fig: use the $out path in the subtitle

The input dataset is not enough to determine which script produced a
given plot.

garlic/fig/creams/granularity.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -62,7 +63,7 @@ p = ggplot(df, aes(x=granul, y=normalized.time)) +
   facet_wrap(branch ~ .) +
   labs(x="granul", y="Normalized time",
        title="Creams granularity: normalized time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -75,7 +76,7 @@ p = ggplot(df, aes(x=granul, y=time, color=branch)) +
   geom_line(aes(y=median.time, group=branch)) +
   theme_bw() +
   labs(x="granul", y="Time (s)", title="Creams granularity: time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/creams/ss.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -64,7 +65,7 @@ p = ggplot(df, aes(x=nodes, y=normalized.time, fill=granul, color=iterations)) +
   facet_wrap(branch ~ .) +
   labs(x="nodes", y="Normalized time",
     title="Creams strong scaling: normalized time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -78,7 +79,7 @@ p = ggplot(df, aes(x=nodes, y=time, color=gitBranch)) +
   theme_bw() +
 #  facet_wrap(branch ~ .) +
   labs(x="nodes", y="Time (s)", title="Creams strong scaling: time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -92,7 +93,7 @@ p = ggplot(df, aes(x=nodes, y=median.time.nodes, color=branch)) +
   theme_bw() +
   #facet_wrap(branch ~ .) +
   labs(x="nodes", y="Median time * nodes (s)", title="Creams strong scaling: median time * nodes", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("median.time.nodes.png", plot=p, width=w, height=h, dpi=dpi)
@@ -105,7 +106,7 @@ p = ggplot(df, aes(x=nodes, y=time.nodes, color=branch)) +
   theme_bw() +
   facet_wrap(branch ~ .) +
   labs(x="nodes", y="Time * nodes (s)", title="Creams strong scaling: time * nodes", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.nodes.boxplot.png", plot=p, width=w, height=h, dpi=dpi)
@@ -120,7 +121,7 @@ ggsave("time.nodes.boxplot.pdf", plot=p, width=w, height=h, dpi=dpi)
 #  #facet_wrap(branch ~ .) +
 #  labs(x="nodes", y="Time * nodes / iterations (s)",
 #    title="Creams strong scaling: time * nodes / iterations", 
-#    subtitle=input_file) + 
+#    subtitle=output) + 
 #  theme(plot.subtitle=element_text(size=8))
 #
 #ggsave("time.nodes.iter.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/examples/granularity.R

@@ -28,6 +28,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Here we build of dataframe from the input dataset by chaining operations using
 # the magritte operator `%>%`, which is similar to a UNIX pipe.
@@ -94,7 +95,7 @@ p = ggplot(df, aes(x=cbs, y=median.time, color=rbs)) +
 
   # Here we add the title and the labels of the axes
   labs(x="cbs", y="Median time (s)", title="Heat granularity: median time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
 
   # And set the subtitle font size a bit smaller, so it fits nicely
   theme(plot.subtitle=element_text(size=8))
@@ -126,7 +127,7 @@ p = ggplot(df, aes(x=cbs, y=normalized.time)) +
 
   # Here we add the title and the labels of the axes
   labs(x="cbs", y="Normalized time", title="Heat granularity: normalized time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
 
   # And set the subtitle font size a bit smaller, so it fits nicely
   theme(plot.subtitle=element_text(size=8))
@@ -151,7 +152,7 @@ p = ggplot(df, aes(x=cbs, y=time, color=rbs)) +
 
   # Here we add the title and the labels of the axes
   labs(x="cbs", y="Time (s)", title="Heat granularity: time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
 
   # And set the subtitle font size a bit smaller, so it fits nicely
   theme(plot.subtitle=element_text(size=8))
@@ -184,7 +185,7 @@ p = ggplot(df, aes(x=cbs, y=rbs, fill=median.time)) +
 
   # Here we add the title and the labels of the axes
   labs(x="cbs", y="rbs", title="Heat granularity: time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
 
   # And set the subtitle font size a bit smaller, so it fits nicely
   theme(plot.subtitle=element_text(size=8))

garlic/fig/fwi/granularity.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -51,7 +52,7 @@ p = ggplot(df, aes(x=blocksize, y=normalized.time)) +
   facet_wrap(branch ~ .) +
   labs(y="Normalized time",
     title=sprintf("%s: normalized time", main_title), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -65,7 +66,7 @@ p = ggplot(df, aes(x=blocksize, y=time, color=branch)) +
   theme_bw() +
   labs(y="Time (s)",
     title=sprintf("%s: time", main_title), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(legend.position="bottom") +
   theme(plot.subtitle=element_text(size=8))
 

garlic/fig/fwi/io.R

@@ -9,6 +9,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -48,7 +49,7 @@ p = ggplot(df, aes(x=nodes, y=time, group=enableIO, color=enableIO)) +
   geom_line() +
   theme_bw() +
   labs(x="Nodes", y="Time (s)", title="FWI strong scaling for mpi+send+oss+task",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position = c(0.5, 0.88))
 
@@ -68,7 +69,7 @@ p = ggplot(df, aes(x=nodes, y=nxtime, group=enableIO, color=enableIO)) +
   geom_line() +
   theme_bw() +
   labs(x="Nodes", y="Time * Nodes (s)", title="FWI strong scaling for mpi+send+oss+task",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position = c(0.5, 0.88))
 
@@ -88,7 +89,7 @@ dev.off()
 #  geom_line() +
 #  theme_bw() +
 #  labs(x="Nodes", y="Median Time (s)", title="FWI strong scaling",
-#    subtitle=input_file) +
+#    subtitle=output) +
 #  theme(plot.subtitle=element_text(size=8)) +
 #  theme(legend.position = c(0.5, 0.88))
 #
@@ -108,7 +109,7 @@ dev.off()
 #  geom_line() +
 #  theme_bw() +
 #  labs(x="Nodes", y="Median Time * Nodes (s)", title="FWI strong scaling",
-#    subtitle=input_file) +
+#    subtitle=output) +
 #  theme(plot.subtitle=element_text(size=8)) +
 #  theme(legend.position = c(0.5, 0.88))
 #

garlic/fig/fwi/ss.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -57,7 +58,7 @@ p = ggplot(df, aes(x=nodes, y=normalized.time)) +
   facet_wrap(branch ~ .) +
   labs(x="nodes", y="Normalized time",
     title=sprintf("%s: normalized time", main_title), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -72,7 +73,7 @@ p = ggplot(df, aes(x=nodes, y=time, color=gitBranch)) +
 #  facet_wrap(branch ~ .) +
   labs(y="Time (s)",
     title=sprintf("%s: time", main_title), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -87,7 +88,7 @@ p = ggplot(df, aes(x=nodes, y=time.nodes, color=branch)) +
   #facet_wrap(branch ~ .) +
   labs(x="nodes", y="Time * nodes (s)",
     title=sprintf("%s: time * nodes", main_title), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.nodes.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/heat/cache.R

@@ -9,6 +9,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -49,7 +50,7 @@ heatmap_plot = function(df, colname, title) {
     guides(fill = guide_colorbar(barwidth=12, title.vjust=0.8)) +
     labs(x="cbs", y="rbs",
       title=sprintf("Heat granularity: %s", title), 
-      subtitle=input_file) +
+      subtitle=output) +
     theme(legend.position="bottom")
 
   k=1

garlic/fig/heat/granularity.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -47,7 +48,7 @@ p = ggplot(df, aes(x=cbs, y=normalized.time)) +
   theme_bw() +
   labs(y="Normalized time",
        title="Heat granularity: normalized time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -60,7 +61,7 @@ p = ggplot(df, aes(x=cbs, y=time)) +
   geom_line(aes(y=median.time, group=0)) +
   theme_bw() +
   labs(y="Time (s)", title="Heat granularity: time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/heat/mode.R

@@ -10,6 +10,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -62,7 +63,7 @@ heatmap_plot = function(df, colname, title) {
     guides(fill = guide_colorbar(barwidth=12, title.vjust=0.8)) +
     labs(x="cbs", y="rbs",
       title=sprintf("Heat granularity: %s", title), 
-      subtitle=input_file) +
+      subtitle=output) +
     theme(legend.position="bottom")
 
   k=1
@@ -103,7 +104,7 @@ p = ggplot(df_square, aes(x=cbs, y=acc.time)) +
     labels = c("Total time"), guide = "legend") +
   labs(x="Blocksize (side)", y="Time (s)",
     fill="Estimated", color="Direct measurement",
-    title="Heat granularity: time distribution", subtitle=input_file)
+    title="Heat granularity: time distribution", subtitle=output)
 
 ggsave("area.time.png", plot=p, width=6, height=6, dpi=300)
 ggsave("area.time.pdf", plot=p, width=6, height=6, dpi=300)
@@ -115,7 +116,7 @@ p = ggplot(df_square, aes(x=cbs, y=acc.time)) +
   theme(legend.position=c(0.5, 0.7)) +
   labs(x="Blocksize (side)", y="Time (s)",
     fill="Estimated", color="Direct measurement",
-    title="Heat granularity: time distribution", subtitle=input_file)
+    title="Heat granularity: time distribution", subtitle=output)
 
 ggsave("col.time.png", plot=p, width=6, height=6, dpi=300)
 ggsave("col.time.pdf", plot=p, width=6, height=6, dpi=300)

garlic/fig/hpcg/granularity.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 args = commandArgs(trailingOnly=TRUE)
 
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -44,7 +45,7 @@ p = ggplot(df, aes(x=blocksPerCpu, y=normalized.time)) +
   geom_hline(yintercept=c(-0.01, 0.01), linetype="dashed", color="red") +
   theme_bw() +
   labs(x="Blocks per CPU", y="Normalized time", title="HPCG granularity: normalized time",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -54,7 +55,7 @@ p = ggplot(df, aes(x=blocksPerCpu, y=time)) +
   geom_point(shape=21, size=3) +
   theme_bw() +
   labs(x="Blocks per CPU", y="Time (s)", title="HPCG granularity: time",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/hpcg/size.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 args = commandArgs(trailingOnly=TRUE)
 
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -62,7 +63,7 @@ p = ggplot(df, aes(x=sizePerCpu.z, y=time.nodes.elem)) +
   theme_bw() +
   labs(x="Size per CPU in Z", y="Time * nodes / spcz (s)",
     title="HPCG size: time * nodes / spcz",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8),
     legend.position="bottom")
 

garlic/fig/hpcg/ss.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 args = commandArgs(trailingOnly=TRUE)
 
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -61,7 +62,7 @@ p = ggplot(df, aes(x=nodes, y=time.nodes)) +
   theme_bw() +
   labs(x="Nodes", y="Time * nodes (s)",
     title="HPCG strong scalability in Z",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8),
     legend.position="bottom")
 
@@ -73,7 +74,7 @@ p = ggplot(df, aes(x=nodes, y=time.sizeZ, fill=sizePerCpu.z)) +
   theme_bw() +
   labs(x="Nodes", y="Time / npcz (s)", title="HPCG strong scalability in Z",
     color="Size per CPU in Z",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8),
     legend.position="bottom")
 

garlic/fig/hpcg/ws.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 args = commandArgs(trailingOnly=TRUE)
 
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -62,7 +63,7 @@ p = ggplot(df, aes(x=nodes, y=time, fill=sizePerCpu.z)) +
   theme_bw() +
   labs(x="Nodes", y="Time (s)", title="HPCG weak scaling in Z",
     color="Size per CPU in Z",
-    subtitle=input_file) +
+    subtitle=output) +
   theme(plot.subtitle=element_text(size=8),
     legend.position="bottom")
 

garlic/fig/nbody/granularity.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 # Load the arguments (argv)
 args = commandArgs(trailingOnly=TRUE)
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
   jsonlite::flatten() %>%
@@ -38,7 +39,7 @@ p = ggplot(df, aes(x=blocksize, y=normalized.time, color=branch)) +
   facet_wrap(~ branch) +
   theme_bw() +
   labs(x="Blocksize", y="Normalized Time", title="NBody Granularity: Normalized Time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position="bottom") +
   theme(legend.text = element_text(size=7))
@@ -52,7 +53,7 @@ p = ggplot(df, aes(x=blocksize, y=time)) +
   geom_boxplot() +
   theme_bw() +
   labs(x="Blocksize", y="Time (s)", title="NBody Granularity: Time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position="bottom") +
   theme(legend.text = element_text(size=7))

garlic/fig/nbody/numa.R

@@ -8,6 +8,7 @@ library(stringr)
 # Load the arguments (argv)
 args = commandArgs(trailingOnly=TRUE)
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
   jsonlite::flatten() %>%
@@ -60,7 +61,7 @@ p = ggplot(df, aes(x=blocksize, y=normalized.time, color=interleaveMem)) +
   labs(x="Blocksize", y="Normalized time",
     title=sprintf("NBody NUMA (%s | %d Nodes): Normalized time",
       branch, nodes), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position="bottom")
 
@@ -77,7 +78,7 @@ p = ggplot(df, aes(x=blocksize, y=time, color=interleaveMem)) +
   labs(x="Blocksize", y="Time (s)",
     title=sprintf("NBody NUMA (%s | %d Nodes): Time",
       branch, nodes), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8)) +
   theme(legend.position="bottom")
 

garlic/fig/nbody/old/baseline.R

@@ -9,6 +9,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -79,7 +80,7 @@ p = ggplot(data=D, aes(x=blocksPerCpuFactor, y=tnorm, color=bad)) +
   # Labels
   labs(x="Blocks/CPU", y="Normalized time",
               title=sprintf("Nbody normalized time. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 
 
   # Center the title
@@ -117,7 +118,7 @@ p1 = ggplot(D, aes(x=blocksizeFactor, y=time)) +
 
   labs(x="Blocksize", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
   theme_bw() +
   theme(plot.subtitle=element_text(size=8)) +
   #theme(legend.position = c(0.5, 0.8)) +
@@ -138,7 +139,7 @@ p2 = ggplot(D, aes(x=blocksPerCpuFactor, y=time)) +
 
   labs(x="Blocks/CPU", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
   theme_bw() +
   theme(plot.subtitle=element_text(size=8)) +
 

garlic/fig/nbody/old/freeCpu.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -50,7 +51,7 @@ p = ggplot(data=D, aes(x=blocksPerCpuFactor, y=tnorm)) +
 	# Labels
 	labs(x="Blocks/CPU", y="Normalized time",
               title=sprintf("Nbody normalized time. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 
 	# Center the title
 	#theme(plot.title = element_text(hjust = 0.5)) +
@@ -95,7 +96,7 @@ p = ggplot(D, aes(x=blocksPerCpuFactor, y=time, color=freeCpu)) +
 
 	labs(x="Blocks/CPU", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 	theme_bw() +
 	theme(plot.subtitle=element_text(size=8)) +
 	theme(legend.position = c(0.5, 0.88)) +

garlic/fig/nbody/old/jemalloc.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -52,7 +53,7 @@ p = ggplot(data=D, aes(x=nblocks, y=tnorm)) +
 	# Labels
 	labs(x="Num blocks", y="Normalized time",
               title=sprintf("Nbody normalized time. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 
 	# Center the title
 	#theme(plot.title = element_text(hjust = 0.5)) +
@@ -96,7 +97,7 @@ p = ggplot(D, aes(x=blocksPerCpu, y=time, color=jemalloc)) +
 
 	labs(x="Blocks/CPU", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 	theme_bw() +
 	theme(plot.subtitle=element_text(size=8)) +
 	theme(legend.position = c(0.5, 0.88)) +

garlic/fig/nbody/old/scaling.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file)) %>%
@@ -53,7 +54,7 @@ p = ggplot(data=D, aes(x=blocksPerCpuFactor, y=tnorm, color=bad)) +
 	# Labels
 	labs(x="Blocks/CPU", y="Normalized time",
               title=sprintf("Nbody normalized time. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 
 
 	# Center the title
@@ -94,7 +95,7 @@ p = ggplot(D, aes(x=blocksPerCpuFactor, y=time)) +
 
 	labs(x="Blocks/CPU", y="Time (s)",
               title=sprintf("Nbody granularity. Particles=%d", particles), 
-              subtitle=input_file) +
+              subtitle=output) +
 	theme_bw() +
 	theme(plot.subtitle=element_text(size=8)) +
 	theme(legend.position = c(0.5, 0.88)) +

garlic/fig/nbody/ss.R

@@ -7,6 +7,7 @@ library(viridis, warn.conflicts = FALSE)
 # Load the arguments (argv)
 args = commandArgs(trailingOnly=TRUE)
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
   jsonlite::flatten() %>%
@@ -41,7 +42,7 @@ p = ggplot(df, aes(x=nodes, y=normalized.time, color=branch)) +
   facet_wrap(~ branch) +
   theme_bw() +
   labs(x="Nodes", y="Normalized time (s)", title="NBody Scaling: Normalized Time", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=5)) +
   theme(legend.position="bottom") +
   theme(legend.text = element_text(size=7))
@@ -56,7 +57,7 @@ p = ggplot(df, aes(x=nodes, y=time.nodes, color=branch)) +
   geom_line(aes(y=median.time.nodes, group=branch)) +
   theme_bw() +
   labs(x="Nodes", y="Time * nodes (s)", title="NBody Scaling: Time * nodes", 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=5)) +
   theme(legend.position="bottom") +
   theme(legend.text = element_text(size=7))

garlic/fig/osu/bw.R

@@ -11,6 +11,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
@@ -39,7 +40,7 @@ w=6
 p = ggplot(data=df, aes(x=size, y=median.bw)) +
 	labs(x="Message size", y="Bandwidth (GB/s)",
     #title=sprintf("OSU benchmark: osu_bw", nodes, tasksPerNode, cpusPerTask), 
-    subtitle=gsub("-", "\uad", input_file)) +
+    subtitle=gsub("-", "\uad", output)) +
 	geom_line(aes(linetype=unitName)) +
 	geom_point(aes(shape=unitName), size=1.5) +
   scale_shape_discrete(name = "MPI version") +
@@ -73,7 +74,7 @@ ggsave("median-lines.pdf", plot=p, width=w, height=h, dpi=ppi)
 p = ggplot(data=df, aes(x=size, y=bw)) +
 	labs(x="Message size", y="Bandwidth (MB/s)",
     #title=sprintf("OSU benchmark: osu_bw", nodes, tasksPerNode, cpusPerTask),
-    subtitle=input_file) +
+    subtitle=output) +
 	geom_line(aes(y=median.bw, linetype=unitName, group=unitName)) +
 	geom_point(aes(shape=unitName), size=2) +
   scale_shape(solid = FALSE) +

garlic/fig/osu/eager.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
@@ -49,7 +50,7 @@ w=8
 p = ggplot(data=df, aes(x=sizeKB, y=bw)) +
   labs(x="Message size (KB)", y="Bandwidth (MB/s)",
     title=sprintf("OSU benchmark: osu_bw --iterations %d", iterations), 
-    subtitle=input_file) +
+    subtitle=output) +
   geom_point(shape=21, size=3) +
   geom_vline(aes(xintercept = PSM2_MQ_EAGER_SDMA_SZ/1024), color="blue") +
   geom_vline(xintercept = 10, color="red") +

garlic/fig/osu/impi.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
@@ -36,7 +37,7 @@ p = ggplot(data=df, aes(x=size, y=bw)) +
 	labs(x="Size (bytes)", y="Bandwidth (MB/s)",
               title=sprintf("OSU bandwidth benchmark: nodes=%d tasksPerNode=%d cpusPerTask=%d",
 			    nodes, tasksPerNode, cpusPerTask), 
-              subtitle=input_file) +
+              subtitle=output) +
 	geom_boxplot(aes(color=threshold, group=interaction(threshold, sizeFactor))) +
 	scale_x_continuous(trans=log2_trans()) +
 	#scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) +
@@ -53,7 +54,7 @@ p = ggplot(data=df, aes(x=size, y=medianBw)) +
 	labs(x="Size (bytes)", y="Bandwidth (MB/s)",
               title=sprintf("OSU benchmark: osu_bw",
 			    nodes, tasksPerNode, cpusPerTask), 
-              subtitle=input_file) +
+              subtitle=output) +
 	geom_line(aes(color=threshold, linetype=threshold)) +
 	geom_point(aes(color=threshold, shape=threshold)) +
   geom_hline(yintercept = 100e3 / 8, color="red") +

garlic/fig/osu/latency.R

@@ -9,6 +9,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
@@ -39,7 +40,7 @@ w=6
 p = ggplot(data=df, aes(x=size, y=medianLatency)) +
 	labs(x="Message size", y="Median latency (µs)",
     #title=sprintf("OSU benchmark: osu_latency", nodes, tasksPerNode, cpusPerTask), 
-    subtitle=gsub("-", "\uad", input_file)) +
+    subtitle=gsub("-", "\uad", output)) +
 	geom_line(aes(linetype=unitName)) +
 	geom_point(aes(shape=unitName), size=2) +
 	scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) +
@@ -59,7 +60,7 @@ ggsave("median-lines.pdf", plot=p, width=w, height=h, dpi=ppi)
 p = ggplot(data=df, aes(x=size, y=latency)) +
 	labs(x="Size (bytes)", y="Latency (us)",
     #title=sprintf("OSU benchmark: osu_latency", nodes, tasksPerNode, cpusPerTask), 
-    subtitle=input_file) +
+    subtitle=output) +
 	geom_line(aes(y=medianLatency, linetype=unitName, group=unitName)) +
 	geom_point(aes(shape=unitName), size=2) +
 	scale_y_log10(breaks = breaks, minor_breaks = minor_breaks) +

garlic/fig/osu/mtu.R

@@ -8,6 +8,7 @@ args=commandArgs(trailingOnly=TRUE)
 # Read the timetable from args[1]
 input_file = "input.json"
 if (length(args)>0) { input_file = args[1] }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 # Load the dataset in NDJSON format
 dataset = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
@@ -55,7 +56,7 @@ p = ggplot(data=df, aes(x=sizeKB, y=bw)) +
   geom_vline(aes(xintercept = PSM2_MTU.val/1024), color="red") +
   labs(x="Message size (KiB)", y="Bandwidth (GB/s)",
     #title=sprintf("OSU benchmark: osu_bw --iterations %d", iterations), 
-    subtitle=gsub("-", "\uad", input_file)) +
+    subtitle=gsub("-", "\uad", output)) +
   geom_point(shape=21, size=2) +
   #annotate("text", x = 10.2, y = 8.5e3, label = "MTU = 10KB", color="red", hjust=0) +
   facet_wrap(vars(PSM2_MTU), nrow=3, labeller = "label_both") +

garlic/fig/saiph/granularity.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -72,7 +73,7 @@ p = ggplot(df, aes(x=nbly, y=normalized.time, fill=sizex)) +
   facet_wrap(branch ~ .) +
   labs(y="Normalized time",
     title=sprintf("%s: normalized time", maintitle), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -87,7 +88,7 @@ p = ggplot(df, aes(x=blocksPerCpu, y=time, color=sizex)) +
   scale_x_continuous(trans=log2_trans()) +
   labs(y="Time (s)",
     title=sprintf("%s: time", maintitle), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)

garlic/fig/saiph/ss.R

@@ -9,6 +9,7 @@ args = commandArgs(trailingOnly=TRUE)
 
 # Set the input dataset if given in argv[1], or use "input" as default
 if (length(args)>0) { input_file = args[1] } else { input_file = "input" }
+if (length(args)>1) { output = args[2] } else { output = "?" }
 
 df = jsonlite::stream_in(file(input_file), verbose=FALSE) %>%
 
@@ -72,7 +73,7 @@ p = ggplot(df, aes(x=nodes, y=normalized.time, fill=sizex)) +
   facet_wrap(branch ~ .) +
   labs(x="nodes", y="Normalized time",
     title=sprintf("%s: normalized time", maintitle), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("normalized.time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -87,7 +88,7 @@ p = ggplot(df, aes(x=nodes, y=time, color=sizex)) +
 #  facet_wrap(branch ~ .) +
   labs(x="nodes", y="Time (s)",
     title=sprintf("%s: time", maintitle), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.png", plot=p, width=w, height=h, dpi=dpi)
@@ -102,7 +103,7 @@ p = ggplot(df, aes(x=nodes, y=time.nodes, color=sizex)) +
   #facet_wrap(branch ~ .) +
   labs(x="nodes", y="Time * nodes (s)",
     title=sprintf("%s: time * nodes", maintitle), 
-    subtitle=input_file) + 
+    subtitle=output) + 
   theme(plot.subtitle=element_text(size=8))
 
 ggsave("time.nodes.png", plot=p, width=w, height=h, dpi=dpi)

garlic/pp/rplot.nix

@@ -147,7 +147,7 @@ in stdenv.mkDerivation {
     dataset="${dataset}"
 
     ln -s $dataset input
-    Rscript --vanilla ${script} ${dataset}
+    Rscript --vanilla ${script} ${dataset} "$out"
 
     if [ "''${dataset##*.}" == gz ]; then
       gunzip --stdout $dataset