tests/testthat/test-urls.R
In natverse/fafbseg: Support Functions for Analysis of FAFB EM Segmentation
context("test-urls")
# utils::URLencode has subtle differences from curl
ngurl="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:[%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22,%22type%22:%22segmentation%22,%22segments%22:[%220%22,%223140809165%22,%224193866734%22,%224256801664%22,%224314929385%22,%224373082358%22,%224610419193%22,%224672751347%22],%22name%22:%22agglo16_32_4_gt3um%22%7D],%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:[8,8,40],%22voxelCoordinates%22:[78997,25574,3600]%7D%7D,%22zoomFactor%22:13.1%7D,%22showAxisLines%22:false,%22showDefaultAnnotations%22:false,%22perspectiveOrientation%22:[0.08,0.22,-0.15,-0.95],%22perspectiveZoom%22:2382,%22showSlices%22:false,%22layout%22:%223d%22%7D"
# this uses the new urlencode function and is confirmed to work ...
ngurl="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22brainmaps%3A%2F%2F772153499790%3Afafb_v14%3Afafb14_4nm_split4x_fill2%3Affnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22%3A%22segmentation%22%2C%22segments%22%3A%5B%220%22%2C%223140809165%22%2C%224193866734%22%2C%224256801664%22%2C%224314929385%22%2C%224373082358%22%2C%224610419193%22%2C%224672751347%22%5D%2C%22name%22%3A%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22%3A%5B78997%2C25574%2C3600%5D%7D%7D%2C%22zoomFactor%22%3A13.1%7D%2C%22showAxisLines%22%3Afalse%2C%22showDefaultAnnotations%22%3Afalse%2C%22perspectiveOrientation%22%3A%5B0.08%2C0.22%2C-0.15%2C-0.95%5D%2C%22perspectiveZoom%22%3A2382%2C%22showSlices%22%3Afalse%2C%22layout%22%3A%223d%22%7D"
test_that("decode scene works", {
expect_error(ngl_decode_scene('https'))
expect_error(ngl_decode_scene('{'))
# url="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%220%22%2C%223140809165%22%2C%224193866734%22%2C%224256801664%22%2C%224314929385%22%2C%224373082358%22%2C%224610419193%22%2C%224672751347%22%5D%2C%22name%22:%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22:%5B78997.46875%2C25574.220703125%2C3600.365966796875%5D%7D%7D%2C%22zoomFactor%22:13.123994088552514%7D%2C%22showAxisLines%22:false%2C%22showDefaultAnnotations%22:false%2C%22perspectiveOrientation%22:%5B0.08349629491567612%2C0.2258872538805008%2C-0.15645836293697357%2C-0.9578747749328613%5D%2C%22perspectiveZoom%22:2382.282469476382%2C%22showSlices%22:false%2C%22layout%22:%223d%22%7D"
# after url decoding, reducing precision and re-encoding
expect_is(sc <- ngl_decode_scene(ngurl), "ngscene")
expect_known_value(sc, file = testthat::test_path('testdata/ngscene.rds'))
with_segmentation("20190805", expect_equal(ngl_encode_url(sc), ngurl))
# expect_is(json <- ngl_decode_scene(ngurl, return.json = TRUE), "character")
# writeLines(json, con='tests/testthat/testdata/ngurl.json')
expect_equal(ngl_decode_scene(ngurl, return.json = TRUE),
readLines('testdata/ngurl.json'))
# check we can cope with a scene as input as a convenience
expect_equal(ngl_decode_scene(sc), sc)
# check that we can cope with a scene that contains state server details
u="https://neuromancer-seung-import.appspot.com/#!%7B%22layers%22:[%7B%22source%22:%22precomputed://gs://zetta_lee_fly_vnc_001_precomputed/fanc_v4_em%22,%22type%22:%22image%22,%22blend%22:%22default%22,%22shaderControls%22:%7B%7D,%22name%22:%22FANCv4%22%7D,%7B%22source%22:%22graphene://https://cave.fanc-fly.com/segmentation/table/mar2021_prod%22,%22type%22:%22segmentation_with_graph%22,%22colorSeed%22:1792288153,%22segmentColors%22:%7B%22648518346498254576%22:%22#1fe0f9%22%7D,%22segments%22:[%22648518346498254576%22],%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22,%22mode3d%22:%22lines%22%7D,%22graphOperationMarker%22:[%7B%22annotations%22:[],%22tags%22:[]%7D,%7B%22annotations%22:[],%22tags%22:[]%7D],%22pathFinder%22:%7B%22color%22:%22#ffff00%22,%22pathObject%22:%7B%22annotationPath%22:%7B%22annotations%22:[],%22tags%22:[]%7D,%22hasPath%22:false%7D%7D,%22name%22:%22seg_Mar2021_proofreading%22%7D,%7B%22source%22:%22precomputed://gs://lee-lab_female-adult-nerve-cord/alignmentV4/synapses/postsynapses_May2021%22,%22type%22:%22image%22,%22blend%22:%22default%22,%22shader%22:%22void%20main()%20%7B%20emitRGBA(vec4(1,%200,%201,%20toNormalized(getDataValue())));%20%7D%22,%22shaderControls%22:%7B%7D,%22name%22:%22synapses_May2021%22,%22visible%22:false%7D,%7B%22type%22:%22segmentation%22,%22mesh%22:%22precomputed://gs://zetta_lee_fly_vnc_001_precomputed/vnc1_full_v3align_2/brain_regions%22,%22objectAlpha%22:0.1,%22hideSegmentZero%22:false,%22ignoreSegmentInteractions%22:true,%22segmentColors%22:%7B%221%22:%22#bfbfbf%22,%222%22:%22#d343d6%22%7D,%22segments%22:[%221%22,%222%22],%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22,%22mode3d%22:%22lines%22%7D,%22name%22:%22volume%20outlines%22%7D],%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:[4.300000190734863,4.300000190734863,45],%22voxelCoordinates%22:[48848.171875,114737.2109375,2690]%7D%7D,%22zoomFactor%22:11.839474231467724%7D,%22perspectiveZoom%22:6704.002738252677,%22showSlices%22:false,%22gpuMemoryLimit%22:4000000000,%22systemMemoryLimit%22:4000000000,%22concurrentDownloads%22:64,%22jsonStateServer%22:%22https://global.daf-apis.com/nglstate/api/v1/post%22,%22selectedLayer%22:%7B%22layer%22:%22seg_Mar2021_proofreading%22,%22visible%22:true%7D,%22layout%22:%22xy-3d%22%7D"
expect_s3_class(sc <- ngl_decode_scene(u), 'ngscene')
expect_s3_class(ngl_decode_scene("https://tinyurl.com/rmr58jpn"), 'ngscene')
expect_s3_class(ngl_decode_scene("https://neuroglancer-demo.appspot.com/#!gs://flyem-user-links/short/2023-08-26.151006.json"), 'ngscene')
expect_s3_class(ngl_decode_scene("https://tinyurl.com/flywirehb2"), 'ngscene')
expect_type(ngl_decode_scene("https://tinyurl.com/flywirehb2", return.json = T), 'character')
})
test_that("we can work round toJSON array issue",{
# This URL only refers to one segment
# toJSON has a problem in
singleton_url="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%223140809165%22%5D%2C%22name%22:%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22:%5B78997%2C25574%2C3600%5D%7D%7D%2C%22zoomFactor%22:13.1%7D%2C%22showAxisLines%22:false%2C%22showDefaultAnnotations%22:false%2C%22perspectiveOrientation%22:%5B0.08082044869661331%2C0.22225624322891235%2C-0.15153835713863373%2C-0.9597428441047668%5D%2C%22perspectiveZoom%22:2382%2C%22showSlices%22:false%2C%22layout%22:%223d%22%7D"
sc2=ngl_decode_scene(singleton_url)
sc2.rt=ngl_decode_scene(ngl_encode_url(sc2), return.json = TRUE)
expect_match(sc2.rt, '"segments":["3140809165"]', fixed = T)
f=system.file("flywire-annotations.json" , package = 'fafbseg')
expect_is(u <- ngl_encode_url(f), 'character')
expect_equal(ngl_encode_url(ngl_decode_scene(u)), u)
# round trip test for a singleton annotation
expect_is(u <- ngl_encode_url(test_path("testdata/flywire-elipse.json")), 'character')
expect_equal(ngl_encode_url(ngl_decode_scene(u)), u)
# alternative way to convert scene to URL
expect_equal(as.character(ngl_decode_scene(u)), u)
# check we use original baseurl when available
fu=flywire_expandurl('https://tinyurl.com/rmr58jpn')
hostname <- function(x) httr::parse_url(x)$hostname
expect_equal(hostname(as.character(ngl_decode_scene(fu))),
hostname(fu))
})
test_that('we can expand neuroglancer URLs without following', {
expect_equal(
flywire_expandurl('https://tinyurl.com/NeckConnective', follow = FALSE),
"https://neuroglancer-demo.appspot.com/#!gs://flyem-user-links/short/NeckConnective.json"
)
})
test_that('we can make a neuroglancer URL', {
catmaid_url <- "https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1"
expect_match(url <- with_segmentation("flywire31", open_fafb_ngl(catmaid_url, open = F)),
"flywire")
expect_equal(xyzmatrix(ngl_decode_scene(url)),
xyzmatrix(catmaid::catmaid_parse_url(catmaid_url)))
})
test_that('we can print scene/layer summaries', {
releases = eval(formals(choose_segmentation)[['release']])
for (r in releases) {
u=getOption("fafbseg.sampleurl")
sc=ngl_decode_scene(u)
expect_output(with_segmentation(r, print(sc)),
"neuroglancer scene with .* layers")
expect_is(ngl_layers(sc, type=='segmentation'), 'nglayers')
expect_is(ngl_layers(sc, visible & nsegs>0), 'nglayers')
}
})
test_that('we can manipulate layers using +/-', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(sc2 <- sc-c("annotation", "jfrc_mesh_test"), 'ngscene')
expect_equal(length(ngl_layers(sc2)), 2L)
expect_is(sc3 <- sc2+ngl_layers(sc)["jfrc_mesh_test"], 'ngscene')
expect_equal(length(ngl_layers(sc3)), 3L)
})
test_that('we can extract annotations', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(ann <- ngl_layers(sc, 'annotation'), 'nglayers')
expect_equal(ngl_layers(sc, type=='annotation'), ann)
})
test_that('we can colour a scene object', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(sc2 <- ngl_add_colours(sc, c("720575940616120581"="red")), "ngscene")
expect_equal(sc2$layers$`Production-segmentation_with_graph`$segmentColors,
list(`720575940616120581` = col2hex("red")))
expect_equal(ngl_add_colours(sc, c("red")), sc2)
expect_is(sc3 <- ngl_add_colours(sc2, c("1"="red", "720575940616120581"="green")), "ngscene")
expect_equal(sc3$layers$`Production-segmentation_with_graph`$segmentColors,
list('1' = col2hex('red'), `720575940616120581` = col2hex("green")))
expect_error(ngl_add_colours(sc, c("-1" = "red")), "invalid ids")
expect_error(ngl_add_colours(sc, c("2" = "rhubarb")), "invalid color name 'rhubarb'")
token=try(chunkedgraph_token(), silent = TRUE)
skip_if(inherits(token, "try-error"),
"Skipping live flywire tests")
# FIXME want to skip on mac on ci only
skip_on_os('mac')
u1="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6528186495008768"
u2="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5198787572137984"
u3="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5673953041317888"
# sequentially build up a data.frame with the colour information
# note that col will be recycled to the same length as the number of segments
colourdf=data.frame(ids=ngl_segments(u1), col='red')
colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u2), col='green'))
colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u3), col='blue'))
colourdf$col=factor(colourdf$col)
# apply that to the first URL
expect_is(sc <- ngl_add_colours(u1, colourdf), 'ngscene')
expect_equal(ngl_segments(sc), colourdf$ids)
})
test_that('we can get blank scene urls', {
expect_s3_class(sc <- ngl_blank_scene(), 'ngscene')
kcid="720575940623755722"
expect_equal(ngl_segments(sc+kcid), kcid)
expect_match(ngl_segmentation(ngl_blank_scene("202004")+1), "ffn1-20200412")
expect_match(ngl_segmentation(ngl_blank_scene("202004", return.url = T)),
"ffn1-20200412")
expect_match(ngl_blank_scene("202004", return.url = T),
baseurl_from_url(
with_segmentation("202004", getOption("fafbseg.sampleurl"))))
})
test_that('we can extract ids from delimited strings',{
expect_equal(flywire_ids('1234, 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('1234, 12345', integer64 = T),
bit64::as.integer64(c("1234", "12345")))
expect_equal(flywire_ids('1234, 12345 ', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids(' 1234 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('\t 1234 \t\n 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('\t fw:1234 \t\n fw:12345', integer64 = T),
c("1234", "12345"))
ids='720575940628529156,720575940621343749,720575940628007172,720575940625455370'
bl=c("720575940628529156", "720575940621343749", "720575940628007172",
"720575940625455370")
expect_equal(flywire_ids(ids), bl)
tf=tempfile('ids', fileext = '.txt')
on.exit(unlink(tf))
writeLines(ids, tf)
expect_equal(flywire_ids(file = tf), bl)
writeLines(bl, tf)
expect_equal(flywire_ids(file = tf), bl)
expect_warning(flywire_ids(1, file = tf), regexp = 'only')
expect_error(flywire_ids(file = tempfile()), regexp = 'file')
})
natverse/fafbseg documentation built on Nov. 11, 2024, 9:50 p.m.
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context("test-urls")
# utils::URLencode has subtle differences from curl
ngurl="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:[%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22,%22type%22:%22segmentation%22,%22segments%22:[%220%22,%223140809165%22,%224193866734%22,%224256801664%22,%224314929385%22,%224373082358%22,%224610419193%22,%224672751347%22],%22name%22:%22agglo16_32_4_gt3um%22%7D],%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:[8,8,40],%22voxelCoordinates%22:[78997,25574,3600]%7D%7D,%22zoomFactor%22:13.1%7D,%22showAxisLines%22:false,%22showDefaultAnnotations%22:false,%22perspectiveOrientation%22:[0.08,0.22,-0.15,-0.95],%22perspectiveZoom%22:2382,%22showSlices%22:false,%22layout%22:%223d%22%7D"
# this uses the new urlencode function and is confirmed to work ...
ngurl="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22%3A%5B%7B%22source%22%3A%22brainmaps%3A%2F%2F772153499790%3Afafb_v14%3Afafb14_4nm_split4x_fill2%3Affnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22%3A%22segmentation%22%2C%22segments%22%3A%5B%220%22%2C%223140809165%22%2C%224193866734%22%2C%224256801664%22%2C%224314929385%22%2C%224373082358%22%2C%224610419193%22%2C%224672751347%22%5D%2C%22name%22%3A%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22%3A%7B%22pose%22%3A%7B%22position%22%3A%7B%22voxelSize%22%3A%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22%3A%5B78997%2C25574%2C3600%5D%7D%7D%2C%22zoomFactor%22%3A13.1%7D%2C%22showAxisLines%22%3Afalse%2C%22showDefaultAnnotations%22%3Afalse%2C%22perspectiveOrientation%22%3A%5B0.08%2C0.22%2C-0.15%2C-0.95%5D%2C%22perspectiveZoom%22%3A2382%2C%22showSlices%22%3Afalse%2C%22layout%22%3A%223d%22%7D"
test_that("decode scene works", {
expect_error(ngl_decode_scene('https'))
expect_error(ngl_decode_scene('{'))
# url="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%220%22%2C%223140809165%22%2C%224193866734%22%2C%224256801664%22%2C%224314929385%22%2C%224373082358%22%2C%224610419193%22%2C%224672751347%22%5D%2C%22name%22:%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22:%5B78997.46875%2C25574.220703125%2C3600.365966796875%5D%7D%7D%2C%22zoomFactor%22:13.123994088552514%7D%2C%22showAxisLines%22:false%2C%22showDefaultAnnotations%22:false%2C%22perspectiveOrientation%22:%5B0.08349629491567612%2C0.2258872538805008%2C-0.15645836293697357%2C-0.9578747749328613%5D%2C%22perspectiveZoom%22:2382.282469476382%2C%22showSlices%22:false%2C%22layout%22:%223d%22%7D"
# after url decoding, reducing precision and re-encoding
expect_is(sc <- ngl_decode_scene(ngurl), "ngscene")
expect_known_value(sc, file = testthat::test_path('testdata/ngscene.rds'))
with_segmentation("20190805", expect_equal(ngl_encode_url(sc), ngurl))
# expect_is(json <- ngl_decode_scene(ngurl, return.json = TRUE), "character")
# writeLines(json, con='tests/testthat/testdata/ngurl.json')
expect_equal(ngl_decode_scene(ngurl, return.json = TRUE),
readLines('testdata/ngurl.json'))
# check we can cope with a scene as input as a convenience
expect_equal(ngl_decode_scene(sc), sc)
# check that we can cope with a scene that contains state server details
u="https://neuromancer-seung-import.appspot.com/#!%7B%22layers%22:[%7B%22source%22:%22precomputed://gs://zetta_lee_fly_vnc_001_precomputed/fanc_v4_em%22,%22type%22:%22image%22,%22blend%22:%22default%22,%22shaderControls%22:%7B%7D,%22name%22:%22FANCv4%22%7D,%7B%22source%22:%22graphene://https://cave.fanc-fly.com/segmentation/table/mar2021_prod%22,%22type%22:%22segmentation_with_graph%22,%22colorSeed%22:1792288153,%22segmentColors%22:%7B%22648518346498254576%22:%22#1fe0f9%22%7D,%22segments%22:[%22648518346498254576%22],%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22,%22mode3d%22:%22lines%22%7D,%22graphOperationMarker%22:[%7B%22annotations%22:[],%22tags%22:[]%7D,%7B%22annotations%22:[],%22tags%22:[]%7D],%22pathFinder%22:%7B%22color%22:%22#ffff00%22,%22pathObject%22:%7B%22annotationPath%22:%7B%22annotations%22:[],%22tags%22:[]%7D,%22hasPath%22:false%7D%7D,%22name%22:%22seg_Mar2021_proofreading%22%7D,%7B%22source%22:%22precomputed://gs://lee-lab_female-adult-nerve-cord/alignmentV4/synapses/postsynapses_May2021%22,%22type%22:%22image%22,%22blend%22:%22default%22,%22shader%22:%22void%20main()%20%7B%20emitRGBA(vec4(1,%200,%201,%20toNormalized(getDataValue())));%20%7D%22,%22shaderControls%22:%7B%7D,%22name%22:%22synapses_May2021%22,%22visible%22:false%7D,%7B%22type%22:%22segmentation%22,%22mesh%22:%22precomputed://gs://zetta_lee_fly_vnc_001_precomputed/vnc1_full_v3align_2/brain_regions%22,%22objectAlpha%22:0.1,%22hideSegmentZero%22:false,%22ignoreSegmentInteractions%22:true,%22segmentColors%22:%7B%221%22:%22#bfbfbf%22,%222%22:%22#d343d6%22%7D,%22segments%22:[%221%22,%222%22],%22skeletonRendering%22:%7B%22mode2d%22:%22lines_and_points%22,%22mode3d%22:%22lines%22%7D,%22name%22:%22volume%20outlines%22%7D],%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:[4.300000190734863,4.300000190734863,45],%22voxelCoordinates%22:[48848.171875,114737.2109375,2690]%7D%7D,%22zoomFactor%22:11.839474231467724%7D,%22perspectiveZoom%22:6704.002738252677,%22showSlices%22:false,%22gpuMemoryLimit%22:4000000000,%22systemMemoryLimit%22:4000000000,%22concurrentDownloads%22:64,%22jsonStateServer%22:%22https://global.daf-apis.com/nglstate/api/v1/post%22,%22selectedLayer%22:%7B%22layer%22:%22seg_Mar2021_proofreading%22,%22visible%22:true%7D,%22layout%22:%22xy-3d%22%7D"
expect_s3_class(sc <- ngl_decode_scene(u), 'ngscene')
expect_s3_class(ngl_decode_scene("https://tinyurl.com/rmr58jpn"), 'ngscene')
expect_s3_class(ngl_decode_scene("https://neuroglancer-demo.appspot.com/#!gs://flyem-user-links/short/2023-08-26.151006.json"), 'ngscene')
expect_s3_class(ngl_decode_scene("https://tinyurl.com/flywirehb2"), 'ngscene')
expect_type(ngl_decode_scene("https://tinyurl.com/flywirehb2", return.json = T), 'character')
})
test_that("we can work round toJSON array issue",{
# This URL only refers to one segment
# toJSON has a problem in
singleton_url="https://neuroglancer-demo.appspot.com/#!%7B%22layers%22:%5B%7B%22source%22:%22brainmaps://772153499790:fafb_v14:fafb14_4nm_split4x_fill2:ffnreseg_whitened_16nm_32nm_4nm%22%2C%22type%22:%22segmentation%22%2C%22segments%22:%5B%223140809165%22%5D%2C%22name%22:%22agglo16_32_4_gt3um%22%7D%5D%2C%22navigation%22:%7B%22pose%22:%7B%22position%22:%7B%22voxelSize%22:%5B8%2C8%2C40%5D%2C%22voxelCoordinates%22:%5B78997%2C25574%2C3600%5D%7D%7D%2C%22zoomFactor%22:13.1%7D%2C%22showAxisLines%22:false%2C%22showDefaultAnnotations%22:false%2C%22perspectiveOrientation%22:%5B0.08082044869661331%2C0.22225624322891235%2C-0.15153835713863373%2C-0.9597428441047668%5D%2C%22perspectiveZoom%22:2382%2C%22showSlices%22:false%2C%22layout%22:%223d%22%7D"
sc2=ngl_decode_scene(singleton_url)
sc2.rt=ngl_decode_scene(ngl_encode_url(sc2), return.json = TRUE)
expect_match(sc2.rt, '"segments":["3140809165"]', fixed = T)
f=system.file("flywire-annotations.json" , package = 'fafbseg')
expect_is(u <- ngl_encode_url(f), 'character')
expect_equal(ngl_encode_url(ngl_decode_scene(u)), u)
# round trip test for a singleton annotation
expect_is(u <- ngl_encode_url(test_path("testdata/flywire-elipse.json")), 'character')
expect_equal(ngl_encode_url(ngl_decode_scene(u)), u)
# alternative way to convert scene to URL
expect_equal(as.character(ngl_decode_scene(u)), u)
# check we use original baseurl when available
fu=flywire_expandurl('https://tinyurl.com/rmr58jpn')
hostname <- function(x) httr::parse_url(x)$hostname
expect_equal(hostname(as.character(ngl_decode_scene(fu))),
hostname(fu))
})
test_that('we can expand neuroglancer URLs without following', {
expect_equal(
flywire_expandurl('https://tinyurl.com/NeckConnective', follow = FALSE),
"https://neuroglancer-demo.appspot.com/#!gs://flyem-user-links/short/NeckConnective.json"
)
})
test_that('we can make a neuroglancer URL', {
catmaid_url <- "https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&yp=170014.98879622458&xp=426584.81386896875&tool=navigator&sid0=2&s0=-1"
expect_match(url <- with_segmentation("flywire31", open_fafb_ngl(catmaid_url, open = F)),
"flywire")
expect_equal(xyzmatrix(ngl_decode_scene(url)),
xyzmatrix(catmaid::catmaid_parse_url(catmaid_url)))
})
test_that('we can print scene/layer summaries', {
releases = eval(formals(choose_segmentation)[['release']])
for (r in releases) {
u=getOption("fafbseg.sampleurl")
sc=ngl_decode_scene(u)
expect_output(with_segmentation(r, print(sc)),
"neuroglancer scene with .* layers")
expect_is(ngl_layers(sc, type=='segmentation'), 'nglayers')
expect_is(ngl_layers(sc, visible & nsegs>0), 'nglayers')
}
})
test_that('we can manipulate layers using +/-', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(sc2 <- sc-c("annotation", "jfrc_mesh_test"), 'ngscene')
expect_equal(length(ngl_layers(sc2)), 2L)
expect_is(sc3 <- sc2+ngl_layers(sc)["jfrc_mesh_test"], 'ngscene')
expect_equal(length(ngl_layers(sc3)), 3L)
})
test_that('we can extract annotations', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(ann <- ngl_layers(sc, 'annotation'), 'nglayers')
expect_equal(ngl_layers(sc, type=='annotation'), ann)
})
test_that('we can colour a scene object', {
f=system.file("flywire-annotations.json" , package = 'fafbseg')
sc=ngl_decode_scene(f)
expect_is(sc2 <- ngl_add_colours(sc, c("720575940616120581"="red")), "ngscene")
expect_equal(sc2$layers$`Production-segmentation_with_graph`$segmentColors,
list(`720575940616120581` = col2hex("red")))
expect_equal(ngl_add_colours(sc, c("red")), sc2)
expect_is(sc3 <- ngl_add_colours(sc2, c("1"="red", "720575940616120581"="green")), "ngscene")
expect_equal(sc3$layers$`Production-segmentation_with_graph`$segmentColors,
list('1' = col2hex('red'), `720575940616120581` = col2hex("green")))
expect_error(ngl_add_colours(sc, c("-1" = "red")), "invalid ids")
expect_error(ngl_add_colours(sc, c("2" = "rhubarb")), "invalid color name 'rhubarb'")
token=try(chunkedgraph_token(), silent = TRUE)
skip_if(inherits(token, "try-error"),
"Skipping live flywire tests")
# FIXME want to skip on mac on ci only
skip_on_os('mac')
u1="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6528186495008768"
u2="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5198787572137984"
u3="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/5673953041317888"
# sequentially build up a data.frame with the colour information
# note that col will be recycled to the same length as the number of segments
colourdf=data.frame(ids=ngl_segments(u1), col='red')
colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u2), col='green'))
colourdf=rbind(colourdf, data.frame(ids=ngl_segments(u3), col='blue'))
colourdf$col=factor(colourdf$col)
# apply that to the first URL
expect_is(sc <- ngl_add_colours(u1, colourdf), 'ngscene')
expect_equal(ngl_segments(sc), colourdf$ids)
})
test_that('we can get blank scene urls', {
expect_s3_class(sc <- ngl_blank_scene(), 'ngscene')
kcid="720575940623755722"
expect_equal(ngl_segments(sc+kcid), kcid)
expect_match(ngl_segmentation(ngl_blank_scene("202004")+1), "ffn1-20200412")
expect_match(ngl_segmentation(ngl_blank_scene("202004", return.url = T)),
"ffn1-20200412")
expect_match(ngl_blank_scene("202004", return.url = T),
baseurl_from_url(
with_segmentation("202004", getOption("fafbseg.sampleurl"))))
})
test_that('we can extract ids from delimited strings',{
expect_equal(flywire_ids('1234, 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('1234, 12345', integer64 = T),
bit64::as.integer64(c("1234", "12345")))
expect_equal(flywire_ids('1234, 12345 ', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids(' 1234 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('\t 1234 \t\n 12345', integer64 = T),
c("1234", "12345"))
expect_equal(flywire_ids('\t fw:1234 \t\n fw:12345', integer64 = T),
c("1234", "12345"))
ids='720575940628529156,720575940621343749,720575940628007172,720575940625455370'
bl=c("720575940628529156", "720575940621343749", "720575940628007172",
"720575940625455370")
expect_equal(flywire_ids(ids), bl)
tf=tempfile('ids', fileext = '.txt')
on.exit(unlink(tf))
writeLines(ids, tf)
expect_equal(flywire_ids(file = tf), bl)
writeLines(bl, tf)
expect_equal(flywire_ids(file = tf), bl)
expect_warning(flywire_ids(1, file = tf), regexp = 'only')
expect_error(flywire_ids(file = tempfile()), regexp = 'file')
})
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