filter out 0s

src/harpy/reports/HapCut2.Rmd

@@ -45,7 +45,7 @@ script src = "https://ajax.googleapis.com/ajax/libs/jquery/3.7.1/jquery.min.js"
 ```
 
 ```{r echo= FALSE, message = FALSE, warning = FALSE}
-#file <- "/home/pdimens/Documents/harpy/Phase/reports/blocks.summary.gz"
+#file <- "~/blocks.summary.gz"
 file <- snakemake@input[[1]]
 df <- read.table(
   file, header = T,
@@ -56,7 +56,7 @@ if(nrow(df) < 1){
   knitr::knit_exit()
 }
 df$pos_end <- df$pos_start + df$block_length
-df <- df[, c(1,2,3,4,6,5)]
+df <- df[df$block_length > 0, c(1,2,3,4,6,5)]
 levels(df$sample) <- basename(levels(df$sample))
 ```
 
@@ -89,7 +89,8 @@ some of the information in the `.blocks` files that were collated in this report
 This page shows general and per-contig information. You may click the plots to
 expand them in your browser. Clicking them again will exit from the zoomed pop-up
 window. The `Per-Sample Stats` tab in the navigation bar above will show you
-statistics relating to haplotypes on the per-sample level.
+statistics relating to haplotypes on the per-sample level. Haplotype blocks with a size
+of `0` were removed from the data.
 
 ## Haplotyping details {data-height=100}
 ```{r echo= FALSE, message = FALSE, warning = FALSE}
@@ -187,9 +188,9 @@ DT::datatable(
 ## contig ridgeplot
 ### per contig plot {.no-title}
 ```{r contig_ridgeplot, warning=FALSE, message=FALSE, echo= FALSE, fig.height=ridgeheight, fig.width=8}
-ggplot(df, aes(x = block_length, y = contig) + #, fill = stat(x))) +
-  geom_density_ridges() + #_gradient() +
-  #scale_fill_viridis_c(option = "C", trans = "log10") +
+ggplot(df, aes(x = block_length, y = contig, fill = stat(x))) +
+  geom_density_ridges_gradient() +
+  scale_fill_viridis_c(option = "C", trans = "log10") +
   theme_minimal() +
   theme(legend.position = "none") +
   scale_x_log10(
@@ -240,9 +241,9 @@ DT::datatable(
 ## ridgeplot
 ### the ridgeplot {.no-title}
 ```{r sample_ridgeplot, warning=FALSE, message=FALSE, echo= FALSE, fig.height=ridgeheight.samples, fig.width=8}
-ggplot(df, aes(x = block_length, y = sample) + #, fill = stat(x))) +
-  geom_density_ridges() + #_gradient(rel_min_height = 0.01) +
-  #scale_fill_viridis_c(option = "G", trans = "log10") +
+ggplot(df, aes(x = block_length, y = sample, fill = stat(x))) +
+  geom_density_ridges_gradient(scale = 0.1) +
+  scale_fill_viridis_c(option = "G", trans = "log10") +
   theme_minimal() +
   theme(legend.position = "none") +
   scale_x_log10(