sourceMultipleData.R
In Hugemiler/ZedXL: Package for data analysis and restriction recovery (selection) via processing of topological analysis files and similarity analysis files
####
# Sourcing multiple data
###
require(mp)
require(ggplot2)
require(ZedXL)
set.seed(102528)
computeproq3 <- F
get_density <- function(x, y, n = 1000) {
dens <- MASS::kde2d(x = x, y = y, n = n)
ix <- findInterval(x, dens$x)
iy <- findInterval(y, dens$y)
ii <- cbind(ix, iy)
return(dens$z[ii])
}
compute.density.centromer <- function(funnelTable) {
centromerX <- sum(funnelTable$projectionX * funnelTable$density)/sum(funnelTable$density)
centromerY <- sum(funnelTable$projectionY * funnelTable$density)/sum(funnelTable$density)
return(c("centromerX" = centromerX, "centromerY" = centromerY))
}
# SALB3.INIT.001
init_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.001/gscore/gscore-TMscore-050.dat'
init_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/loglist.txt'
init_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.001/topolink_observed/'
init_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.001/alignlist.txt'
init_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.001/gscore/compactlog-TMscore.dat'
init_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.001/lovoalign.log'
init_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.001/proq3list.txt'
cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/cryslist.txt'
optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/optlist.txt'
init_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/distance_table.log'
init_modelScores <- compute.model.scores(type = "gscore",
init_gscoreLogPath,
init_lovoalignLogPath,
init_proq3listLocation,
computeproq3)
init_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
init_loglistLocation,
init_topolinkLogsDirectory)
)
)
init_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
init_alignlistPath,
init_compactlogPath,
nmodels = nrow(init_optimumXlinkMirttable))
init_optimumXlinkMirttable <- digest.xlink.mirttable(init_optimumXlinkMirttable)
init_optimumDescript <- ltm::descript(init_optimumXlinkMirttable)
init_globalCronbachAlpha <- init_optimumDescript$alpha[1]
init_restrictionScores <- data.frame(bis = init_optimumDescript$bisCorr,
right = init_optimumDescript$perc[,2],
logit = init_optimumDescript$perc[,3],
alpha = init_optimumDescript$alpha[-1],
deltaAlpha = init_optimumDescript$alpha[2:length(init_optimumDescript$alpha)] - init_globalCronbachAlpha)
init_restrictionScores <- attribute.crys.and.opt(init_restrictionScores, cryslistLocation, optlistLocation)
init_modelDistanceTable <- 1/(init_optimumSimilarityTable)
init_projection.coordinates <- forceScheme(init_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
init_projection.coordinates <- scale(init_projection.coordinates, center = T, scale = T)
init_funnelTable <- data.frame("projectionX" = init_projection.coordinates[,1],
"projectionY" = init_projection.coordinates[,2],
"tmscore" = init_modelScores$`TM-Score`,
"density" = get_density(x = init_projection.coordinates[,1], y = init_projection.coordinates[,2]))
init_densityCentromer <- compute.density.centromer(init_funnelTable)
# First iteration
first_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/gscore/gscore-TMscore-050.dat'
first_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/loglist.txt'
first_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/topolink_observed/'
first_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/alignlist.txt'
first_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/gscore/compactlog-TMscore.dat'
first_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/lovoalign.log'
first_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/proq3list.txt'
first_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/cryslist.txt'
first_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/optlist.txt'
first_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/distance_table.log'
first_modelScores <- compute.model.scores(type = "gscore",
first_gscoreLogPath,
first_lovoalignLogPath,
first_proq3listLocation,
computeproq3)
first_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
first_loglistLocation,
first_topolinkLogsDirectory)
)
)
first_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
first_alignlistPath,
first_compactlogPath,
nmodels = nrow(first_optimumXlinkMirttable))
first_optimumXlinkMirttable <- digest.xlink.mirttable(first_optimumXlinkMirttable)
first_optimumDescript <- ltm::descript(first_optimumXlinkMirttable)
first_globalCronbachAlpha <- first_optimumDescript$alpha[1]
first_restrictionScores <- data.frame(bis = first_optimumDescript$bisCorr,
right = first_optimumDescript$perc[,2],
logit = first_optimumDescript$perc[,3],
alpha = first_optimumDescript$alpha[-1],
deltaAlpha = first_optimumDescript$alpha[2:length(first_optimumDescript$alpha)] - first_globalCronbachAlpha)
first_restrictionScores <- attribute.crys.and.opt(first_restrictionScores, cryslistLocation, optlistLocation)
first_modelDistanceTable <- 1/(first_optimumSimilarityTable)
first_projection.coordinates <- forceScheme(first_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
first_projection.coordinates <- scale(first_projection.coordinates, center = T, scale = T)
first_funnelTable <- data.frame("projectionX" = first_projection.coordinates[,1],
"projectionY" = first_projection.coordinates[,2],
"tmscore" = first_modelScores$`TM-Score`,
"density" = get_density(x = first_projection.coordinates[,1], y = first_projection.coordinates[,2]))
first_densityCentromer <- compute.density.centromer(first_funnelTable)
# Second Iteration
second_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/gscore/gscore-TMscore-050.dat'
second_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/loglist.txt'
second_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/topolink_observed/'
second_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/alignlist.txt'
second_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/gscore/compactlog-TMscore.dat'
second_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/lovoalign.log'
second_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/proq3list.txt'
second_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/cryslist.txt'
second_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/optlist.txt'
second_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/distance_table.log'
second_modelScores <- compute.model.scores(type = "gscore",
second_gscoreLogPath,
second_lovoalignLogPath,
second_proq3listLocation,
computeproq3)
second_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
second_loglistLocation,
second_topolinkLogsDirectory)
)
)
second_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
second_alignlistPath,
second_compactlogPath,
nmodels = nrow(second_optimumXlinkMirttable))
second_optimumXlinkMirttable <- digest.xlink.mirttable(second_optimumXlinkMirttable)
second_optimumDescript <- ltm::descript(second_optimumXlinkMirttable)
second_globalCronbachAlpha <- second_optimumDescript$alpha[1]
second_restrictionScores <- data.frame(bis = second_optimumDescript$bisCorr,
right = second_optimumDescript$perc[,2],
logit = second_optimumDescript$perc[,3],
alpha = second_optimumDescript$alpha[-1],
deltaAlpha = second_optimumDescript$alpha[2:length(second_optimumDescript$alpha)] - second_globalCronbachAlpha)
second_restrictionScores <- attribute.crys.and.opt(second_restrictionScores, cryslistLocation, optlistLocation)
second_modelDistanceTable <- 1/(second_optimumSimilarityTable)
second_projection.coordinates <- forceScheme(second_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
second_projection.coordinates <- scale(second_projection.coordinates, center = T, scale = T)
second_funnelTable <- data.frame("projectionX" = second_projection.coordinates[,1],
"projectionY" = second_projection.coordinates[,2],
"tmscore" = second_modelScores$`TM-Score`,
"density" = get_density(x = second_projection.coordinates[,1], y = second_projection.coordinates[,2]))
second_densityCentromer <- compute.density.centromer(second_funnelTable)
# Third Iteration
third_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/gscore/gscore-TMscore-050.dat'
third_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/loglist.txt'
third_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/topolink_observed/'
third_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/alignlist.txt'
third_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/gscore/compactlog-TMscore.dat'
third_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/lovoalign.log'
third_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/proq3list.txt'
third_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/cryslist.txt'
third_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/optlist.txt'
third_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/distance_table.log'
third_modelScores <- compute.model.scores(type = "gscore",
third_gscoreLogPath,
third_lovoalignLogPath,
third_proq3listLocation,
computeproq3)
third_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
third_loglistLocation,
third_topolinkLogsDirectory)
)
)
third_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
third_alignlistPath,
third_compactlogPath,
nmodels = nrow(third_optimumXlinkMirttable))
third_optimumXlinkMirttable <- digest.xlink.mirttable(third_optimumXlinkMirttable)
third_optimumDescript <- ltm::descript(third_optimumXlinkMirttable)
third_globalCronbachAlpha <- third_optimumDescript$alpha[1]
third_restrictionScores <- data.frame(bis = third_optimumDescript$bisCorr,
right = third_optimumDescript$perc[,2],
logit = third_optimumDescript$perc[,3],
alpha = third_optimumDescript$alpha[-1],
deltaAlpha = third_optimumDescript$alpha[2:length(third_optimumDescript$alpha)] - third_globalCronbachAlpha)
third_restrictionScores <- attribute.crys.and.opt(third_restrictionScores, cryslistLocation, optlistLocation)
third_modelDistanceTable <- 1/(third_optimumSimilarityTable)
third_projection.coordinates <- forceScheme(third_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
third_projection.coordinates <- scale(third_projection.coordinates, center = T, scale = T)
third_funnelTable <- data.frame("projectionX" = third_projection.coordinates[,1],
"projectionY" = third_projection.coordinates[,2],
"tmscore" = third_modelScores$`TM-Score`,
"density" = get_density(x = third_projection.coordinates[,1], y = third_projection.coordinates[,2]))
third_densityCentromer <- compute.density.centromer(third_funnelTable)
# Fourth Iteration
fourth_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/gscore/gscore-TMscore-050.dat'
fourth_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/loglist.txt'
fourth_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/topolink_observed/'
fourth_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/alignlist.txt'
fourth_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/gscore/compactlog-TMscore.dat'
fourth_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/lovoalign.log'
fourth_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/proq3list.txt'
fourth_modelScores <- compute.model.scores(type = "gscore",
fourth_gscoreLogPath,
fourth_lovoalignLogPath,
fourth_proq3listLocation,
computeproq3)
fourth_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
fourth_loglistLocation,
fourth_topolinkLogsDirectory)
)
)
fourth_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
fourth_alignlistPath,
fourth_compactlogPath,
nmodels = nrow(fourth_optimumXlinkMirttable))
fourth_optimumXlinkMirttable <- digest.xlink.mirttable(fourth_optimumXlinkMirttable)
fourth_optimumDescript <- ltm::descript(fourth_optimumXlinkMirttable)
fourth_globalCronbachAlpha <- fourth_optimumDescript$alpha[1]
fourth_restrictionScores <- data.frame(bis = fourth_optimumDescript$bisCorr,
right = fourth_optimumDescript$perc[,2],
logit = fourth_optimumDescript$perc[,3],
alpha = fourth_optimumDescript$alpha[-1],
deltaAlpha = fourth_optimumDescript$alpha[2:length(fourth_optimumDescript$alpha)] - fourth_globalCronbachAlpha)
fourth_restrictionScores <- attribute.crys.and.opt(fourth_restrictionScores, cryslistLocation, optlistLocation)
fourth_modelDistanceTable <- 1/(fourth_optimumSimilarityTable)
fourth_projection.coordinates <- forceScheme(fourth_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
fourth_projection.coordinates <- scale(fourth_projection.coordinates, center = T, scale = T)
fourth_funnelTable <- data.frame("projectionX" = fourth_projection.coordinates[,1],
"projectionY" = fourth_projection.coordinates[,2],
"tmscore" = fourth_modelScores$`TM-Score`,
"density" = get_density(x = fourth_projection.coordinates[,1], y = fourth_projection.coordinates[,2]))
fourth_densityCentromer <- compute.density.centromer(fourth_funnelTable)
# Fifth iteration
fifth_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/gscore/gscore-TMscore-050.dat'
fifth_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/loglist.txt'
fifth_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/topolink_observed/'
fifth_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/alignlist.txt'
fifth_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/gscore/compactlog-TMscore.dat'
fifth_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/lovoalign.log'
fifth_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/proq3list.txt'
fifth_modelScores <- compute.model.scores(type = "gscore",
fifth_gscoreLogPath,
fifth_lovoalignLogPath,
fifth_proq3listLocation,
computeproq3)
fifth_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
fifth_loglistLocation,
fifth_topolinkLogsDirectory)
)
)
fifth_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
fifth_alignlistPath,
fifth_compactlogPath,
nmodels = nrow(fifth_optimumXlinkMirttable))
fifth_optimumXlinkMirttable <- digest.xlink.mirttable(fifth_optimumXlinkMirttable)
fifth_optimumDescript <- ltm::descript(fifth_optimumXlinkMirttable)
fifth_globalCronbachAlpha <- fifth_optimumDescript$alpha[1]
fifth_restrictionScores <- data.frame(bis = fifth_optimumDescript$bisCorr,
right = fifth_optimumDescript$perc[,2],
logit = fifth_optimumDescript$perc[,3],
alpha = fifth_optimumDescript$alpha[-1],
deltaAlpha = fifth_optimumDescript$alpha[2:length(fifth_optimumDescript$alpha)] - fifth_globalCronbachAlpha)
fifth_restrictionScores <- attribute.crys.and.opt(fifth_restrictionScores, cryslistLocation, optlistLocation)
fifth_modelDistanceTable <- 1/(fifth_optimumSimilarityTable)
fifth_projection.coordinates <- forceScheme(fifth_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
fifth_projection.coordinates <- scale(fifth_projection.coordinates, center = T, scale = T)
fifth_funnelTable <- data.frame("projectionX" = fifth_projection.coordinates[,1],
"projectionY" = fifth_projection.coordinates[,2],
"tmscore" = fifth_modelScores$`TM-Score`,
"density" = get_density(x = fifth_projection.coordinates[,1], y = fifth_projection.coordinates[,2]))
fifth_densityCentromer <- compute.density.centromer(fifth_funnelTable)
## Collective Plots
### Tm_Score
# Initial Modeling:
ggplot(init_funnelTable[order(init_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = init_densityCentromer["centromerX"], y = init_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# First Iteration:
ggplot(first_funnelTable[order(first_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = first_densityCentromer["centromerX"], y = first_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Second Iteration:
ggplot(second_funnelTable[order(second_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = second_densityCentromer["centromerX"], y = second_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Third Iteration:
ggplot(third_funnelTable[order(third_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = third_densityCentromer["centromerX"], y = third_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Fourth Iteration:
ggplot(fourth_funnelTable[order(fourth_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fourth_densityCentromer["centromerX"], y = fourth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Fifth Iteration:
ggplot(fifth_funnelTable[order(fifth_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
## Combination of all modelings:
combined_funnelTable <- rbind(init_funnelTable,
first_funnelTable,
second_funnelTable,
third_funnelTable,
fourth_funnelTable,
fifth_funnelTable)
combined_funnelTable$density <- get_density(x = combined_funnelTable$projectionX, y = combined_funnelTable$projectionY)
ggplot(combined_funnelTable[order(combined_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.2, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
ggplot(combined_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.2, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
### Density
# Initial Modeling:
ggplot(init_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = init_densityCentromer["centromerX"], y = init_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
# First Iteration:
ggplot(first_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = first_densityCentromer["centromerX"], y = first_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
# First Iteration:
ggplot(second_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = second_densityCentromer["centromerX"], y = second_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(third_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.9, size = 3) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = third_densityCentromer["centromerX"], y = third_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(fourth_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fourth_densityCentromer["centromerX"], y = fourth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(fifth_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
### Baripapa
bigfunnel <- read.table('/home/guilherme/logs/2018-10-07/coordinates.txt')
bigfunnelScores <- read.table('/home/guilherme/logs/2018-10-07/lovoalign.log')
bigfunnel <- scale(bigfunnel, center = T, scale = T)
bigfunnelTable <- data.frame("projectionX" = bigfunnel[,1],
"projectionY" = bigfunnel[,2],
"tmscore" = bigfunnelScores$V3,
"density" = get_density(x = bigfunnel[,1], y = bigfunnel[,2]))
bigfunnelCentromer <- compute.density.centromer(bigfunnelTable)
ggplot(bigfunnelTable[order(bigfunnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = bigfunnelCentromer["centromerX"], y = bigfunnelCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.85), direction = -1) + theme_bw()
ggplot(bigfunnelTable[order(bigfunnelTable$density),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = bigfunnelCentromer["centromerX"], y = bigfunnelCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
library(plot3D)
library(plotly)
scatter3D(bigfunnelTable$projectionX,
bigfunnelTable$projectionY,
-bigfunnelTable$tmscore, phi = 0, bty ="b2")
plot_ly(bigfunnelTable,
x = ~projectionX,
y = ~projectionY,
z = ~-tmscore,
marker=list(
color=~-tmscore,
colorbar=list(
title='Colorbar'
),
colorscale='viridis',
reversescale = F
)) %>%
add_markers()
# Animation
animationTable <- bigfunnelTable
animationTable$frame <- c(rep(1, 5000), rep(2, 5000), rep(3, 5000), rep(4, 5000), rep(5, 5000), rep(6, 5000))
scatter3D(animationTable[animationTable$frame == 1, ]$projectionX,
animationTable[animationTable$frame == 1, ]$projectionY,
-animationTable[animationTable$frame == 1, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 2, ]$projectionX,
animationTable[animationTable$frame == 2, ]$projectionY,
-animationTable[animationTable$frame == 2, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 3, ]$projectionX,
animationTable[animationTable$frame == 3, ]$projectionY,
-animationTable[animationTable$frame == 3, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 4, ]$projectionX,
animationTable[animationTable$frame == 4, ]$projectionY,
-animationTable[animationTable$frame == 4, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 5, ]$projectionX,
animationTable[animationTable$frame == 5, ]$projectionY,
-animationTable[animationTable$frame == 5, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 6, ]$projectionX,
animationTable[animationTable$frame == 6, ]$projectionY,
-animationTable[animationTable$frame == 6, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(bigfunnelTable$projectionX,
bigfunnelTable$projectionY,
-bigfunnelTable$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
animationTable <- do.call(rbind, animationTable)
funnelPlot <- plot_ly(animationTable,
x = ~projectionX,
y = ~projectionY,
z = ~-tmscore,
frame = ~frame,
color = ~-tmscore,
colors = viridis(10)) %>%
add_markers() %>%
animation_opts(frame = 5000,
transition = 2000,
easing = "elastic",
redraw = F)
funnelPlot
Sys.setenv("plotly_username"="GuilhermeFahurBottino")
Sys.setenv("plotly_api_key"="le7AUsxZNFDYFKUPEQ0Y")
chart_link = api_create(funnelPlot, filename="animations-animation-options")
htmlwidgets::saveWidget(widget=funnelPlot,"index.html")
library(plotly)
library(htmlwidgets)
Hugemiler/ZedXL documentation built on Oct. 6, 2019, 11:14 p.m.
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####
# Sourcing multiple data
###
require(mp)
require(ggplot2)
require(ZedXL)
set.seed(102528)
computeproq3 <- F
get_density <- function(x, y, n = 1000) {
dens <- MASS::kde2d(x = x, y = y, n = n)
ix <- findInterval(x, dens$x)
iy <- findInterval(y, dens$y)
ii <- cbind(ix, iy)
return(dens$z[ii])
}
compute.density.centromer <- function(funnelTable) {
centromerX <- sum(funnelTable$projectionX * funnelTable$density)/sum(funnelTable$density)
centromerY <- sum(funnelTable$projectionY * funnelTable$density)/sum(funnelTable$density)
return(c("centromerX" = centromerX, "centromerY" = centromerY))
}
# SALB3.INIT.001
init_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.001/gscore/gscore-TMscore-050.dat'
init_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/loglist.txt'
init_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.001/topolink_observed/'
init_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.001/alignlist.txt'
init_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.001/gscore/compactlog-TMscore.dat'
init_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.001/lovoalign.log'
init_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.001/proq3list.txt'
cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/cryslist.txt'
optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/optlist.txt'
init_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.001/utility/distance_table.log'
init_modelScores <- compute.model.scores(type = "gscore",
init_gscoreLogPath,
init_lovoalignLogPath,
init_proq3listLocation,
computeproq3)
init_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
init_loglistLocation,
init_topolinkLogsDirectory)
)
)
init_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
init_alignlistPath,
init_compactlogPath,
nmodels = nrow(init_optimumXlinkMirttable))
init_optimumXlinkMirttable <- digest.xlink.mirttable(init_optimumXlinkMirttable)
init_optimumDescript <- ltm::descript(init_optimumXlinkMirttable)
init_globalCronbachAlpha <- init_optimumDescript$alpha[1]
init_restrictionScores <- data.frame(bis = init_optimumDescript$bisCorr,
right = init_optimumDescript$perc[,2],
logit = init_optimumDescript$perc[,3],
alpha = init_optimumDescript$alpha[-1],
deltaAlpha = init_optimumDescript$alpha[2:length(init_optimumDescript$alpha)] - init_globalCronbachAlpha)
init_restrictionScores <- attribute.crys.and.opt(init_restrictionScores, cryslistLocation, optlistLocation)
init_modelDistanceTable <- 1/(init_optimumSimilarityTable)
init_projection.coordinates <- forceScheme(init_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
init_projection.coordinates <- scale(init_projection.coordinates, center = T, scale = T)
init_funnelTable <- data.frame("projectionX" = init_projection.coordinates[,1],
"projectionY" = init_projection.coordinates[,2],
"tmscore" = init_modelScores$`TM-Score`,
"density" = get_density(x = init_projection.coordinates[,1], y = init_projection.coordinates[,2]))
init_densityCentromer <- compute.density.centromer(init_funnelTable)
# First iteration
first_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/gscore/gscore-TMscore-050.dat'
first_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/loglist.txt'
first_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/topolink_observed/'
first_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/alignlist.txt'
first_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/gscore/compactlog-TMscore.dat'
first_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/lovoalign.log'
first_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/proq3list.txt'
first_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/cryslist.txt'
first_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/optlist.txt'
first_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.002/utility/distance_table.log'
first_modelScores <- compute.model.scores(type = "gscore",
first_gscoreLogPath,
first_lovoalignLogPath,
first_proq3listLocation,
computeproq3)
first_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
first_loglistLocation,
first_topolinkLogsDirectory)
)
)
first_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
first_alignlistPath,
first_compactlogPath,
nmodels = nrow(first_optimumXlinkMirttable))
first_optimumXlinkMirttable <- digest.xlink.mirttable(first_optimumXlinkMirttable)
first_optimumDescript <- ltm::descript(first_optimumXlinkMirttable)
first_globalCronbachAlpha <- first_optimumDescript$alpha[1]
first_restrictionScores <- data.frame(bis = first_optimumDescript$bisCorr,
right = first_optimumDescript$perc[,2],
logit = first_optimumDescript$perc[,3],
alpha = first_optimumDescript$alpha[-1],
deltaAlpha = first_optimumDescript$alpha[2:length(first_optimumDescript$alpha)] - first_globalCronbachAlpha)
first_restrictionScores <- attribute.crys.and.opt(first_restrictionScores, cryslistLocation, optlistLocation)
first_modelDistanceTable <- 1/(first_optimumSimilarityTable)
first_projection.coordinates <- forceScheme(first_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
first_projection.coordinates <- scale(first_projection.coordinates, center = T, scale = T)
first_funnelTable <- data.frame("projectionX" = first_projection.coordinates[,1],
"projectionY" = first_projection.coordinates[,2],
"tmscore" = first_modelScores$`TM-Score`,
"density" = get_density(x = first_projection.coordinates[,1], y = first_projection.coordinates[,2]))
first_densityCentromer <- compute.density.centromer(first_funnelTable)
# Second Iteration
second_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/gscore/gscore-TMscore-050.dat'
second_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/loglist.txt'
second_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/topolink_observed/'
second_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/alignlist.txt'
second_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/gscore/compactlog-TMscore.dat'
second_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/lovoalign.log'
second_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/proq3list.txt'
second_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/cryslist.txt'
second_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/optlist.txt'
second_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.003/utility/distance_table.log'
second_modelScores <- compute.model.scores(type = "gscore",
second_gscoreLogPath,
second_lovoalignLogPath,
second_proq3listLocation,
computeproq3)
second_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
second_loglistLocation,
second_topolinkLogsDirectory)
)
)
second_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
second_alignlistPath,
second_compactlogPath,
nmodels = nrow(second_optimumXlinkMirttable))
second_optimumXlinkMirttable <- digest.xlink.mirttable(second_optimumXlinkMirttable)
second_optimumDescript <- ltm::descript(second_optimumXlinkMirttable)
second_globalCronbachAlpha <- second_optimumDescript$alpha[1]
second_restrictionScores <- data.frame(bis = second_optimumDescript$bisCorr,
right = second_optimumDescript$perc[,2],
logit = second_optimumDescript$perc[,3],
alpha = second_optimumDescript$alpha[-1],
deltaAlpha = second_optimumDescript$alpha[2:length(second_optimumDescript$alpha)] - second_globalCronbachAlpha)
second_restrictionScores <- attribute.crys.and.opt(second_restrictionScores, cryslistLocation, optlistLocation)
second_modelDistanceTable <- 1/(second_optimumSimilarityTable)
second_projection.coordinates <- forceScheme(second_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
second_projection.coordinates <- scale(second_projection.coordinates, center = T, scale = T)
second_funnelTable <- data.frame("projectionX" = second_projection.coordinates[,1],
"projectionY" = second_projection.coordinates[,2],
"tmscore" = second_modelScores$`TM-Score`,
"density" = get_density(x = second_projection.coordinates[,1], y = second_projection.coordinates[,2]))
second_densityCentromer <- compute.density.centromer(second_funnelTable)
# Third Iteration
third_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/gscore/gscore-TMscore-050.dat'
third_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/loglist.txt'
third_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/topolink_observed/'
third_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/alignlist.txt'
third_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/gscore/compactlog-TMscore.dat'
third_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/lovoalign.log'
third_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/proq3list.txt'
third_cryslistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/cryslist.txt'
third_optlistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/optlist.txt'
third_distanceTableLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.004/utility/distance_table.log'
third_modelScores <- compute.model.scores(type = "gscore",
third_gscoreLogPath,
third_lovoalignLogPath,
third_proq3listLocation,
computeproq3)
third_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
third_loglistLocation,
third_topolinkLogsDirectory)
)
)
third_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
third_alignlistPath,
third_compactlogPath,
nmodels = nrow(third_optimumXlinkMirttable))
third_optimumXlinkMirttable <- digest.xlink.mirttable(third_optimumXlinkMirttable)
third_optimumDescript <- ltm::descript(third_optimumXlinkMirttable)
third_globalCronbachAlpha <- third_optimumDescript$alpha[1]
third_restrictionScores <- data.frame(bis = third_optimumDescript$bisCorr,
right = third_optimumDescript$perc[,2],
logit = third_optimumDescript$perc[,3],
alpha = third_optimumDescript$alpha[-1],
deltaAlpha = third_optimumDescript$alpha[2:length(third_optimumDescript$alpha)] - third_globalCronbachAlpha)
third_restrictionScores <- attribute.crys.and.opt(third_restrictionScores, cryslistLocation, optlistLocation)
third_modelDistanceTable <- 1/(third_optimumSimilarityTable)
third_projection.coordinates <- forceScheme(third_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
third_projection.coordinates <- scale(third_projection.coordinates, center = T, scale = T)
third_funnelTable <- data.frame("projectionX" = third_projection.coordinates[,1],
"projectionY" = third_projection.coordinates[,2],
"tmscore" = third_modelScores$`TM-Score`,
"density" = get_density(x = third_projection.coordinates[,1], y = third_projection.coordinates[,2]))
third_densityCentromer <- compute.density.centromer(third_funnelTable)
# Fourth Iteration
fourth_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/gscore/gscore-TMscore-050.dat'
fourth_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/loglist.txt'
fourth_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/topolink_observed/'
fourth_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/alignlist.txt'
fourth_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/gscore/compactlog-TMscore.dat'
fourth_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/lovoalign.log'
fourth_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.005/proq3list.txt'
fourth_modelScores <- compute.model.scores(type = "gscore",
fourth_gscoreLogPath,
fourth_lovoalignLogPath,
fourth_proq3listLocation,
computeproq3)
fourth_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
fourth_loglistLocation,
fourth_topolinkLogsDirectory)
)
)
fourth_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
fourth_alignlistPath,
fourth_compactlogPath,
nmodels = nrow(fourth_optimumXlinkMirttable))
fourth_optimumXlinkMirttable <- digest.xlink.mirttable(fourth_optimumXlinkMirttable)
fourth_optimumDescript <- ltm::descript(fourth_optimumXlinkMirttable)
fourth_globalCronbachAlpha <- fourth_optimumDescript$alpha[1]
fourth_restrictionScores <- data.frame(bis = fourth_optimumDescript$bisCorr,
right = fourth_optimumDescript$perc[,2],
logit = fourth_optimumDescript$perc[,3],
alpha = fourth_optimumDescript$alpha[-1],
deltaAlpha = fourth_optimumDescript$alpha[2:length(fourth_optimumDescript$alpha)] - fourth_globalCronbachAlpha)
fourth_restrictionScores <- attribute.crys.and.opt(fourth_restrictionScores, cryslistLocation, optlistLocation)
fourth_modelDistanceTable <- 1/(fourth_optimumSimilarityTable)
fourth_projection.coordinates <- forceScheme(fourth_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
fourth_projection.coordinates <- scale(fourth_projection.coordinates, center = T, scale = T)
fourth_funnelTable <- data.frame("projectionX" = fourth_projection.coordinates[,1],
"projectionY" = fourth_projection.coordinates[,2],
"tmscore" = fourth_modelScores$`TM-Score`,
"density" = get_density(x = fourth_projection.coordinates[,1], y = fourth_projection.coordinates[,2]))
fourth_densityCentromer <- compute.density.centromer(fourth_funnelTable)
# Fifth iteration
fifth_gscoreLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/gscore/gscore-TMscore-050.dat'
fifth_loglistLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/loglist.txt'
fifth_topolinkLogsDirectory = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/topolink_observed/'
fifth_alignlistPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/alignlist.txt'
fifth_compactlogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/gscore/compactlog-TMscore.dat'
fifth_lovoalignLogPath = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/lovoalign.log'
fifth_proq3listLocation = '/home/guilherme/datasets/SALB3.NOCST.BISCORE_PROQ3_TM.006/proq3list.txt'
fifth_modelScores <- compute.model.scores(type = "gscore",
fifth_gscoreLogPath,
fifth_lovoalignLogPath,
fifth_proq3listLocation,
computeproq3)
fifth_optimumXlinkMirttable <- create.xlink.mirttable(
prepare.topolink.logs(
read.topolink.output(mode,
fifth_loglistLocation,
fifth_topolinkLogsDirectory)
)
)
fifth_optimumSimilarityTable <- create.dissimilarity.matrix(mode = "similarity",
diagonal = 1,
fifth_alignlistPath,
fifth_compactlogPath,
nmodels = nrow(fifth_optimumXlinkMirttable))
fifth_optimumXlinkMirttable <- digest.xlink.mirttable(fifth_optimumXlinkMirttable)
fifth_optimumDescript <- ltm::descript(fifth_optimumXlinkMirttable)
fifth_globalCronbachAlpha <- fifth_optimumDescript$alpha[1]
fifth_restrictionScores <- data.frame(bis = fifth_optimumDescript$bisCorr,
right = fifth_optimumDescript$perc[,2],
logit = fifth_optimumDescript$perc[,3],
alpha = fifth_optimumDescript$alpha[-1],
deltaAlpha = fifth_optimumDescript$alpha[2:length(fifth_optimumDescript$alpha)] - fifth_globalCronbachAlpha)
fifth_restrictionScores <- attribute.crys.and.opt(fifth_restrictionScores, cryslistLocation, optlistLocation)
fifth_modelDistanceTable <- 1/(fifth_optimumSimilarityTable)
fifth_projection.coordinates <- forceScheme(fifth_modelDistanceTable,
Y = NULL,
#max.iter = ,
tol = 1e-04,
#fraction = 8,
eps = 1e-05)
fifth_projection.coordinates <- scale(fifth_projection.coordinates, center = T, scale = T)
fifth_funnelTable <- data.frame("projectionX" = fifth_projection.coordinates[,1],
"projectionY" = fifth_projection.coordinates[,2],
"tmscore" = fifth_modelScores$`TM-Score`,
"density" = get_density(x = fifth_projection.coordinates[,1], y = fifth_projection.coordinates[,2]))
fifth_densityCentromer <- compute.density.centromer(fifth_funnelTable)
## Collective Plots
### Tm_Score
# Initial Modeling:
ggplot(init_funnelTable[order(init_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = init_densityCentromer["centromerX"], y = init_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# First Iteration:
ggplot(first_funnelTable[order(first_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = first_densityCentromer["centromerX"], y = first_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Second Iteration:
ggplot(second_funnelTable[order(second_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = second_densityCentromer["centromerX"], y = second_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Third Iteration:
ggplot(third_funnelTable[order(third_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = third_densityCentromer["centromerX"], y = third_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Fourth Iteration:
ggplot(fourth_funnelTable[order(fourth_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fourth_densityCentromer["centromerX"], y = fourth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
# Fifth Iteration:
ggplot(fifth_funnelTable[order(fifth_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
## Combination of all modelings:
combined_funnelTable <- rbind(init_funnelTable,
first_funnelTable,
second_funnelTable,
third_funnelTable,
fourth_funnelTable,
fifth_funnelTable)
combined_funnelTable$density <- get_density(x = combined_funnelTable$projectionX, y = combined_funnelTable$projectionY)
ggplot(combined_funnelTable[order(combined_funnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.2, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.8), direction = -1) + theme_bw()
ggplot(combined_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.2, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
### Density
# Initial Modeling:
ggplot(init_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = init_densityCentromer["centromerX"], y = init_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
# First Iteration:
ggplot(first_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = first_densityCentromer["centromerX"], y = first_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
# First Iteration:
ggplot(second_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = second_densityCentromer["centromerX"], y = second_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(third_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.9, size = 3) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = third_densityCentromer["centromerX"], y = third_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(fourth_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fourth_densityCentromer["centromerX"], y = fourth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
ggplot(fifth_funnelTable, aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = fifth_densityCentromer["centromerX"], y = fifth_densityCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
### Baripapa
bigfunnel <- read.table('/home/guilherme/logs/2018-10-07/coordinates.txt')
bigfunnelScores <- read.table('/home/guilherme/logs/2018-10-07/lovoalign.log')
bigfunnel <- scale(bigfunnel, center = T, scale = T)
bigfunnelTable <- data.frame("projectionX" = bigfunnel[,1],
"projectionY" = bigfunnel[,2],
"tmscore" = bigfunnelScores$V3,
"density" = get_density(x = bigfunnel[,1], y = bigfunnel[,2]))
bigfunnelCentromer <- compute.density.centromer(bigfunnelTable)
ggplot(bigfunnelTable[order(bigfunnelTable$tmscore),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = tmscore), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = bigfunnelCentromer["centromerX"], y = bigfunnelCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(limits = c(0.1, 0.85), direction = -1) + theme_bw()
ggplot(bigfunnelTable[order(bigfunnelTable$density),], aes(x = projectionX, y = projectionY)) +
geom_point(aes(color = density), alpha = 0.5, size = 2.5) +
xlim(-3, 3) + ylim(-3,3) +
annotate("point", x = bigfunnelCentromer["centromerX"], y = bigfunnelCentromer["centromerY"], size = 10,color = "orange", alpha = 0.5) +
scale_colour_viridis_c(direction = -1) + theme_bw()
library(plot3D)
library(plotly)
scatter3D(bigfunnelTable$projectionX,
bigfunnelTable$projectionY,
-bigfunnelTable$tmscore, phi = 0, bty ="b2")
plot_ly(bigfunnelTable,
x = ~projectionX,
y = ~projectionY,
z = ~-tmscore,
marker=list(
color=~-tmscore,
colorbar=list(
title='Colorbar'
),
colorscale='viridis',
reversescale = F
)) %>%
add_markers()
# Animation
animationTable <- bigfunnelTable
animationTable$frame <- c(rep(1, 5000), rep(2, 5000), rep(3, 5000), rep(4, 5000), rep(5, 5000), rep(6, 5000))
scatter3D(animationTable[animationTable$frame == 1, ]$projectionX,
animationTable[animationTable$frame == 1, ]$projectionY,
-animationTable[animationTable$frame == 1, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 2, ]$projectionX,
animationTable[animationTable$frame == 2, ]$projectionY,
-animationTable[animationTable$frame == 2, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 3, ]$projectionX,
animationTable[animationTable$frame == 3, ]$projectionY,
-animationTable[animationTable$frame == 3, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 4, ]$projectionX,
animationTable[animationTable$frame == 4, ]$projectionY,
-animationTable[animationTable$frame == 4, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 5, ]$projectionX,
animationTable[animationTable$frame == 5, ]$projectionY,
-animationTable[animationTable$frame == 5, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(animationTable[animationTable$frame == 6, ]$projectionX,
animationTable[animationTable$frame == 6, ]$projectionY,
-animationTable[animationTable$frame == 6, ]$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
scatter3D(bigfunnelTable$projectionX,
bigfunnelTable$projectionY,
-bigfunnelTable$tmscore, phi = 0, bty ="b2",
xlab = "Projection X", ylab = "Projection Y", zlab = "-(TM-Score)",
col = viridis(100))
animationTable <- do.call(rbind, animationTable)
funnelPlot <- plot_ly(animationTable,
x = ~projectionX,
y = ~projectionY,
z = ~-tmscore,
frame = ~frame,
color = ~-tmscore,
colors = viridis(10)) %>%
add_markers() %>%
animation_opts(frame = 5000,
transition = 2000,
easing = "elastic",
redraw = F)
funnelPlot
Sys.setenv("plotly_username"="GuilhermeFahurBottino")
Sys.setenv("plotly_api_key"="le7AUsxZNFDYFKUPEQ0Y")
chart_link = api_create(funnelPlot, filename="animations-animation-options")
htmlwidgets::saveWidget(widget=funnelPlot,"index.html")
library(plotly)
library(htmlwidgets)
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