update readme files

fa-compression/README.md

@@ -4,28 +4,27 @@
 ![Codecov](https://img.shields.io/codecov/c/github/unipept/unipept-index?token=IZ75A2FY98&flag=fa-compression&logo=codecov)
 ![Static Badge](https://img.shields.io/badge/doc-rustdoc-blue)
 
-The `fa-compression` library offers compression for Unipept's functional annotation strings. These strings follow a very specific 
-format that the compression algorithm will use to achieve a guaranteed minimal compression of **50%** for both very large and very 
-small input strings. The compression ratio will often situate around **60-70%**.
+The `fa-compression` library offers two compression algorithms for Unipept's functional annotation strings. These strings follow a very specific format that the first compression algorithm will use to achieve a guaranteed minimal compression of **50%** for both very large and very small input strings. The compression ratio will often situate around **68-71%**. This compression algorithm never has to allocate 
+extra memory to build an encoding table or something similar. We can encode each string separately. This is particullary useful when 
+all strings have to be encoded/decoded on their own. There is no need to decode an entire database to only fetch a single entry.
 
-The compression algorithm never has to allocate extra memory to build an encoding table or something similar. We can encode each 
-string separately. This is particullary useful when all strings have to be encoded/decoded on their own. There is no need to decode 
-an entire database to only fetch a single entry.
+The second algorithm will build a global decoding table. This table maps 32-bit integers onto functional annotations. Each annotation in an 
+input string can then be represented by only 3 bytes. The compression ratio will be slightly higher at around **76%**. The performance however, is slightly worse. The allocation of a table, makes it a little bit more complex to use.
 
 ## Example
 
 ```rust
 use fa_compression;
 
 fn main() {
-    let encoded: Vec<u8> = fa_compression::encode(
+    let encoded: Vec<u8> = fa_compression::algorithm1::encode(
         "IPR:IPR016364;EC:1.1.1.-;IPR:IPR032635;GO:0009279;IPR:IPR008816"
     );
 
     // [ 44, 44, 44, 189, 17, 26, 56, 173, 18, 116, 117, 225, 67, 116, 110, 17, 153, 39 ]
     println!("{:?}", encoded);
 
-    let decoded: String = fa_compression::decode(&encoded);
+    let decoded: String = fa_compression::algorithm1::decode(&encoded);
 
     // "EC:1.1.1.-;GO:0009279;IPR:IPR016364;IPR:IPR032635;IPR:IPR008816"
     println!("{:?}", decoded);

sa-mappings/README.md

@@ -0,0 +1,13 @@
+# Suffix Array Mappings
+
+![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/unipept/unipept-index/test.yml?logo=github)
+![Codecov](https://img.shields.io/codecov/c/github/unipept/unipept-index?token=IZ75A2FY98&flag=sa-mappings&logo=codecov)
+![Static Badge](https://img.shields.io/badge/doc-rustdoc-blue)
+
+A suffix array returns a range of matches. This range has to be mapped to some informational data. The `sa-mappings` library 
+offers a few utilities to build these mapping tables. The library offers functionality to map each SA output onto its 
+proteins, taxonomy and functional annotations.
+
+- `sa_mappings::taxonomy::TaxonAggregator` can aggregate a list of taxa.
+- `sa_mappings::functionality::FunctionAggregator` can aggregate a list of functional annotations.
+- `sa_mappings::proteins::Proteins` can map an SA entry to a protein and all its information