docs: update memory usage diagram for version 1.4.0

ChangeLog

@@ -1,6 +1,19 @@
 CHANGES
 =======
 
+1.4.0
+-----
+
+* perf: switch source and target for dijkstra
+
+1.3.3
+-----
+
+* refactor: make type of 0L clear to std::max on Windows
+* Revert "fix: don't assume vertices are uint32"
+* fix: don't assume vertices are uint32
+* chore: update ChangeLog
+
 1.3.2
 -----
 

README.md

@@ -30,7 +30,7 @@ In the future, we may create a fully binary distribution.
 Fig. 2: Memory Usage on a 512x512x512 Densely Labeled Volume
 </p>
 
-Figure 2 shows the memory usage and processessing time (~390 seconds, about 6.5 minutes) required when Kimimaro 0.5.2 was applied to a 512x512x512 cutout, *labels*, from a connectomics dataset containing 2124 connected components. The different sections of the algorithm are depicted. Grossly, the preamble runs for about half a minute, skeletonization for about six minutes, and finalization within seconds. The peak memory usage was about 4.1 GB. The code below was used to process *labels*. The processing of the glia was truncated in due to a combination of *fix_borders* and max_paths.  
+Figure 2 shows the memory usage and processessing time (~390 seconds, about 6.5 minutes) required when Kimimaro 1.4.0 was applied to a 512x512x512 cutout, *labels*, from a connectomics dataset containing 2124 connected components. The different sections of the algorithm are depicted. Grossly, the preamble runs for about half a minute, skeletonization for about six minutes, and finalization within seconds. The peak memory usage was about 4.5 GB. The code below was used to process *labels*. The processing of the glia was truncated in due to a combination of *fix_borders* and max_paths.  
 
 Kimimaro has come a long way. Version 0.2.1 took over 15 minutes and had a  Preamble run time twice as long on the same dataset.