tests/testthat/test_read_cpout.R
In BodenmillerGroup/imcRtools: Methods for imaging mass cytometry data analysis
test_that("read_cpout function works.", {
path <- system.file("extdata/mockData/cpout", package = "imcRtools")
# SpatialExperiment
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv")
expect_equal(colnames(cur_spe), paste0(cur_spe$sample_id, "_", cur_spe$ObjectNumber))
expect_s4_class(cur_spe, "SpatialExperiment")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_spe, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_spe[,cur_spe$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
cur_dat <- unique(colData(cur_spe)[,c("sample_id", "Metadata_acname", "Metadata_acid", "Metadata_description")])
expect_equal(as.numeric(cur_dat$sample_id), image_file$ImageNumber)
expect_equal(cur_dat$Metadata_acname, image_file$Metadata_acname)
expect_equal(cur_dat$Metadata_acid, image_file$Metadata_acid)
expect_equal(cur_dat$Metadata_description, image_file$Metadata_description)
# SingleCellExperiment
cur_sce <- read_cpout(path, return_as = "sce", graph_file = "Object_relationships.csv")
expect_equal(colnames(cur_sce), paste0(cur_sce$sample_id, "_", cur_sce$ObjectNumber))
expect_s4_class(cur_sce, "SingleCellExperiment")
expect_equal(rownames(cur_sce), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_sce), "counts")
expect_equal(dim(cur_sce), c(5, 239))
expect_equal(names(rowData(cur_sce)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "Pos_X", "Pos_Y", "AreaShape_Area",
"Neighbors_NumberOfNeighbors_8", "AreaShape_Eccentricity", "AreaShape_MajorAxisLength",
"AreaShape_MinorAxisLength", "AreaShape_MeanRadius", "ImageNumber", "Metadata_acname",
"Metadata_acid", "Metadata_description"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_sce)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_sce)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_sce)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_sce$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_sce$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_sce$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_sce$Metadata_description, object_file$Metadata_description)
expect_equal(cur_sce$Pos_X, object_file$Location_Center_X)
expect_equal(cur_sce$Pos_Y, object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_sce)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_sce)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_sce)$Target, cur_panel$Target)
expect_equal(rowData(cur_sce)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_sce)$full, cur_panel$full)
expect_equal(colPairNames(cur_sce), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_sce, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_sce[,cur_sce$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
# Test other inputs
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv",
panel_file = paste0(path, "/panel.csv"))
cur_spe <- read_cpout(path, image_file = NULL, scale_intensities = FALSE,
graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_spe)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(counts(cur_spe)[1:10] * (2^16 - 1), c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_spe, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_spe[,cur_spe$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_sce <- read_cpout(path, return_as = "sce", image_file = NULL,
scale_intensities = FALSE, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_sce), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_sce), "counts")
expect_equal(dim(cur_sce), c(5, 239))
expect_equal(names(rowData(cur_sce)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "Pos_X", "Pos_Y", "AreaShape_Area",
"Neighbors_NumberOfNeighbors_8", "AreaShape_Eccentricity", "AreaShape_MajorAxisLength",
"AreaShape_MinorAxisLength", "AreaShape_MeanRadius"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_sce)
test1 <- counts(cur_sce)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_sce)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(cur_sce$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_sce$Pos_X, object_file$Location_Center_X)
expect_equal(cur_sce$Pos_Y, object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_sce)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_sce)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_sce)$Target, cur_panel$Target)
expect_equal(rowData(cur_sce)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_sce)$full, cur_panel$full)
expect_equal(colPairNames(cur_sce), "neighborhood")
expect_equal(length(colPair(cur_sce, "neighborhood")), 1484)
cur_spe <- read_cpout(path, scale_intensities = FALSE, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_spe)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, graph_file = NULL)
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(length(colPairNames(cur_spe)), 0)
cur_spe <- read_cpout(path, panel_file = NULL, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(length(names(rowData(cur_spe))), 0)
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, intensities = "MedianIntensity_FullStack_", graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MedianIntensity_FullStack_", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- merge(object_file, image_file, by = "ImageNumber", order = FALSE)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0, 0, 0, 0, 0,
0, 0, 0, 0, 1))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, extract_cellmetadata_from = "Location_MaxIntensity_Y_FullStack_c1",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "Location_MaxIntensity_Y_FullStack_c1",
"ImageNumber",
"Metadata_acname",
"Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
expect_equal(cur_spe$Location_MaxIntensity_Y_FullStack_c1, object_file$Location_MaxIntensity_Y_FullStack_c1)
cur_spe <- read_cpout(path, extract_imagemetadata_from = "Metadata_end_timestamp",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius","ImageNumber", "Metadata_end_timestamp"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- merge(object_file, image_file, by = "ImageNumber", order = FALSE)
expect_equal(cur_spe$Metadata_end_timestamp, object_file$Metadata_end_timestamp)
cur_spe <- read_cpout(path, extract_coords_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(length(spatialCoordsNames(cur_spe)), 0)
cur_sce <- read_cpout(path, extract_coords_from = NULL, return_as = "sce",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"
))
cur_spe <- read_cpout(path, extract_cellmetadata_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "ImageNumber",
"Metadata_acname", "Metadata_acid", "Metadata_description"))
cur_spe <- read_cpout(path, extract_imagemetadata_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber"))
# Test other Images.csv entries
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv",
extract_imagemetadata_from = c("Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x"))
image_file <- vroom::vroom(file.path(path, "Image.csv"))
cur_test <- unique(colData(cur_spe)[,c("ImageNumber", "Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x")])
expect_equal(image_file$ImageNumber, cur_test$ImageNumber)
expect_equal(image_file$Intensity_PercentMaximal_FullStack_c1, cur_test$Intensity_PercentMaximal_FullStack_c1)
expect_equal(image_file$Intensity_MeanIntensity_FullStack_c5, cur_test$Intensity_MeanIntensity_FullStack_c5)
expect_equal(image_file$Metadata_max_x, cur_test$Metadata_max_x)
cur_sce <- read_cpout(path, graph_file = "Object_relationships.csv",
extract_imagemetadata_from = c("Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x"), return_as = "sce")
image_file <- vroom::vroom(file.path(path, "Image.csv"))
cur_test <- unique(colData(cur_sce)[,c("ImageNumber", "Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x")])
expect_equal(image_file$ImageNumber, cur_test$ImageNumber)
expect_equal(image_file$Intensity_PercentMaximal_FullStack_c1, cur_test$Intensity_PercentMaximal_FullStack_c1)
expect_equal(image_file$Intensity_MeanIntensity_FullStack_c5, cur_test$Intensity_MeanIntensity_FullStack_c5)
expect_equal(image_file$Metadata_max_x, cur_test$Metadata_max_x)
# Fail
expect_error(read_cpout("test",
graph_file = "Object_relationships.csv"),
regexp = "'path' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(1,
graph_file = "Object_relationships.csv"),
regexp = "'path' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(c("test", "test"),
graph_file = "Object_relationships.csv"),
regexp = "'path' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = NULL),
regexp = "'object_file' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = "test"),
regexp = "'object_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = 1),
regexp = "'object_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = c("test", "test")),
regexp = "'object_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = NULL),
regexp = "'object_feature_file' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = "test"),
regexp = "'object_feature_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = 1),
regexp = "'object_feature_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = c("test", "test")),
regexp = "'object_feature_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = NULL),
regexp = "When scaling the summarized object intensities, please supply the 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = "test"),
regexp = "'image_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = 1),
regexp = "'image_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = c("test", "test")),
regexp = "'image_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = "test"),
regexp = "'graph_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = 1),
regexp = "'graph_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = c("test", "test")),
regexp = "'graph_file' must be a single string.",
fixed = TRUE)
expect_warning(read_cpout(path, panel_file = "test",
graph_file = "Object_relationships.csv"),
regexp = "'panel_file' does not exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
panel_file = 1),
regexp = "'panel_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
panel_file = c("test", "test")),
regexp = "'panel_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = NULL),
regexp = "'extract_metal_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = "test"),
regexp = "'extract_metal_from' not in panel file.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = 1),
regexp = "'extract_metal_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = c("test", "test")),
regexp = "'extract_metal_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = NULL),
regexp = "'intensities' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = "test"),
regexp = "No intensity features were read in. Please check the 'intensities' parameter.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = "MeanIntensity"),
regexp = "Some of the features set via 'intensities' cannot be uniquely accessed.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = c("MeanIntensity", "MedianIntensity")),
regexp = "'intensities' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = 1),
regexp = "'intensities' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = NULL),
regexp = "'extract_imgid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = 1),
regexp = "'extract_imgid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = c("test", "test")),
regexp = "'extract_imgid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = "test"),
regexp = "'extract_imgid_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = NULL),
regexp = "'extract_cellid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = 1),
regexp = "'extract_cellid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = c("test", "test")),
regexp = "'extract_cellid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = "test"),
regexp = "'extract_cellid_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_coords_from = 1),
regexp = "'extract_coords_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_coords_from = c("test1", "Location_X")),
regexp = "'extract_coords_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellmetadata_from = 1),
regexp = "'extract_cellmetadata_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellmetadata_from = c("test1", "Location_X")),
regexp = "'extract_cellmetadata_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = NULL),
regexp = "'scale_intensities' needs to be logical.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = c(1,2)),
regexp = "'scale_intensities' needs to be of length 1.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = "test"),
regexp = "'scale_intensities' needs to be logical.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = NULL),
regexp = "When scaling the summarized object intensities, please supply the 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imagemetadata_from = "test"),
regexp = "'extract_imagemetadata_from' not in 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_scalingfactor_from = c(1,2)),
regexp = "'extract_scalingfactor_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_scalingfactor_from = "test"),
regexp = "'extract_scalingfactor_from' not in 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = NULL),
regexp = "'extract_graphimageid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = c(1,2)),
regexp = "'extract_graphimageid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = "test"),
regexp = "'extract_graphimageid_from' not in 'graph_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphcellids_from = NULL),
regexp = "'extract_graphcellids_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphcellids_from = c("test", "Second Object Number")),
regexp = "'extract_graphcellids_from' not in 'graph_file'.",
fixed = TRUE)
})
BodenmillerGroup/imcRtools documentation built on Oct. 30, 2024, 12:19 p.m.
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test_that("read_cpout function works.", {
path <- system.file("extdata/mockData/cpout", package = "imcRtools")
# SpatialExperiment
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv")
expect_equal(colnames(cur_spe), paste0(cur_spe$sample_id, "_", cur_spe$ObjectNumber))
expect_s4_class(cur_spe, "SpatialExperiment")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_spe, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_spe[,cur_spe$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
cur_dat <- unique(colData(cur_spe)[,c("sample_id", "Metadata_acname", "Metadata_acid", "Metadata_description")])
expect_equal(as.numeric(cur_dat$sample_id), image_file$ImageNumber)
expect_equal(cur_dat$Metadata_acname, image_file$Metadata_acname)
expect_equal(cur_dat$Metadata_acid, image_file$Metadata_acid)
expect_equal(cur_dat$Metadata_description, image_file$Metadata_description)
# SingleCellExperiment
cur_sce <- read_cpout(path, return_as = "sce", graph_file = "Object_relationships.csv")
expect_equal(colnames(cur_sce), paste0(cur_sce$sample_id, "_", cur_sce$ObjectNumber))
expect_s4_class(cur_sce, "SingleCellExperiment")
expect_equal(rownames(cur_sce), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_sce), "counts")
expect_equal(dim(cur_sce), c(5, 239))
expect_equal(names(rowData(cur_sce)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "Pos_X", "Pos_Y", "AreaShape_Area",
"Neighbors_NumberOfNeighbors_8", "AreaShape_Eccentricity", "AreaShape_MajorAxisLength",
"AreaShape_MinorAxisLength", "AreaShape_MeanRadius", "ImageNumber", "Metadata_acname",
"Metadata_acid", "Metadata_description"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_sce)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_sce)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_sce)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_sce$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_sce$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_sce$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_sce$Metadata_description, object_file$Metadata_description)
expect_equal(cur_sce$Pos_X, object_file$Location_Center_X)
expect_equal(cur_sce$Pos_Y, object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_sce)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_sce)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_sce)$Target, cur_panel$Target)
expect_equal(rowData(cur_sce)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_sce)$full, cur_panel$full)
expect_equal(colPairNames(cur_sce), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_sce, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_sce[,cur_sce$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
# Test other inputs
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv",
panel_file = paste0(path, "/panel.csv"))
cur_spe <- read_cpout(path, image_file = NULL, scale_intensities = FALSE,
graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_spe)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(counts(cur_spe)[1:10] * (2^16 - 1), c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_silent(cur_graphs <- colPair(cur_spe, "neighborhood"))
cur_test <- vroom::vroom(file.path(path, "Object_relationships.csv"))
for (i in unique(cur_test$`First Image Number`)) {
cur_dat <- cur_spe[,cur_spe$sample_id == i]
cur_test_dat <- cur_test[cur_test$`First Image Number` == i,]
expect_equal(from(colPair(cur_dat, "neighborhood")), cur_test_dat$`First Object Number`)
expect_equal(to(colPair(cur_dat, "neighborhood")), cur_test_dat$`Second Object Number`)
}
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_sce <- read_cpout(path, return_as = "sce", image_file = NULL,
scale_intensities = FALSE, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_sce), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_sce), "counts")
expect_equal(dim(cur_sce), c(5, 239))
expect_equal(names(rowData(cur_sce)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "Pos_X", "Pos_Y", "AreaShape_Area",
"Neighbors_NumberOfNeighbors_8", "AreaShape_Eccentricity", "AreaShape_MajorAxisLength",
"AreaShape_MinorAxisLength", "AreaShape_MeanRadius"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_sce)
test1 <- counts(cur_sce)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_sce)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(cur_sce$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_sce$Pos_X, object_file$Location_Center_X)
expect_equal(cur_sce$Pos_Y, object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_sce)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_sce)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_sce)$Target, cur_panel$Target)
expect_equal(rowData(cur_sce)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_sce)$full, cur_panel$full)
expect_equal(colPairNames(cur_sce), "neighborhood")
expect_equal(length(colPair(cur_sce, "neighborhood")), 1484)
cur_spe <- read_cpout(path, scale_intensities = FALSE, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts)
expect_equal(counts(cur_spe)[1:10], c(1.65858933621127e-06, 3.31717867242253e-07, 0, 6.63435734484507e-07,
1.12784074862366e-05, 0, 0, 0, 0, 1.83108262717724e-05))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, graph_file = NULL)
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(length(colPairNames(cur_spe)), 0)
cur_spe <- read_cpout(path, panel_file = NULL, graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(length(names(rowData(cur_spe))), 0)
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- dplyr::left_join(object_file, image_file, by = "ImageNumber")
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0.108695652148605, 0.0217391304297211, 0, 0.0434782608594421,
0.739130434610516, 0, 0, 0, 0, 1.1999999997206))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, intensities = "MedianIntensity_FullStack_", graph_file = "Object_relationships.csv")
expect_equal(rownames(cur_spe), c("Ag107", "Pr141", "Sm147", "Eu153", "Yb172"))
expect_equal(assayNames(cur_spe), "counts")
expect_equal(dim(cur_spe), c(5, 239))
expect_equal(names(rowData(cur_spe)),
c("Tube.Number", "Metal.Tag", "Target", "ilastik", "full", "deepcell",
"cellpose"))
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MedianIntensity_FullStack_", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- merge(object_file, image_file, by = "ImageNumber", order = FALSE)
test1 <- counts(cur_spe)
colnames(test1) <- NULL
expect_equal(test1, cur_counts * (2^16 - 1))
expect_equal(counts(cur_spe)[1:10], c(0, 0, 0, 0, 0,
0, 0, 0, 0, 1))
expect_equal(cur_spe$Neighbors_NumberOfNeighbors_8, object_file$Neighbors_NumberOfNeighbors_8)
expect_equal(cur_spe$Metadata_acname, object_file$Metadata_acname)
expect_equal(cur_spe$Metadata_acid, object_file$Metadata_acid)
expect_equal(cur_spe$Metadata_description, object_file$Metadata_description)
expect_equal(as.numeric(spatialCoords(cur_spe)[,1]), object_file$Location_Center_X)
expect_equal(as.numeric(spatialCoords(cur_spe)[,2]), object_file$Location_Center_Y)
cur_panel <- vroom::vroom(file.path(path, "panel.csv"))
mass <- as.numeric(stringr::str_extract(cur_panel$`Metal Tag`, "[0-9]{2,3}"))
cur_panel <- cur_panel[order(as.numeric(mass), decreasing = FALSE),]
expect_equal(rowData(cur_spe)$Tube.Number, cur_panel$`Tube Number`)
expect_equal(rowData(cur_spe)$Metal.Tag, cur_panel$`Metal Tag`)
expect_equal(rowData(cur_spe)$Target, cur_panel$Target)
expect_equal(rowData(cur_spe)$ilastik, cur_panel$ilastik)
expect_equal(rowData(cur_spe)$full, cur_panel$full)
expect_equal(colPairNames(cur_spe), "neighborhood")
expect_equal(length(colPair(cur_spe, "neighborhood")), 1484)
cur_spe <- read_cpout(path, extract_cellmetadata_from = "Location_MaxIntensity_Y_FullStack_c1",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "Location_MaxIntensity_Y_FullStack_c1",
"ImageNumber",
"Metadata_acname",
"Metadata_acid", "Metadata_description"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
expect_equal(cur_spe$Location_MaxIntensity_Y_FullStack_c1, object_file$Location_MaxIntensity_Y_FullStack_c1)
cur_spe <- read_cpout(path, extract_imagemetadata_from = "Metadata_end_timestamp",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius","ImageNumber", "Metadata_end_timestamp"))
expect_equal(spatialCoordsNames(cur_spe), c("Pos_X", "Pos_Y"))
object_file <- vroom::vroom(file.path(path, "cell.csv"))
cur_counts <- t(object_file[,grepl("MeanIntensity_FullStack", colnames(object_file))])
rownames(cur_counts) <- rownames(cur_spe)
image_file <- vroom::vroom(file.path(path, "Image.csv"))
object_file <- merge(object_file, image_file, by = "ImageNumber", order = FALSE)
expect_equal(cur_spe$Metadata_end_timestamp, object_file$Metadata_end_timestamp)
cur_spe <- read_cpout(path, extract_coords_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(length(spatialCoordsNames(cur_spe)), 0)
cur_sce <- read_cpout(path, extract_coords_from = NULL, return_as = "sce",
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_sce)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber", "Metadata_acname", "Metadata_acid", "Metadata_description"
))
cur_spe <- read_cpout(path, extract_cellmetadata_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "ImageNumber",
"Metadata_acname", "Metadata_acid", "Metadata_description"))
cur_spe <- read_cpout(path, extract_imagemetadata_from = NULL,
graph_file = "Object_relationships.csv")
expect_equal(names(colData(cur_spe)), c("sample_id", "ObjectNumber", "AreaShape_Area", "Neighbors_NumberOfNeighbors_8",
"AreaShape_Eccentricity", "AreaShape_MajorAxisLength", "AreaShape_MinorAxisLength",
"AreaShape_MeanRadius", "ImageNumber"))
# Test other Images.csv entries
cur_spe <- read_cpout(path, graph_file = "Object_relationships.csv",
extract_imagemetadata_from = c("Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x"))
image_file <- vroom::vroom(file.path(path, "Image.csv"))
cur_test <- unique(colData(cur_spe)[,c("ImageNumber", "Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x")])
expect_equal(image_file$ImageNumber, cur_test$ImageNumber)
expect_equal(image_file$Intensity_PercentMaximal_FullStack_c1, cur_test$Intensity_PercentMaximal_FullStack_c1)
expect_equal(image_file$Intensity_MeanIntensity_FullStack_c5, cur_test$Intensity_MeanIntensity_FullStack_c5)
expect_equal(image_file$Metadata_max_x, cur_test$Metadata_max_x)
cur_sce <- read_cpout(path, graph_file = "Object_relationships.csv",
extract_imagemetadata_from = c("Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x"), return_as = "sce")
image_file <- vroom::vroom(file.path(path, "Image.csv"))
cur_test <- unique(colData(cur_sce)[,c("ImageNumber", "Intensity_PercentMaximal_FullStack_c1",
"Intensity_MeanIntensity_FullStack_c5",
"Metadata_max_x")])
expect_equal(image_file$ImageNumber, cur_test$ImageNumber)
expect_equal(image_file$Intensity_PercentMaximal_FullStack_c1, cur_test$Intensity_PercentMaximal_FullStack_c1)
expect_equal(image_file$Intensity_MeanIntensity_FullStack_c5, cur_test$Intensity_MeanIntensity_FullStack_c5)
expect_equal(image_file$Metadata_max_x, cur_test$Metadata_max_x)
# Fail
expect_error(read_cpout("test",
graph_file = "Object_relationships.csv"),
regexp = "'path' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(1,
graph_file = "Object_relationships.csv"),
regexp = "'path' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(c("test", "test"),
graph_file = "Object_relationships.csv"),
regexp = "'path' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = NULL),
regexp = "'object_file' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = "test"),
regexp = "'object_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = 1),
regexp = "'object_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_file = c("test", "test")),
regexp = "'object_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = NULL),
regexp = "'object_feature_file' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = "test"),
regexp = "'object_feature_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = 1),
regexp = "'object_feature_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
object_feature_file = c("test", "test")),
regexp = "'object_feature_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = NULL),
regexp = "When scaling the summarized object intensities, please supply the 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = "test"),
regexp = "'image_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = 1),
regexp = "'image_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = c("test", "test")),
regexp = "'image_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = "test"),
regexp = "'graph_file' doesn't exist.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = 1),
regexp = "'graph_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path, graph_file = c("test", "test")),
regexp = "'graph_file' must be a single string.",
fixed = TRUE)
expect_warning(read_cpout(path, panel_file = "test",
graph_file = "Object_relationships.csv"),
regexp = "'panel_file' does not exist.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
panel_file = 1),
regexp = "'panel_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
panel_file = c("test", "test")),
regexp = "'panel_file' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = NULL),
regexp = "'extract_metal_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = "test"),
regexp = "'extract_metal_from' not in panel file.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = 1),
regexp = "'extract_metal_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_metal_from = c("test", "test")),
regexp = "'extract_metal_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = NULL),
regexp = "'intensities' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = "test"),
regexp = "No intensity features were read in. Please check the 'intensities' parameter.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = "MeanIntensity"),
regexp = "Some of the features set via 'intensities' cannot be uniquely accessed.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = c("MeanIntensity", "MedianIntensity")),
regexp = "'intensities' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
intensities = 1),
regexp = "'intensities' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = NULL),
regexp = "'extract_imgid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = 1),
regexp = "'extract_imgid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = c("test", "test")),
regexp = "'extract_imgid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imgid_from = "test"),
regexp = "'extract_imgid_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = NULL),
regexp = "'extract_cellid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = 1),
regexp = "'extract_cellid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = c("test", "test")),
regexp = "'extract_cellid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellid_from = "test"),
regexp = "'extract_cellid_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_coords_from = 1),
regexp = "'extract_coords_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_coords_from = c("test1", "Location_X")),
regexp = "'extract_coords_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellmetadata_from = 1),
regexp = "'extract_cellmetadata_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_cellmetadata_from = c("test1", "Location_X")),
regexp = "'extract_cellmetadata_from' not in 'object_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = NULL),
regexp = "'scale_intensities' needs to be logical.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = c(1,2)),
regexp = "'scale_intensities' needs to be of length 1.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
scale_intensities = "test"),
regexp = "'scale_intensities' needs to be logical.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
image_file = NULL),
regexp = "When scaling the summarized object intensities, please supply the 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_imagemetadata_from = "test"),
regexp = "'extract_imagemetadata_from' not in 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_scalingfactor_from = c(1,2)),
regexp = "'extract_scalingfactor_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_scalingfactor_from = "test"),
regexp = "'extract_scalingfactor_from' not in 'image_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = NULL),
regexp = "'extract_graphimageid_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = c(1,2)),
regexp = "'extract_graphimageid_from' must be a single string.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphimageid_from = "test"),
regexp = "'extract_graphimageid_from' not in 'graph_file'.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphcellids_from = NULL),
regexp = "'extract_graphcellids_from' must be specified.",
fixed = TRUE)
expect_error(read_cpout(path,
graph_file = "Object_relationships.csv",
extract_graphcellids_from = c("test", "Second Object Number")),
regexp = "'extract_graphcellids_from' not in 'graph_file'.",
fixed = TRUE)
})
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