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Merge pull request #16 from FRAMverse/add/readme
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@Ty-WDFW
Ty-WDFW authored Apr 25, 2024
2 parents 68f61a1 + a8e3a55 commit 220e37a
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8 changes: 4 additions & 4 deletions R/compare_inputs.R
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Expand Up @@ -598,14 +598,14 @@ compare_runs <- function(fram_db, run_ids, tolerance = .01){
cli::cli_alert_success('No changes detected in fishery flag inputs')
}

cli::cli_h3('Checking for changes to fishery flags')
cli::cli_alert_info('detection tolerance set to: {scales::percent(tolerance)}')
cli::cli_h3('Checking for changes to fishery inputs')
cli::cli_alert_info('Detection tolerance set to: {scales::percent(tolerance)}')
fishery_inputs <- fram_db |> compare_fishery_inputs(run_ids, tolerance = tolerance)
if(nrow(fishery_inputs) > 0){
cli::cli_alert_info('Changes detected in fishery flag inputs, below is a table outlining them')
cli::cli_alert_info('Changes detected in fishery inputs, below is a table outlining them')
print(fishery_inputs, n=Inf)
} else {
cli::cli_alert_success('No changes detected in fishery flag inputs')
cli::cli_alert_success('No changes detected in fishery inputs')
}

cli::cli_h3('Checking for changes to stock fishery rate scalers')
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203 changes: 200 additions & 3 deletions README.md
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@@ -1,15 +1,212 @@
# framrsquared
<!-- badges: start -->

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![R-CMD-check](https://github.com/FRAMverse/framrsquared/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/FRAMverse/framrsquared/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

# framrsquared
## Overview

R Package interfacing with the FRAM databases
framrsquared is a library with a focus on easing the burden of working in the FRAM database by providing convenient methods to import tables into R, and producing similar analyses as the FRAM executable while extending it some circumstances.

# Installation
## Installation

``` r
devtools::install_github("FRAMverse/framrsquared")

# Alternatively
remotes::install_github("FRAMverse/framrsquared")
```

## Connecting to a FRAM database
```r
library(framrsquared)

fram_db <- connect_fram_db("<path_to_database>")

✔ Successfully connected to FRAM database
Database Species: COHO
Run Count: 34
Last Run Date: Wed, April 10, 2024 05:42 PM
Last Run Name: bc-Coho2425
Last Modify Date: Wed, April 10, 2024 05:41 PM

```

## Importing FRAM tables into R
Imported tables from the FRAM database are automatically converted to [tibbles](https://github.com/tidyverse/tibble) and column names are converted to snakecase.
```r
time_step <- fram_db |>
fetch_table('TimeStep')

time_step

# A tibble: 9 × 5
species version_number time_step_id time_step_name time_step_title
<chr> <int> <int> <chr> <chr>
1 COHO 1 1 Jan-Jun January - June
2 COHO 1 2 July July
3 COHO 1 3 August August
4 COHO 1 4 Septmbr September
5 COHO 1 5 Oct-Dec October - December
6 CHINOOK 1 1 Oct-Apr-1 October-April-1
7 CHINOOK 1 2 May-June May - June
8 CHINOOK 1 3 July-Sept July - September
9 CHINOOK 1 4 Oct-Apr-2 October-April-2
```

## Dynamic and Additive Fisheries Filtering
Filtering functions in this package are agnostic to species and designed to retain the same syntax between Chinook FRAM databases and coho FRAM databases.

State level filters:
- `filter_wa()` Filters fisheries to Washington
- `filter_bc()` Filters fisheries to Canada
- `filter_ca()` Filters fisheries to California
- `filter_or()` Filters fisheries to Oregon
- `filter_or()` Filters fisheries to Alaska

Gear level filters:
- `filter_net()` Filters to net fisheries
- `filter_sport()` Filters to sport fisheries

Regional level filters;
- `filter_marine()` Filters to marine fisheries
- `filter_coast()` Filters to coastal fisheries
- `filter_puget_sound()` Filters to Puget Sound Fisheries

```r
# coho database
fram_db_coho <- connect_fram_db('<path_to_coho_database>')

fram_db_coho |>
fetch_table('Fishery') |>
filter_marine() |>
filter_puget_sound() |>
filter_sport()

# A tibble: 10 × 5
species version_number fishery_id fishery_name fishery_title
<chr> <int> <int> <chr> <chr>
1 COHO 1 91 Area 5 Spt WA Area 5 Sport (Sekiu)
2 COHO 1 92 Area 6 Spt WA Area 6 Sport (Port Angeles)
3 COHO 1 93 Area 7 Spt WA Area 7 Sport (San Juan Islands)
4 COHO 1 106 Ar 8-1 Spt WA Area 8.1 Sport (Skagit Bay)
5 COHO 1 107 Area 9 Spt WA Area 9 Sport (Admirality Inlet)
6 COHO 1 115 Ar 8-2 Spt WA Area 8.2 Sport (Everett)
7 COHO 1 118 Ar 10 Spt WA Area 10 Sport (Seattle)
8 COHO 1 129 Ar 11 Spt WA Area 11 Sport (Tacoma)
9 COHO 1 136 Ar 13 Spt WAArea 13 Marine Sport
10 COHO 1 152 Ar 12 Spt Area 12 Marine Sport

# chinook database
fram_db_chinook <- connect_fram_db('<path_to_chinook_database>')

fram_db_chinook |>
fetch_table('Fishery') |>
filter_marine() |>
filter_puget_sound() |>
filter_sport()

# A tibble: 12 × 5
species version_number fishery_id fishery_name fishery_title
<chr> <int> <int> <chr> <chr>
1 CHINOOK 1 56 A 10 Sport NT Area 10 Sport
2 CHINOOK 1 57 A 11 Sport NT Area 11 Sport
3 CHINOOK 1 60 A 10A Sprt NT Area 10A Sport
4 CHINOOK 1 62 A 10E Sprt NT Area 10E Sport
5 CHINOOK 1 64 A 12 Sport NT Area 12 Sport
6 CHINOOK 1 67 A 13 Sport NT Area 13 Sport
7 CHINOOK 1 36 Ar 7 Sport NT Area 7 Sport
8 CHINOOK 1 42 Ar 5 Sport NT Area 5 Sport
9 CHINOOK 1 45 Ar 8-1 Spt NT Area 8-1 Sport
10 CHINOOK 1 48 Area8D Spt NT Area 8D Sport
11 CHINOOK 1 53 Ar 9 Sport NT Area 9 Sport
12 CHINOOK 1 54 Ar 6 Sport NT Area 6 Sport

# disconnect databases
disconnect_fram_db(fram_db_coho)
✔ Successfully disconnected from FRAM database (fram_db_coho)

disconnect_fram_db(fram_db_chinook)
✔ Successfully disconnected from FRAM database (fram_db_chinook)
```
## Auditing Tools
This family of functions compares two different runs, returning tibbles of detected differences.

Input specific:
- `compare_fishery_inputs()` Compares fishery inputs `compare_fishery_input_flags()` is a variant to compare flags

- `compare_recruits()` Compares recruits between two runs
- `compare_non_retention_inputs()` Compares non-retention inputs `compare_non_retention_input_flags()` is a variant to compare flags
- `compare_stock_fishery_rate_scalers()` Compares the stock fishery rate scalers

Reporting to console:
- `compare_runs()` Generates a report to the console with all of the outputs from the functions above
```r
fram_db <- connect_fram_db('<path_to_coho_database>')

fram_db |>
compare_runs(c(56:57))

── Comparing run bc-Coho2423_STT_NOF to bc-Coho2424_NOF ─────────────────────────────────────────────────────────────────────────────────
ℹ bc-Coho2423_STT_NOF was run at 2024-04-09 10:41:30 PM, bc-Coho2424_NOF was run at 2024-04-10 12:40:07 PM

── Non-Retention Inputs ──

── Checking for changes in non-retention flagging
ℹ Changes detected in non-retention flagging, below is a table outlining them
# A tibble: 4 × 5
fishery_id time_step fishery_name `bc-Coho2423_STT_NOF` `bc-Coho2424_NOF`
<int> <int> <chr> <int> <int>
1 154 4 1212BNetTR 1 NA
2 36 4 Area2TrlTR NA 1
3 39 4 Area3TrlTR NA 1
4 43 4 A4/4BTrlTR NA 1

── Checking for changes in non-retention inputs
ℹ Changes detected in non-retention inputs, below is a table outlining them
# A tibble: 7 × 6
fishery_id time_step name fishery_name `bc-Coho2423_STT_NOF` `bc-Coho2424_NOF`
<int> <int> <chr> <chr> <dbl> <dbl>
1 154 3 cnr_input1 1212BNetTR 71.4 36.7
2 154 4 cnr_input1 1212BNetTR 28.4 0
3 154 5 cnr_input1 1212BNetTR 7 8
4 156 5 cnr_input1 A9-9ANetTR 15 18
5 36 4 cnr_input1 Area2TrlTR 0 52
6 39 4 cnr_input1 Area3TrlTR 0 52
7 43 4 cnr_input1 A4/4BTrlTR 0 52

── Recruit Inputs ──

── Checking for changes to recruits
✔ No changes detected in recruit inputs

── Fishery Inputs ──

── Checking for changes to fishery flags
✔ No changes detected in fishery flag inputs

── Checking for changes to fishery inputs
ℹ Detection tolerance set to: 1%
ℹ Changes detected in fishery inputs, below is a table outlining them
# A tibble: 12 × 6
fishery_id fishery_name time_step name `bc-Coho2423_STT_NOF` `bc-Coho2424_NOF`
<int> <chr> <int> <chr> <dbl> <dbl>
1 47 WlpaBT Net 4 quota 26427 25411
2 48 GryHbr Spt 4 quota 2489 2285
3 49 SGryHb Spt 5 quota 79 73
4 50 GryHbr Net 5 quota 5873 4751
5 51 Hump R Spt 5 quota 1551 1505
6 52 LwCheh Net 5 quota 24219 26299
7 54 Chehal Spt 5 quota 14723 14553
8 55 Hump R Net 5 quota 4485 4372
9 56 UpCheh Net 5 quota 4267 3844
10 63 Quin R Net 4 quota 10166 9860
11 68 Queets Net 4 quota 7486 8079
12 68 Queets Net 5 quota 2358 170

── Checking for changes to stock fishery rate scalers
✔ No changes detected in fishery inputs

```

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