Cohort {cohortBuilder} R Documentation

R6 class representing Cohort object.

Description

R6 class representing Cohort object.

R6 class representing Cohort object.

Details

Cohort object is designed to make operations on source data possible.

Public fields

attributes

List of Cohort attributes defined while creating a new Cohort object.

Methods

Method new()

Create Cohort object.

Arguments
source

Source object created with set_source.

Method update_source()

Update Source in the Cohort object.

Method add_step()

Arguments
step_id

Id of the step to be copied. If missing the last step is taken. The copied step is added as the last one in the Cohort.

filters

List of Source-evaluated filters to copy to new step.

run_flow

If 'TRUE', data flow is run after the operation is completed.

Method remove_step()

Remove filtering step definition

Arguments
filter

Filter definition created with filter.

step_id

Id of the step to add the filter to. If missing, filter is added to the last step.

run_flow

If 'TRUE', data flow is run after the operation is completed.

Method remove_filter()

Remove filter definition

Arguments
step_id

Id of the step where filter is defined.

filter_id

Id of the filter to be updated.

...

Filter parameters that should be updated.

active

Mark filter as active ('TRUE') or inactive ('FALSE').

run_flow

If 'TRUE', data flow is run after the operation is completed.

Method clear_filter()

Reset filter to its default values.

Arguments
step_id

Id of the step where filters should be cleared.

run_flow

If 'TRUE', data flow is run after the operation is completed.

Method sum_up_state()

Sum up Cohort configuration - Source, steps definition and evaluated data.

Arguments
step_id

If provided, the selected step state is returned.

json

If TRUE, return state in JSON format.

extra_fields

Names of extra fields included in filter to be added to state. Restore Cohort configuration.

Method restore()

Arguments
step_id

Id of the step from which to source data.

state

Return data before ("pre") or after ("post") step filtering?

collect

Return raw data source ('FALSE') object or collected (to R memory) data ('TRUE').

Method plot_data()

Plot filter specific data summary.

Arguments
...

Source specific parameters required to generate attrition.

percent

Should attrition changes be presented with percentage values.

Method get_stats()

Get Cohort related statistics.

Cohort$get_stats(step_id, filter_id, ..., state = "post") Arguments step_id When 'filter_id' specified, 'step_id' precises from which step the filter comes from. Otherwise data from specified step is used to calculate required statistics. filter_id If not missing, filter related data statistics are returned. ... Specific parameters passed to filter related method. state Should the stats be calculated on data before ("pre") or after ("post") filtering in specified step. Method show_help() Show source data or filter description Usage Cohort$show_help(
field,
step_id,
filter_id,
modifier = getOption("cb_help_modifier", default = function(x) x)
)
Arguments
field

Name of the source description field provided as 'description' argument to set_source. If missing, 'step_id' and 'filter_id' are used to return filter description.

step_id

Id of the filter step to return description of.

filter_id

Id of the filter to return description of.

modifier

A function taking the description as argument. The function can be used to modify its argument (convert to html, display in browser etc.).

Method get_code()

Return reproducible data filtering code.

Cohort$get_code( include_source = TRUE, include_methods = c(".pre_filtering", ".post_filtering", ".run_binding"), include_action = c("pre_filtering", "post_filtering", "run_binding"), modifier = .repro_code_tweak, mark_step = TRUE, ... ) Arguments include_source If 'TRUE' source generating code will be included. include_methods Which methods definition should be included in the result. include_action Which action should be returned in the result. 'pre_filtering'/'.post_filtering' - to include data transformation before/after filtering. s'run_binding' - data binding transformation. modifier A function taking data frame (storing reproducible code metadata) as an argument, and returning data frame with 'expr' column which is then combined into a single expression (final result of 'get_code'). See .repro_code_tweak. mark_step Include information which filtering step is performed. ... Other parameters passed to tidy_source. Method run_flow() Trigger data calculations sequentially. Usage Cohort$run_flow(
min_step,
hook = list(pre = get_hook("pre_run_flow_hook"), post = get_hook("post_run_flow_hook"))
)
Arguments
min_step

Step id starting from the calculation will be started.

hook

List of hooks describing methods before/after the Cohort is created. See hooks for more details.

Method run_step()

Trigger data calculations for selected step.

Arguments
step_id

Id of the step for which to bind the data.

Method describe_state()

Print defined steps configuration.

Arguments
step_id

Id of the step to be returned.

Method get_filter()

Get selected filter configuration.

Arguments
step_id

Id of the step for which caching should be applied. If 'filter_id' is not missing, the parameter describes id of the step where filter should be found.

filter_id

Id of the filter for which caching should be applied.

state

Should caching be done on data before ("pre") or after ("post") filtering in specified step.

Method get_cache()

Return step of filter specific cache.

Arguments
step_id

Id of the step where filters should be found.

Method last_step_id()

Return id of the last existing step in Cohort.

Arguments
modifier

Function of two arguments 'self' and 'private'.

Method clone()

The objects of this class are cloneable with this method.

Usage
Cohort\$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

[Package cohortBuilder version 0.2.0 Index]