Package 'cs9example'

Declaration of environments that can be used globally

Description

cs9example creates global empty, and fills it when the package loads. It holds two things every task needs. global$border is the Norwegian border year the package is configured for. global$ss is a cs9::SurveillanceSystem_v9 object with every database table and every task already registered.

Usage

global

See Also

cs9::SurveillanceSystem_v9 for the class global$ss is an instance of, and make_skeleton_date() for the skeleton builder the tasks use. cs9example has no vignettes of its own; the framework is documented in the cs9 package.

Examples

# The border year, set when the package loads.
global$border

# The two tables and the three tasks the package registers.
names(global$ss$tables)
names(global$ss$tasks)

---

Create Date-Based Data Skeleton

Description

Creates a data skeleton with complete date sequences and location codes for the geographic granularities you specify.

Usage

make_skeleton_date(
  date_min,
  date_max,
  granularity_geo,
  location_reference = csdata::nor_locations_names()
)

Arguments

date_min	Start date (Date or character in YYYY-MM-DD format)
date_max	End date (Date or character in YYYY-MM-DD format)
granularity_geo	Vector of granularity_geo values to include
location_reference	Location reference data, defaults to csdata::nor_locations_names()

Value

data.table with complete skeleton

See Also

weather_clean_data_action(), the task action that starts from this skeleton, and csdata::nor_locations_names() for the default location reference. cs9example has no vignettes of its own; the framework is documented in the cs9 package.

Other skeleton builders: make_skeleton_isoyearweek()

Examples

# Every county, every day of the first week of 2024, with no data merged in
# yet: 15 counties x 7 days.
skeleton <- make_skeleton_date(
  date_min = "2024-01-01",
  date_max = "2024-01-07",
  granularity_geo = "county"
)
nrow(skeleton)
head(skeleton)

---

Create ISO Year-Week Data Skeleton

Description

Creates a data skeleton with complete ISO year-week sequences and location codes for the geographic granularities you specify.

Usage

make_skeleton_isoyearweek(
  isoyearweek_min,
  isoyearweek_max,
  granularity_geo,
  location_reference = csdata::nor_locations_names()
)

Arguments

isoyearweek_min	Start ISO year-week (character in YYYY-WW format)
isoyearweek_max	End ISO year-week (character in YYYY-WW format)
granularity_geo	Vector of granularity_geo values to include
location_reference	Location reference data, defaults to csdata::nor_locations_names()

Value

data.table with complete skeleton

See Also

make_skeleton_date() for the daily equivalent, and csdata::nor_locations_names() for the default location reference. cs9example has no vignettes of its own; the framework is documented in the cs9 package.

Other skeleton builders: make_skeleton_date()

Examples

# Every county, the first three ISO weeks of 2024: 15 counties x 3 weeks.
skeleton <- make_skeleton_isoyearweek(
  isoyearweek_min = "2024-01",
  isoyearweek_max = "2024-03",
  granularity_geo = "county"
)
nrow(skeleton)
head(skeleton)

---

Set global definitions

Description

Set global definitions

Usage

set_definitions()

---

weather_clean_data (action)

Description

Lays out a complete municipality-by-date skeleton with make_skeleton_date(). Merges the raw weather onto that skeleton. Aggregates it up to county and to nation. Aggregates the whole lot up again to ISO year-week. The action formats both granularities as csfmt_rts_data_v2, stacks them, and writes them to anon_example_weather_data. The write replaces whatever was there.

Usage

weather_clean_data_action(data, argset, tables)

Arguments

data	Data
argset	Argset
tables	DB tables

See Also

weather_clean_data_data_selector(), which produces this action's data argument, and make_skeleton_date() for the skeleton it starts from. cs9example has no vignettes of its own; how cs9 pairs an action with a data selector is documented in cs9::SurveillanceSystem_v9.

Other cs9 task actions: weather_download_and_import_rawdata_action(), weather_export_plots_action()

Examples

## Not run: 
# Needs a live cs9 PostgreSQL database: the action ends by dropping every row
# of anon_example_weather_data and inserting the cleaned data in its place.
global$ss$run_task("weather_clean_data")

## End(Not run)

---

weather_clean_data (data selector)

Description

Pulls the daily, municipality-level, total-age, total-sex rows out of anon_example_weather_rawdata. Returns them under the name date_municip, ordered by location and date.

Usage

weather_clean_data_data_selector(argset, tables)

Arguments

argset	Argset
tables	DB tables

Value

A named list with one element, date_municip: a data.table of granularity_time, location_code, date, temp_max, temp_min and precip.

See Also

weather_clean_data_action(), which consumes this list, and cs9::mandatory_db_filter() for the filter it applies. cs9example has no vignettes of its own; how cs9 pairs a data selector with an action is documented in cs9::SurveillanceSystem_v9.

Other cs9 task data selectors: weather_download_and_import_rawdata_data_selector(), weather_export_plots_data_selector()

Examples

## Not run: 
# Needs a live cs9 PostgreSQL database: it reads the
# anon_example_weather_rawdata table.
weather_clean_data_data_selector(
  argset = global$ss$shortcut_get_argset("weather_clean_data"),
  tables = global$ss$shortcut_get_tables("weather_clean_data")
)

## End(Not run)

---

weather_download_and_import_rawdata (action)

Description

Keeps the 00, 06, 12 and 18 o'clock timepoints of the forecast that weather_download_and_import_rawdata_data_selector() returned. Reduces them to one row per date: maximum air temperature, minimum air temperature and total precipitation. Upserts those rows into anon_example_weather_rawdata.

Usage

weather_download_and_import_rawdata_action(data, argset, tables)

Arguments

data	Data
argset	Argset
tables	DB tables

See Also

weather_download_and_import_rawdata_data_selector(), which produces this action's data argument. cs9example has no vignettes of its own; how cs9 pairs an action with a data selector is documented in cs9::SurveillanceSystem_v9.

Other cs9 task actions: weather_clean_data_action(), weather_export_plots_action()

Examples

## Not run: 
# Needs a live cs9 PostgreSQL database: the last thing the action does is
# upsert into the anon_example_weather_rawdata table.
global$ss$run_task("weather_download_and_import_rawdata")

## End(Not run)

---

weather_download_and_import_rawdata (data selector)

Description

Takes the mean latitude and longitude of the municipality named in argset$location_code. Downloads the MET Norway location forecast for that point. Returns it under the name data.

Usage

weather_download_and_import_rawdata_data_selector(argset, tables)

Arguments

argset	Argset
tables	DB tables

Value

A named list with one element, data: the parsed forecast.

See Also

weather_download_and_import_rawdata_action(), which consumes this list. cs9example has no vignettes of its own; how cs9 pairs a data selector with an action is documented in cs9::SurveillanceSystem_v9.

Other cs9 task data selectors: weather_clean_data_data_selector(), weather_export_plots_data_selector()

Examples

## Not run: 
# Needs internet access to api.met.no, and the csmaps package for the
# municipality's coordinates.
weather_download_and_import_rawdata_data_selector(
  argset = list(location_code = "municip_nor0301"),
  tables = NULL
)

## End(Not run)

---

weather_export_plots (action)

Description

Creates argset$output_dir, draws data$data as a ribbon between temp_min and temp_max over date, and saves it with ggplot2::ggsave() to argset$output_absolute_path. That path is a glue::glue() template evaluated once against argset, so "{argset$output_dir}" resolves but a brace left inside argset$output_filename does not.

Usage

weather_export_plots_action(data, argset, tables)

Arguments

data	Data
argset	Argset
tables	DB tables

Details

This is the one action that touches no database table, so tables is unused and the example below passes NULL for it.

See Also

weather_export_plots_data_selector(), which produces this action's data argument. cs9example has no vignettes of its own; how cs9 pairs an action with a data selector is documented in cs9::SurveillanceSystem_v9.

Other cs9 task actions: weather_clean_data_action(), weather_download_and_import_rawdata_action()

Examples

# An argset shaped like the one cs9 builds for this task, and a stand-in for
# what the data selector would have returned.
d <- list(data = data.table::data.table(
  date = as.Date("2024-01-01") + 0:29,
  temp_min = seq(-8, 6, length.out = 30),
  temp_max = seq(-2, 12, length.out = 30)
))
argset <- list(
  location_code = "county_nor03",
  output_dir = fs::path(tempdir(), "cs9example-plots"),
  output_filename = "weather_county_nor03.png",
  output_absolute_path = fs::path("{argset$output_dir}", "{argset$output_filename}"),
  first_analysis = TRUE,
  last_analysis = TRUE
)

weather_export_plots_action(data = d, argset = argset, tables = NULL)
fs::dir_ls(argset$output_dir)

---

weather_export_plots (data selector)

Description

Pulls every row of anon_example_weather_data for the location named in argset$location_code. Returns the date, temp_max and temp_min columns under the name data, ordered by date.

Usage

weather_export_plots_data_selector(argset, tables)

Arguments

argset	Argset
tables	DB tables

Value

A named list with one element, data: a data.table of date, temp_max and temp_min.

See Also

weather_export_plots_action(), which consumes this list, and cs9::mandatory_db_filter() for the filter it applies. cs9example has no vignettes of its own; how cs9 pairs a data selector with an action is documented in cs9::SurveillanceSystem_v9.

Other cs9 task data selectors: weather_clean_data_data_selector(), weather_download_and_import_rawdata_data_selector()

Examples

## Not run: 
# Needs a live cs9 PostgreSQL database: it reads the
# anon_example_weather_data table.
weather_export_plots_data_selector(
  argset = global$ss$shortcut_get_argset("weather_export_plots"),
  tables = global$ss$shortcut_get_tables("weather_export_plots")
)

## End(Not run)

---