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Reindent code to use just two spaces

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This commit is contained in:
Elias Projahn 2022-05-26 12:42:19 +02:00
parent a1e6147466
commit c04b6337e9
17 changed files with 1583 additions and 1582 deletions
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148
R/method_adjacency.R
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@ -12,14 +12,14 @@
#'
#' @export
densest <- function(data) {
as.numeric(if (length(data) <= 0) {
NULL
} else if (length(data) == 1) {
data
} else {
density <- stats::density(data)
mean(density$x[density$y == max(density$y)])
})
as.numeric(if (length(data) <= 0) {
NULL
} else if (length(data) == 1) {
data
} else {
density <- stats::density(data)
mean(density$x[density$y == max(density$y)])
})
}
#' Score genes based on their proximity to the reference genes.
@ -40,80 +40,80 @@ densest <- function(data) {
#'
#' @export
adjacency <- function(distance_estimate = densest, summarize = stats::median) {
method(
id = "adjacency",
name = "Adjacency",
description = "Adjacency to reference genes",
function(preset, progress) {
species_ids <- preset$species_ids
gene_ids <- preset$gene_ids
reference_gene_ids <- preset$reference_gene_ids
method(
id = "adjacency",
name = "Adjacency",
description = "Adjacency to reference genes",
function(preset, progress) {
species_ids <- preset$species_ids
gene_ids <- preset$gene_ids
reference_gene_ids <- preset$reference_gene_ids
cached(
"adjacency",
c(
species_ids,
gene_ids,
reference_gene_ids,
distance_estimate,
summarize
),
{ # nolint
# Filter distances by species and gene and summarize each
# gene's distance values using the estimation function.
data <- geposan::distances[
species %chin% species_ids & gene %chin% gene_ids,
.(distance = as.numeric(distance_estimate(distance))),
by = gene
]
cached(
"adjacency",
c(
species_ids,
gene_ids,
reference_gene_ids,
distance_estimate,
summarize
),
{ # nolint
# Filter distances by species and gene and summarize each
# gene's distance values using the estimation function.
data <- geposan::distances[
species %chin% species_ids & gene %chin% gene_ids,
.(distance = as.numeric(distance_estimate(distance))),
by = gene
]
# Compute the absolute value of the difference between the
# estimated distances of each gene to the reference genes.
compute_difference <- function(distance_value,
comparison_ids) {
differences <- data[
gene %chin% comparison_ids,
.(difference = abs(distance_value - distance))
]
# Compute the absolute value of the difference between the
# estimated distances of each gene to the reference genes.
compute_difference <- function(distance_value,
comparison_ids) {
differences <- data[
gene %chin% comparison_ids,
.(difference = abs(distance_value - distance))
]
summarize(differences$difference)
}
summarize(differences$difference)
}
# Compute the differences to the reference genes.
data[
!gene %chin% reference_gene_ids,
difference := compute_difference(
distance,
reference_gene_ids
),
by = gene
]
# Compute the differences to the reference genes.
data[
!gene %chin% reference_gene_ids,
difference := compute_difference(
distance,
reference_gene_ids
),
by = gene
]
progress(0.5)
progress(0.5)
# Exclude the reference gene itself when computing its
# difference.
data[
gene %chin% reference_gene_ids,
difference := compute_difference(
distance,
reference_gene_ids[reference_gene_ids != gene]
),
by = gene
]
# Exclude the reference gene itself when computing its
# difference.
data[
gene %chin% reference_gene_ids,
difference := compute_difference(
distance,
reference_gene_ids[reference_gene_ids != gene]
),
by = gene
]
# Compute the final score by normalizing the difference.
data[, score := 1 - difference / max(difference)]
# Compute the final score by normalizing the difference.
data[, score := 1 - difference / max(difference)]
progress(1.0)
progress(1.0)
result(
method = "adjacency",
scores = data[, .(gene, score)],
details = list(data = data)
)
}
)
result(
method = "adjacency",
scores = data[, .(gene, score)],
details = list(data = data)
)
}
)
)
}
)
}