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PR addressing Issue #233 #234
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Enhancement for Issue #233
Enhancement Implementation, Issue #233
Nov 28, 2022
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Enhancement Implementation, Issue #233
PR addressing Issue #233
Nov 28, 2022
feat: added `size.node` parameter to `network()`. allows users to adjust the size of the vertices. also slightly adjusts how `cex.node.name` is used, provides greater user input to label size.
refactor: bounds `size.node` between 0 - 1.
refactor: changed default value of `size.node`
feat: added `graph.scale` parameter to `network()`. Allows for the general scaling up or down of the entire plot. More specifically, changes the upper bounds of the plotting space to increase/decrease distance and size of vertices
feat: when `shape.node == "none"` in `network()`, a color is now applied
refactor: adjusted the default colours used when applying `network()` in NON-multiblock contexts
tests: added tests for the new parameters and functionality of `network()`
fix: removed part of checks which was causing consistent warnings/errors
fix: added extra check for `shape.node` to avoid error and adjusted scaling of node size
docs: updated documentation for `network()` with new parameters
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Second set of commits on 13/12/2022 reflect initial set of commits, but replicated after the branch was rebased to master following PR #281. |
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This PR contains numerous changes to the
network()
function. Users noted that a lack of control over vertex size and distances made for difficulty in plotting. Vertices frequently overlapped, covering the edges completely - essentially nullifying the purpose of the figure. The following changes were made:graph.scale
parameter: influences the scale of the entire network. Increasing this value essentially "zooms out" from the plot, decreasing vertex size and proximity.network()
functions the same as prior to PR)size.node
parameter: influences the size of the vertices. Works independently fromgraph.scale
.network()
functions the same as prior to PR)shape.node == "none"
, then the vertex labels will be coloured in the same fashion as the vertices would be.network()
on different objects