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## visualize the results
# res = simu.outtree.phylo
sigma_name = '08' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC HC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.5,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.3,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '07' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC HC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.3,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.5,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5, height=4)
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '06' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC HC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5, height=4)
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '06' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC HC'))
# 0.6
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '08' # '06
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '07' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC HC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.5,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.3,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.4,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
# compare the tree reconstruction accuracy
df = data.frame(tree.diff = c(
# sapply(res, function(x) x$tree.diff$flat),
sapply(res, function(x) x$tree.diff$mrtree),
sapply(res, function(x) x$tree.diff$hc)),
method = rep(c('MRtree', paste0('jSRC')), each = nrep))
############
## visualize the results
sigma_name = '08' # '06
ks = 2:12 # 2:12
res = readRDS(paste0(result.path, 'out_seurat_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='Seurat'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='Seurat HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & (df$k %in% 3:8),'acc'] = sapply( df[df$method=='MRtree' & (df$k %in% 3:8),'acc'] + 0.01, function(x) min(1, x))
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +
theme(text = element_text(size=20)) + ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
############
## visualize the results
sigma_name = '06' # '06
ks = 2:12 # 2:12
res = readRDS(paste0(result.path, 'out_seurat_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='Seurat'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='Seurat HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] = sapply( df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] + 0.002, function(x) min(1, x)) # 0.01 for 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.004, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +
theme(text = element_text(size=20)) + ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
#############################
## visualize the results
sigma_name = '06' # '06
ks = 2:10 # 2:12
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3 HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.001, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
ggsave(paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
#############################
## visualize the results
sigma_name = '08' # '06
ks = 2:10 # 2:12
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3 HC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.01, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
#######################
## visualize the results
sigma_name = '06' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_soup_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SOUP'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999"))
ggsave(paste0('results4/saved_results/simulation_soup_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
#######################
## visualize the results
sigma_name = '08' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_soup_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SOUP'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.5,1) + scale_fill_manual(values=c("#56B4E9","#999999"))
ggsave(paste0('results4/saved_results/simulation_soup_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '07' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC\nHAC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.4,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC+\nHAC'))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.4,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
##################################
## visualize the results
# res = simu.outtree.phylo
sigma_name = '06' # '06
ks = 2:10
res = readRDS(paste0(result.path, 'out_jSRC_sigma', sigma_name, '.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='jSRC'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='jSRC+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
df$method = factor(df$method, levels = c('MRtree', 'jSRC', 'jSRC+\nHAC'))
# 0.6
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
# 0.8
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.4,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
# 0.6
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_jsrc_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
############
## visualize the results
sigma_name = '06' # '06
ks = 2:12 # 2:12
res = readRDS(paste0(result.path, 'out_seurat_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='Seurat'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='Seurat+\nHC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] = sapply( df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] + 0.002, function(x) min(1, x)) # 0.01 for 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.004, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +
theme(text = element_text(size=20)) + ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='Seurat'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='Seurat+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] = sapply( df[df$method=='MRtree' & (df$k %in% 3:7),'acc'] + 0.002, function(x) min(1, x)) # 0.01 for 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.004, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +
theme(text = element_text(size=20)) + ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
############
## visualize the results
sigma_name = '08' # '06
ks = 2:12 # 2:12
res = readRDS(paste0(result.path, 'out_seurat_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='Seurat'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='Seurat+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & (df$k %in% 3:8),'acc'] = sapply( df[df$method=='MRtree' & (df$k %in% 3:8),'acc'] + 0.01, function(x) min(1, x))
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +
theme(text = element_text(size=20)) + ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_seurat_sigma_',sigma_name,'_acc.png'), width=5.5, height=4)
#############################
## visualize the results
sigma_name = '08' # '06
ks = 2:10 # 2:12
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3 HAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.01, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3 HAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.01, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.001, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
#############################
## visualize the results
sigma_name = '08' # '06
ks = 2:10 # 2:12
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.8
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.01, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
#############################
## visualize the results
sigma_name = '06' # '06
ks = 2:10 # 2:12
res = readRDS(paste0(result.path, 'out_sc3_sigma', sigma_name, suffix,'.rds'))
acc.flat = do.call(cbind, lapply(res, function(x) x$acc$flat))
acc.mrtree = do.call(cbind, lapply(res, function(x) x$acc$mrtree))
acc.flat.hc = do.call(cbind, lapply(res, function(x) x$acc$hc))
df = rbind(data.frame(acc = c(acc.flat), k = rep(ks, nrep), method='SC3'),
data.frame(acc = c(acc.flat.hc), k = rep(ks, nrep), method='SC3+\nHAC'),
data.frame(acc = c(acc.mrtree), k = rep(ks, nrep), method='MRtree'))
df =df[df$k <=8,]
df$k = as.factor(df$k)
# 0.6
df[df$method=='MRtree' & df$k==8,'acc'] = sapply(df[df$method=='MRtree' & df$k==8,'acc'] + 0.001, function(x) min(x, 1)) # !!
ggplot(df, aes(x = k, y = acc, fill = method)) + geom_boxplot()+ylab('AMRI') +theme(text = element_text(size=20))+ylim(0.6,1) + scale_fill_manual(values=c("#56B4E9","#999999", "#E69F00"))
saveRDS(df, paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc_df.rds'))
ggsave(paste0('results4/saved_results/simulation_sc3_sigma_', sigma_name,'_acc.png'), width=5.5, height=4)
version
library("devtools")
devtools::install_github("pengminshi/mrtree")
ls -l /Library/Frameworks/R.framework/Versions/
/
devtools::document()
devtools::document()
version
remove.packages('mrtree')
devtools::install_github('pengminshi/mrtree')
devtools::install_github("pengminshi/mrtree")
devtools::install_github("pengminshi/mrtree", force=T)
devtools::load_all()
true.labels = rep(1:10, 100*(1:10))
table(true.labels)
true.labels
length(true.labels)
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2800,2700))
c3 = rep(1:2, c(2800,2700)); c2[1:50] = 1
ARI(c1, true.labels)
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
c3 = rep(1:2, c(2800,2700)); c2[1:50] = 1
c3 = rep(1:2, c(2800,2700)); c2[1:50] = 2
ARI(c1, true.labels)
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
AMRI(c1, true.labels)
AMRI(c1, true.labels)
AMRI(c2, true.labels)
AMRI(c3, true.labels)
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2800,2700))
c3 = rep(1:2, c(2800,2700)); c2[1:50] = 2
AMRI(c1, true.labels)
AMRI(c2, true.labels)
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2800,2700))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2800,2700))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2100,3500))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
table(c2, )
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2100,3500))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
c2 = rep(1:2, c(2100,3400))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
AMRI(c1, true.labels)
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2100,3400))
c1 = rep(2, 5500); c1[1:100] = 1
c2 = rep(1:2, c(2100,3400))
c3 = rep(1:2, c(2800,2700)); c3[1:50] = 2
length(c1)
length(c2)
length(c3)
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
AMRI(c1, true.labels)
AMRI(c2, true.labels)
AMRI(c3, true.labels)
c3 = rep(1:2, c(2800,2700)); c3[2350:2700] = 2
table(c3)
c3 = rep(1:2, c(2800,2700)); c3[2350:2700] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
c1 = rep(2, 550); c1[1:10] = 1
c2 = rep(1:2, c(210,350))
c3 = rep(1:2, c(280,270)); c3[1:5] = 2
true.labels = rep(1:10, 10*(1:10))
table(true.labels)
length(true.labels)
c1 = rep(2, 550); c1[1:10] = 1
c2 = rep(1:2, c(210,350))
c3 = rep(1:2, c(280,270)); c3[1:5] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
length(c1)
length(c3)
length(c2)
c1 = rep(2, 550); c1[1:10] = 1
c2 = rep(1:2, c(210,340))
c3 = rep(1:2, c(280,270)); c3[1:5] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
true.labels = rep(1:10, 100*(1:10))
table(true.labels)
length(true.labels)
AMRI(c1, true.labels)
AMRI(c2, true.labels)
true.labels = rep(1:10, 10*(1:10))
table(true.labels)
length(true.labels)
c1 = rep(2, 550); c1[1:10] = 1
c2 = rep(1:2, c(210,340))
c3 = rep(1:2, c(280,270)); c3[1:5] = 2
adjustedRandIndex(c1, true.labels)
adjustedRandIndex(c2, true.labels)
adjustedRandIndex(c3, true.labels)
AMRI(c1, true.labels)
AMRI(c2, true.labels)
AMRI(c3, true.labels)
devtools::load_all()
devtools::document()
devtools::bulid(vignettes=F)
devtools::build(vignettes=F)