viz script: paper submission version

scripts-r/viz-campaign.R

@@ -143,8 +143,7 @@ data_nz %>% ggplot(aes(x=powercap_dynamic_value_ratio)) +
   geom_line(aes(y=power_p99/max_dynamic_power, color=predictor_name), linetype='dotted', show.legend = FALSE) +
   geom_abline(slope=1) +
   theme_bw() +
-  theme(legend.position='top', legend.title=upper_bound
-upper_boundt) +
+  theme(legend.position='top', legend.title=upper_bound) +
   scale_color_viridis(discrete=TRUE) +
   scale_fill_viridis(discrete=TRUE) +
   facet_wrap(vars(start_dt_s)) +
@@ -156,6 +155,7 @@ upper_boundt) +
 ggsave(sprintf("%s/power-consumption-mean-p1-p99-against-powercap-predictor.pdf", output_dir), width=16, height=9)
 
 # distribution of the mean power used for each predictor
+#powercap_ratios_values_to_show = c(0.1, 0.25, 0.4, 0.55, 0.7)
 powercap_ratios_values_to_show = c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7)
 width_scale=0.3
 data_nz %>%
@@ -178,12 +178,11 @@ data_nz %>%
   facet_wrap(vars(powercap_label), nrow=1) +
   labs(
     y="Mean platform power consumption",
-    x="Job power estimator metrics"
+    x="Job power estimator"
   ) +
   scale_fill_grey(start=0.8, end=1)
 scale=0.9
 ggsave(sprintf("%s/sched-mean-power-distribution.pdf", output_dir), width=8*scale, height=4*scale)
-ggsave(sprintf("%s/sched-mean-power-distribution.png", output_dir), width=8*scale, height=4*scale)
 
 # distribution of mean turnaround time diff (EASY) for each predictor
 outlier_workload_start_dt_s = 18474670 # sched metrics are strogly better than EASY there
@@ -191,6 +190,7 @@ width_scale=0.3
 data_nz %>%
   filter(start_dt_s != outlier_workload_start_dt_s) %>%
   filter(powercap_dynamic_value_ratio %in% powercap_ratios_values_to_show) %>%
+  mutate(powercap_label = sprintf("pcap=%g", powercap_dynamic_value_ratio)) %>%
   ggplot() +
   geom_boxplot(aes(y=mean_turnaround_time_minus_zero, fill=predictor_method, x=predictor_metrics), linewidth=width_scale, outlier.size=width_scale) +
   theme_bw() +
@@ -202,10 +202,10 @@ data_nz %>%
 
     axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
   ) +
-  facet_wrap(vars(powercap_dynamic_value_ratio), nrow=1) +
+  facet_wrap(vars(powercap_label), nrow=1) +
   labs(
     y="Mean turnaround time increase (s)",
-    x="Job power estimator metrics"
+    x="Job power estimator"
   ) +
   scale_fill_grey(start=0.8, end=1)
 scale=0.9