality screen.

Stock impact visualizations

Functions that visualize impacts of stocks in fisheries

plot_stock_mortality(): Creates an ordered bar chart with the top number of mortalities per fishery.

plot_stock_mortality_time_step(): Creates an ordered bar chart with the top number of mortalities per fishery and time step.

make_impacts_per_catch_heatmap(): Make plots to show the amount of landed catch_per_impact

Initializing R FRAM Projects

Creates a standardized workspace for fram related R projects

initialize_project(): Initializes a FRAM project

fetch_quarto_templates(): Creates quarto template files

Database altering functions

Functions that alter FRAM database tables, use with caution

copy_fishery_scalers(): Experimental copying scaler inputs from one run to another DANGEROUS

change_run_id(): Changes a run's ID number in a FRAM database

remove_run(): Removes a run in a FRAM database

Week calculations

Functions calculate a week number

management_week(): Vectorized approach to calculating the management week, returns an integer

statistical_week(): Vectorized approach to calculating the statistical week, returns an integer

Validations

Functions that validate FRAM data

validate_fram_db(): Convenience function to check fram_db input

validate_run_id(): Convenience function to check run_id input

Terminal Runs

Functions that unpack the TRuns table in the FRAM database

truns_fisheries(): Returns a dataframe with fisheries defined by the TRuns report driver

truns_stocks(): Returns a dataframe with stocks defined by the TRuns report driver

Post-season FRAM

Functions that focus on post-season runs and backwards FRAM

bkfram_checks_coho(): Performs error checks of a backwards FRAM run Returns nested tibble with diagnostics

post_season_abundance(): Generates post-season January age 3 abundances by stock from post-season databases. Used for forecasting.

Describing the FRAM Database

Functions that describe the current FRAM database

fram_clean_tables(): Cleans the names of FRAM tables and coverts to a tibble

fram_database_species(): Identifies the FRAM database species focus - Chinook or Coho

fram_database_type(): Identifies the FRAM database type - Full or Transfer

get_run_ids(): Gets all run_ids of FRAM database

find_tables_by_column_(): Finds tables that contain a specific column name

provide_table_names(): List names of FRAM table

run_info(): Provides a print out of Run ID information

Data checking

Functions that provide checks for the current data

addstock_check(): Check FRAM database after adding new stock

bkfram_checks_coho(): Performs error checks of a backwards FRAM run Returns nested tibble with diagnostics

error_check_code(): Check code for common errors

stock_age_checker(): Helper function to check that all stock x age combinations are present

stock_check_helper(): Helper function to check that stock id make sense

frs_stylecheck_assignment() frs_stylecheck_snakecase(): Framrsquared style guide

Stock summaries

Functions that descibe the fate of a stock

stock_fate() experimental: Summarizes the three true outcomes of a stocks abundance, where it dies to fishery related mortality, natural mortality, or reaches some sort of escapement. When run against the coho database spawning escapement will be displayed, when run against the Chinook database escapement to the river will be dislpayed along with recruits to the next year 'age_up'

stock_fate_chinook() experimental: Chinook flavor of the stock fate function

stock_fate_coho() experimental: Coho flavor of the stock fate function

Misc.

Miscellaneous functions

add_flag_text(): Adds a column with a text version of flags for either non-retention or fishery scalers

cohort_abundance() experimental: Pulls the starting cohorts from the database, this is stored in the StockRecruit table, but can be wrong. It's best just to multiply the Stock Recruit Scalar by the base period abundance

aeq_mortality(): Extract AEQ mortality from Chinook FRAM database. Refactored and stripped down from the framr package written by Dan Auerbach. https://github.com/FRAMverse/framr/

coho_mark_rates() experimental: Returns a tibble displaying predicted FRAMencounter mark rates by fishery, fishery type, and time-step.

input_summary_(): Generates an input summary based on a FisheryScalers dataframe. Probably end up streamlining / revising this.

mortality_scalers(): Guestimate the impact on a particular stock by multiplying its mortalities by the stock_mortality_ratio produced by these functions.

msp_mortality(): Expand Chinook mortality table using Model-Stock Proportion

NR_flag_translate(): Provides English translation of numeric non-retention flags

scalers_flag_translate(): Provides English translation of numeric scalers flags

stock_id_comp(): Helper function to check that stock id exist in the Stock database

welcome(): Welcome message, summarizing database information