Merge pull request #36 from olivroy/fix-image-links

Move all figures to `man/figures` + update README

.Rbuildignore

@@ -14,5 +14,5 @@
 ^docs$
 ^pkgdown$
 ^\.github$
-man/figures/logo.png
+^man/figures$
 ^vignettes/articles$

README.Rmd

@@ -85,7 +85,7 @@ The main tool is a dashboard, which is started with:
 c4a_gui()
 ```
 
-[<img src="articles/cols4all2.jpg" width="900"/>](articles/cols4all2.jpg)
+[<img src="man/figures/cols4all2.jpg" width="900"/>](man/figures/cols4all2.jpg)
 
 
 What palettes are available? That is, by default; other palettes can be added!
@@ -113,7 +113,7 @@ Find a trade-off you like among the following properties (the columns in the mai
 
 When we are looking for a fair categorical palette of seven colors that is as color blind friendly as possible, then filter on "Fair", and sort by "Colorblind-friendly":
 
-[<img src="articles/cols4all_fair_sort_cbf.jpg" width="900"/>](articles/cols4all_fair_sort_cbf.jpg)
+[<img src="man/figures/cols4all_fair_sort_cbf.jpg" width="900"/>](man/figures/cols4all_fair_sort_cbf.jpg)
 
 
 This inspired us to develop our own palettes: see these `cols4all` palettes below.
@@ -122,33 +122,33 @@ This inspired us to develop our own palettes: see these `cols4all` palettes belo
 
 Say we need a diverging palette that is color blind friendly, and what to choose one by eye. Then filter by "Colorblind-friendly" and sort by "Hue Middle L" (the hue of the left wing):
 
-[<img src="articles/cols4all_div.jpg" width="900"/>](articles/cols4all_div.jpg)
+[<img src="man/figures/cols4all_div.jpg" width="900"/>](man/figures/cols4all_div.jpg)
 
 Reverse sorting is also applied.
 
 ## Preliminary set of new `cols4all` palettes
 
 We applied a basic heuristic to explore palettes that score well on a mix of the properties named above
 
-[<img src="articles/c4a_pals.jpg" width="900"/>](articles/c4a_pals.jpg)
+[<img src="man/figures/c4a_pals.jpg" width="900"/>](man/figures/c4a_pals.jpg)
 
-`area7`, `area8` and `area9` are fair, contain low pastel colors, and are color-blind friendly (up to 7 colors). So ideal for maps and other space-filling visualizations! These are used in [https://github.com/r-tmap/tmap](`tmap4`).
+`area7`, `area8` and `area9` are fair, contain low pastel colors, and are color-blind friendly (up to 7 colors). So ideal for maps and other space-filling visualizations! These are used in [`tmap4`](https://github.com/r-tmap/tmap).
 
-[<img src="articles/area7.jpg" width="900"/>](articles/area7.jpg)
+[<img src="man/figures/area7.jpg" width="900"/>](man/figures/area7.jpg)
 
 `area7d`, `area8d` and `area9d` similar but for dark mode:.
 
-[<img src="articles/area7d.jpg" width="900"/>](articles/area7d.jpg)
+[<img src="man/figures/area7d.jpg" width="900"/>](man/figures/area7d.jpg)
 
 
 `line7`, `line8` and `line9` are colors with good contrast against both black and white, and are also colorblind-friendly to some extent. So ideal for line graphs and scatter plots:
 
-[<img src="articles/line7_wt.jpg" width="440"/>](articles/line7_wt.jpg)
-[<img src="articles/line7_bk.jpg" width="440"/>](articles/line7_bk.jpg)
+[<img src="man/figures/line7_wt.jpg" width="440"/>](man/figures/line7_wt.jpg)
+[<img src="man/figures/line7_bk.jpg" width="440"/>](man/figures/line7_bk.jpg)
 
 Finally `friendly7` ... `friendly13` are colorblind-friendly palettes (disregarding the other properties):
 
-[<img src="articles/friendly13.jpg" width="900"/>](articles/friendly13.jpg)
+[<img src="man/figures/friendly13.jpg" width="900"/>](man/figures/friendly13.jpg)
 
 
 

README.md

@@ -57,7 +57,7 @@ The main tool is a dashboard, which is started with:
 c4a_gui()
 ```
 
-[<img src="articles/cols4all2.jpg" width="900"/>](articles/cols4all2.jpg)
+[<img src="man/figures/cols4all2.jpg" width="900"/>](man/figures/cols4all2.jpg)
 
 What palettes are available? That is, by default; other palettes can be
 added!
@@ -111,7 +111,7 @@ When we are looking for a fair categorical palette of seven colors that
 is as color blind friendly as possible, then filter on “Fair”, and sort
 by “Colorblind-friendly”:
 
-[<img src="articles/cols4all_fair_sort_cbf.jpg" width="900"/>](articles/cols4all_fair_sort_cbf.jpg)
+[<img src="man/figures/cols4all_fair_sort_cbf.jpg" width="900"/>](man/figures/cols4all_fair_sort_cbf.jpg)
 
 This inspired us to develop our own palettes: see these `cols4all`
 palettes below.
@@ -122,7 +122,7 @@ Say we need a diverging palette that is color blind friendly, and what
 to choose one by eye. Then filter by “Colorblind-friendly” and sort by
 “Hue Middle L” (the hue of the left wing):
 
-[<img src="articles/cols4all_div.jpg" width="900"/>](articles/cols4all_div.jpg)
+[<img src="man/figures/cols4all_div.jpg" width="900"/>](man/figures/cols4all_div.jpg)
 
 Reverse sorting is also applied.
 
@@ -131,30 +131,30 @@ Reverse sorting is also applied.
 We applied a basic heuristic to explore palettes that score well on a
 mix of the properties named above
 
-[<img src="articles/c4a_pals.jpg" width="900"/>](articles/c4a_pals.jpg)
+[<img src="man/figures/c4a_pals.jpg" width="900"/>](man/figures/c4a_pals.jpg)
 
 `area7`, `area8` and `area9` are fair, contain low pastel colors, and
 are color-blind friendly (up to 7 colors). So ideal for maps and other
 space-filling visualizations! These are used in
-[https://github.com/r-tmap/tmap](%60tmap4%60).
+[`tmap4`](https://github.com/r-tmap/tmap).
 
-[<img src="articles/area7.jpg" width="900"/>](articles/area7.jpg)
+[<img src="man/figures/area7.jpg" width="900"/>](man/figures/area7.jpg)
 
 `area7d`, `area8d` and `area9d` similar but for dark mode:.
 
-[<img src="articles/area7d.jpg" width="900"/>](articles/area7d.jpg)
+[<img src="man/figures/area7d.jpg" width="900"/>](man/figures/area7d.jpg)
 
 `line7`, `line8` and `line9` are colors with good contrast against both
 black and white, and are also colorblind-friendly to some extent. So
 ideal for line graphs and scatter plots:
 
-[<img src="articles/line7_wt.jpg" width="440"/>](articles/line7_wt.jpg)
-[<img src="articles/line7_bk.jpg" width="440"/>](articles/line7_bk.jpg)
+[<img src="man/figures/line7_wt.jpg" width="440"/>](man/figures/line7_wt.jpg)
+[<img src="man/figures/line7_bk.jpg" width="440"/>](man/figures/line7_bk.jpg)
 
 Finally `friendly7` … `friendly13` are colorblind-friendly palettes
 (disregarding the other properties):
 
-[<img src="articles/friendly13.jpg" width="900"/>](articles/friendly13.jpg)
+[<img src="man/figures/friendly13.jpg" width="900"/>](man/figures/friendly13.jpg)
 
 ## `ggplot2` integration
 

vignettes/articles/paper.Rmd

@@ -50,7 +50,7 @@ library(cols4all)
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cols4all2.jpg")
+knitr::include_graphics("../../man/figures/cols4all2.jpg")
 ```
 
 ## Introduction
@@ -166,63 +166,63 @@ Palettes are organised by functional type. We distinguish the following types:
 #| out.width = 400,
 #| echo = FALSE
 
-knitr::include_graphics("ex_cat.jpg")
+knitr::include_graphics("../../man/figures/ex_cat.jpg")
 ```
 
 ```{r expals2, fig.cap = "Example of palette type: sequential"}
 #| fig.alt = "Example of palette type: sequential",
 #| out.width = 400,
 #| echo = FALSE
 
-knitr::include_graphics("ex_seq.jpg")
+knitr::include_graphics("../../man/figures/ex_seq.jpg")
 ```
 
 ```{r expals3, fig.cap = "Example of palette type: diverging"}
 #| fig.alt = "Example of palette type: diverging",
 #| out.width = 400,
 #| echo = FALSE
 
-knitr::include_graphics("ex_div.jpg")
+knitr::include_graphics("../../man/figures/ex_div.jpg")
 ```
 
 ```{r expals4, fig.cap = "Example of palette type: cyclic"}
 #| fig.alt = "Example of palette type: cyclic",
 #| out.width = 400,
 #| echo = FALSE
 
-knitr::include_graphics("ex_cyc.jpg")
+knitr::include_graphics("../../man/figures/ex_cyc.jpg")
 ```
 
 ```{r expals5, fig.cap = "Example of palette type: bivariate (seq x seq)"}
 #| fig.alt = "Example of palette type: bivariate (seq x seq)",
 #| out.width = 200,
 #| echo = FALSE
 
-knitr::include_graphics("ex_bivs.jpg")
+knitr::include_graphics("../../man/figures/ex_bivs.jpg")
 ```
 
 ```{r expals6, fig.cap = "Example of palette type: bivariate (seq x cat)"}
 #| fig.alt = "Example of palette type: bivariate (seq x cat)",
 #| out.width = 200,
 #| echo = FALSE
 
-knitr::include_graphics("ex_bivc.jpg")
+knitr::include_graphics("../../man/figures/ex_bivc.jpg")
 ```
 
 ```{r expals7, fig.cap = "Example of palette type: bivariate (seq x div)"}
 #| fig.alt = "Example of palette type: bivariate (seq x div)",
 #| out.width = 200,
 #| echo = FALSE
 
-knitr::include_graphics("ex_bivd.jpg")
+knitr::include_graphics("../../man/figures/ex_bivd.jpg")
 ```
 
 ```{r expals8, fig.cap = "Example of palette type: bivariate (seq x desaturated)"}
 #| fig.alt = "Example of palette type: bivariate (seq x desaturated)",
 #| out.width = 200,
 #| echo = FALSE
 
-knitr::include_graphics("ex_bivg.jpg")
+knitr::include_graphics("../../man/figures/ex_bivg.jpg")
 ```
 
 
@@ -392,7 +392,7 @@ To aid decision making a palette is called fair if the fairness score is at leas
 #| out.width = 300,
 #| echo = FALSE
 
-knitr::include_graphics("fairness.jpg")
+knitr::include_graphics("../../man/figures/fairness.jpg")
 ```
 
 
@@ -441,7 +441,7 @@ For diverging palettes, we calculate the hue widths for both wings. If at least
 #| out.width = 400,
 #| echo = FALSE
 
-knitr::include_graphics("necklace.jpg")
+knitr::include_graphics("../../man/figures/necklace.jpg")
 ```
 
 
@@ -457,7 +457,7 @@ In the middle column two similarity matrices are shown, above for people with no
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cbf_okabe.jpg")
+knitr::include_graphics("../../man/figures/cbf_okabe.jpg")
 ```
 
 
@@ -486,7 +486,7 @@ Figure \@ref(fig:contrast) shows a bar chart of the contrast ratio values of the
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("contrast_powerbi_default.jpg")
+knitr::include_graphics("../../man/figures/contrast_powerbi_default.jpg")
 ```
 
 
@@ -502,7 +502,7 @@ Several visual illusions could appear at equiluminance, such as that the eye has
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics(c("equi1.jpg", "equi2.jpg"))
+knitr::include_graphics(c("../../man/figures/equi1.jpg", "../../man/figures/equi2.jpg"))
 ```
 
 
@@ -533,7 +533,7 @@ Figure \@ref(fig:3dblues) illustrates this illusion with a categorical map of th
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("3Dblues_map.jpg")
+knitr::include_graphics("../../man/figures/3Dblues_map.jpg")
 ```
 
 
@@ -578,7 +578,7 @@ The variety of colors shown in the column headings are generated by the specifie
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("naming_tableau10.jpg")
+knitr::include_graphics("../../man/figures/naming_tableau10.jpg")
 ```
 
 
@@ -610,7 +610,7 @@ The columns on the right-hand side of the colors include symbols on which the us
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("overview_seq2.jpg")
+knitr::include_graphics("../../man/figures/overview_seq2.jpg")
 ```
 
 
@@ -619,7 +619,7 @@ knitr::include_graphics("overview_seq2.jpg")
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("overview_div.jpg")
+knitr::include_graphics("../../man/figures/overview_div.jpg")
 ```
 
 
@@ -633,7 +633,7 @@ The properties fairness, hues, and vividness all use the HCL color space, and ar
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("hcl_carto_safe.jpg")
+knitr::include_graphics("../../man/figures/hcl_carto_safe.jpg")
 ```
 
 
@@ -653,7 +653,7 @@ Fairness and color blind friendliness often present conflicting objectives. Many
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cols4all_fair_sort_cbf.jpg")
+knitr::include_graphics("../../man/figures/cols4all_fair_sort_cbf.jpg")
 ```
 
 
@@ -668,7 +668,7 @@ A severe issue that may induce visual bias for color blind people is illustrated
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cols4all_matplotlib_spectral.jpg")
+knitr::include_graphics("../../man/figures/cols4all_matplotlib_spectral.jpg")
 ```
 
 
@@ -680,7 +680,7 @@ Several spectral sequential palettes from the series \texttt{scico} @scico, \tex
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cols4all_seq_spectral.jpg")
+knitr::include_graphics("../../man/figures/cols4all_seq_spectral.jpg")
 ```
 
 
@@ -689,7 +689,7 @@ knitr::include_graphics("cols4all_seq_spectral.jpg")
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("cols4all_div.jpg")
+knitr::include_graphics("../../man/figures/cols4all_div.jpg")
 ```
 
 
@@ -738,7 +738,7 @@ The used approach to find those palettes was the following:
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("c4a_pals.jpg")
+knitr::include_graphics("../../man/figures/c4a_pals.jpg")
 ```
 
 
@@ -748,7 +748,7 @@ knitr::include_graphics("c4a_pals.jpg")
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("area7.jpg")
+knitr::include_graphics("../../man/figures/area7.jpg")
 ```
 
 
@@ -757,7 +757,7 @@ knitr::include_graphics("area7.jpg")
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("area7d.jpg")
+knitr::include_graphics("../../man/figures/area7d.jpg")
 ```
 
 
@@ -766,7 +766,7 @@ knitr::include_graphics("area7d.jpg")
 #| out.width = 350,
 #| echo = FALSE
 
-knitr::include_graphics(c("line7_wt.jpg", "line7_bk.jpg"))
+knitr::include_graphics(c("../../man/figures/line7_wt.jpg", "../../man/figures/line7_bk.jpg"))
 ```
 
 
@@ -775,7 +775,7 @@ knitr::include_graphics(c("line7_wt.jpg", "line7_bk.jpg"))
 #| out.width = 700,
 #| echo = FALSE
 
-knitr::include_graphics("friendly13.jpg")
+knitr::include_graphics("../../man/figures/friendly13.jpg")
 ```