[WIP] Adding filtering capacity when requesting layers

[annakrystalli]

Work in progress - Not Ready to Merge

@salvafern , I've made a start on introducing filtering capacity. Feel free to test this branch out if you like. Feedback welcome!

Still needs tests and a good vignette so feel free to share any interesting examples if you come up with any. I 've made a list of examples to include below.

• Added facility for passing cql filters to emodnet_get_layers()
• Added suite of functions to get, summarise and present layer and feature metadata to facilitate filtering
• Add tests for attribute functions
• Add tests for filtering
• Add vignette to demo more complex use of filtering including
  • Combination of multiple conditional predicates
  • Filtering numerical variable with comparison and range predicates
  • Temporal predicates
  • bbox filtering
  • other spatial predicates like INTERSECTS

[annakrystalli]

FYI, in the previous commits, I'd written function to present attribute data which were erroneously based on cached data! 🤦‍♀️

I've rewritten then to extract data either from layer metadata or from the server by only downloading attribute data (which is generally much faster without the geometries).

Have now also added tests for the new functions

[codecov-commenter]

Codecov Report

Merging #17 (00c1ae4) into master (3ba5d0e) will decrease coverage by 7.67%.
The diff coverage is 75.86%.

❗ Current head 00c1ae4 differs from pull request most recent head 52d50cf. Consider uploading reports for the commit 52d50cf to get more accurate results

@@            Coverage Diff             @@
##           master      #17      +/-   ##
==========================================
- Coverage   91.11%   83.43%   -7.68%     
==========================================
  Files           3        4       +1     
  Lines          90      169      +79     
==========================================
+ Hits           82      141      +59     
- Misses          8       28      +20     

Impacted Files	Coverage Δ
R/layers.R	66.66% <42.85%> (-16.67%)	⬇️
R/layer_attributes.R	85.93% <85.93%> (ø)
R/info.R	94.59% <100.00%> (ø)

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