Final updates for 1.0 release

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: shades
-Version: 0.2.0
-Date: 2016-09-23
+Version: 1.0.0
+Date: 2018-01-10
 Title: Simple Colour Manipulation
 Author: Jon Clayden
 Maintainer: Jon Clayden <code@clayden.org>

LICENCE

@@ -1,3 +1,3 @@
-YEAR: 2016
+YEAR: 2018
 COPYRIGHT HOLDER: Jon Clayden
 ORGANIZATION: University College London

NEWS

@@ -2,6 +2,27 @@ Significant changes to the shades package are laid out below for each release.
 
 ===============================================================================
 
+VERSION 1.0.0
+
+- Support for two new colour spaces has been added: LMS, a direct
+  representation of the response levels of each of the three colour receptor
+  types in the eye; and LCh, a polar representation of Lab space.
+- The new dichromat() function can be used to simulate colour blindness.
+- The gradient() function now additionally supports predefined colour maps from
+  matplotlib and ColorBrewer. Its second argument is now interpreted a little
+  differently.
+- The hueshift() function has been removed, in favour of the more general
+  combination of hue() and delta(). hue(x, delta(y)) is the equivalent of the
+  old hueshift(x,y), and delta() can also be used with other colour properties.
+- New colour property functions lightness() and chroma() have been added.
+- Dimensions are now set when two or more colour properties are changed, and
+  the swatch() visualisation function plots multidimensional shades in a grid.
+- There is now a rev() method for shades.
+- The all.equal() method for shades now passes on its ellipsis argument when
+  checking colour coordinates.
+
+===============================================================================
+
 VERSION 0.2.0
 
 - The package has been reworked to use functions from base R to warp colour

README.Rmd

@@ -47,11 +47,11 @@ Here, we are using the `swatch` function to visualise a set of colours as a seri
 Similarly, we can create a set of new colours by changing the brightness and saturation levels of some base colours, and make the code more readable by using the [`magrittr` pipe operator](https://github.com/smbache/magrittr).
 
 ```{r saturation}
-library(magrittr)
+library(shades); library(magrittr)
 c("red","blue") %>% brightness(0.6) %>% saturation(seq(0,1,0.25)) %>% swatch
 ```
 
-This operation takes the original two colours, reduces their brightness to 60%, assigns a whole series of saturation levels to the result, and then passes it to `swatch` for visualisation. Notice that the final shades are arranged in two rows for convenience, since there are two axes of variation.
+This operation takes the original two colours, reduces their brightness to 60%, assigns a whole series of saturation levels to the result, and then passes it to `swatch` for visualisation. Notice that the pipeline is combinative (like the base function `outer`), returning each combination of parameters in a multidimensional array. The final shades are arranged in two rows by `swatch`, for convenience.
 
 Any of these gradients can be directly passed to a standard graphical function, to be used as a colour scale. However, when choosing a colour scale, it is helpful to bear in mind that some viewers may have a colour vision deficiency (colour blindness), making it harder for them to distinguish certain colours and therefore to see a continuous scale. The `dichromat` function can be used to simulate this.
 

README.md

@@ -64,13 +64,13 @@ Similarly, we can create a set of new colours by changing the brightness and sat
 
 
 ```r
-library(magrittr)
+library(shades); library(magrittr)
 c("red","blue") %>% brightness(0.6) %>% saturation(seq(0,1,0.25)) %>% swatch
 ```
 
 ![plot of chunk saturation](tools/figures/saturation-1.png)
 
-This operation takes the original two colours, reduces their brightness to 60%, assigns a whole series of saturation levels to the result, and then passes it to `swatch` for visualisation. Notice that the final shades are arranged in two rows for convenience, since there are two axes of variation.
+This operation takes the original two colours, reduces their brightness to 60%, assigns a whole series of saturation levels to the result, and then passes it to `swatch` for visualisation. Notice that the pipeline is combinative (like the base function `outer`), returning each combination of parameters in a multidimensional array. The final shades are arranged in two rows by `swatch`, for convenience.
 
 Any of these gradients can be directly passed to a standard graphical function, to be used as a colour scale. However, when choosing a colour scale, it is helpful to bear in mind that some viewers may have a colour vision deficiency (colour blindness), making it harder for them to distinguish certain colours and therefore to see a continuous scale. The `dichromat` function can be used to simulate this.