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Restructure plot filtering

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Bryan Roessler
2024-09-16 15:21:41 -04:00
parent 37743b1f5e
commit 5c87ff8615
1 changed files with 15 additions and 21 deletions
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26
qhtcp-workflow/apps/r/calculate_interaction_zscores.R
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@@ -787,46 +787,40 @@ filter_and_print_non_finite <- function(df, vars_to_check, print_vars) {
df %>% filter(if_all(all_of(vars_to_check), is.finite)) df %>% filter(if_all(all_of(vars_to_check), is.finite))
} }
filter_data_for_plots <- function(df, variables, missing = TRUE, limits_map = NULL) { filter_data_for_plots <- function(df, variables, missing = FALSE, limits_map = NULL) {
# Print missing data and out-of-range data separately # Loop through each variable to filter and print missing/out-of-range data
for (variable in variables) { for (variable in variables) {
y_var_sym <- sym(variable) y_var_sym <- sym(variable)
# Filter missing data
if (missing) { if (missing) {
missing_data <- df %>% filter(is.na(!!y_var_sym)) missing_data <- df %>% filter(is.na(!!y_var_sym))
if (nrow(missing_data) > 0) { if (nrow(missing_data) > 0) {
message("Missing data for variable ", variable, ":") message("Missing data for variable ", variable, ":")
print(missing_data) print(missing_data)
} }
df <- df %>% filter(!is.na(!!y_var_sym))
} }
# Filter out-of-range data if limits_map is provided
if (!is.null(limits_map)) { if (!is.null(limits_map)) {
# Get y-limits for the variable
ylim_vals <- limits_map[[variable]] ylim_vals <- limits_map[[variable]]
# Identify out-of-range data and print it # Print and filter out-of-range data
out_of_range_data <- df %>% filter( out_of_range_data <- df %>% filter(
!is.na(!!y_var_sym) & !!y_var_sym < ylim_vals[1] | !!y_var_sym > ylim_vals[2]
(!!y_var_sym < min(ylim_vals, na.rm = TRUE) | !!y_var_sym > max(ylim_vals, na.rm = TRUE))
) )
if (nrow(out_of_range_data) > 0) { if (nrow(out_of_range_data) > 0) {
message("Out-of-range data for variable ", variable, ":") message("Out-of-range data for variable ", variable, ":")
print(out_of_range_data) print(out_of_range_data)
df <- df %>%
filter(!!y_var_sym >= ylim_vals[1] & !!y_var_sym <= ylim_vals[2])
} }
} }
} }
# Filter data by checking if all variables are within the specified limits return(df)
if (!is.null(limits_map)) {
df_filtered <- df %>%
filter(if_all(all_of(variables), ~ !is.na(.))) %>% # Check for non-NA values
filter(if_all(all_of(variables), ~ . >= limits_map[[cur_column()]][1] & . <= limits_map[[cur_column()]][2]))
} else {
df_filtered <- df %>% filter(if_all(all_of(variables), ~ !is.na(.)))
}
return(df_filtered)
} }
main <- function() { main <- function() {