Remove hrbrthemes due to missing fonts in Windows, MacOS and Ubuntu-1…

…6.04 3.3 as figured by R CMD checks
Anirban166 · Aug 23, 2020 · 61915c6 · 61915c6
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -25,8 +25,7 @@ Imports: boot,
          bench, 
          ggplot2, 
          stats,
-         testthat (>= 2.1.0),
-         hrbrthemes
+         testthat (>= 2.1.0)
 Suggests: 
     covr,
     knitr,

diff --git a/docs/articles/testComplexity.html b/docs/articles/testComplexity.html
diff --git a/docs/articles/testComplexity_files/figure-html/unnamed-chunk-1-1.png b/docs/articles/testComplexity_files/figure-html/unnamed-chunk-1-1.png
diff --git a/docs/articles/testComplexity_files/figure-html/unnamed-chunk-2-1.png b/docs/articles/testComplexity_files/figure-html/unnamed-chunk-2-1.png
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
@@ -10,5 +10,5 @@ articles:
   PELT_and_SegNeigh: PELT_and_SegNeigh.html
   substring_and_gregexpr: substring_and_gregexpr.html
   testComplexity: testComplexity.html
-last_built: 2020-08-23T07:58Z
+last_built: 2020-08-23T08:41Z
 
diff --git a/vignettes/testComplexity.Rmd b/vignettes/testComplexity.Rmd
@@ -202,17 +202,18 @@ The call stack (sequence of calls that lead to the error) is returned via a call
 ### [Plotters](https://anirban166.github.io/testComplexity/reference/index.html#section-plotters)
 These functions are for plotting the metrics returned by the quantifiers, in case the user still prefers to diagnose the obtained complexity result via the traditional method, with a visual representation of the benchmarked data. Considering the columns from the data frames returned by the quantiftying functions, the user can create plots for:
 
-- Timings vs Data sizes, via `plotTimings`:
+- Timings vs Data sizes, via `plotTimings`: <br>
 ```{r echo=TRUE, fig.show='hold', warning=FALSE}
 library(testComplexity)
 df <- asymptoticTimings(PeakSegOptimal::PeakSegPDPA(rpois(N, 1), max.segments = 3L), data.sizes = 10^seq(1, 4))
-plotTimings(df, titles = list("Timings", "PeakSegOptimal::PeakSegPDPA"), line.color = "#ffec1b", point.color = "#ffec1b", line.size = 1, point.size = 1.5) + hrbrthemes::theme_ft_rc() 
+plotTimings(df, titles = list("Timings", "PeakSegOptimal::PeakSegPDPA"), line.color = "orange", point.color = "black", line.size = 1, point.size = 1.5)  
 ```
-- Memory Allocations vs Data sizes, via `plotMemoryUsage`:
+
+- Memory Allocations vs Data sizes, via `plotMemoryUsage`: <br>
 ```{r echo=TRUE, fig.show='hold', warning=FALSE}
 library(testComplexity)
 df <- asymptoticMemoryUsage(PeakSegOptimal::PeakSegPDPA(rpois(N, 1), max.segments = 3L), data.sizes = 10^seq(1, 4, by = 0.1))
-plotMemoryUsage(df, titles = list("Memory usage", "PeakSegOptimal::PeakSegPDPA"), line.color = "#ffec1b", point.color = "#ffec1b", line.size = 1, point.size = 1.5) + hrbrthemes::theme_ft_rc() 
+plotMemoryUsage(df, titles = list("Memory usage", "PeakSegOptimal::PeakSegPDPA"), line.color = "orange", point.color = "black", line.size = 1, point.size = 1.5)  
 ```
 
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