Clarify READMEs

Author: IlyaMuravjov

README.md

@@ -10,7 +10,7 @@ and work with them in terms of linear algebra.
 First of all you need to clone repository with its submodules:
 
 ```bash
-git clone --recurse-submodules https://github.com/JetBrains-Research/CFPQ_PyAlgo.git
+git clone --recurse-submodules -b murav/optimize-matrix https://github.com/JetBrains-Research/CFPQ_PyAlgo.git
 cd CFPQ_PyAlgo/ 
 git submodule init
 git submodule update
@@ -37,14 +37,15 @@ First of all you need to install [pygraphblas](https://github.com/michelp/pygrap
 ```bash
 pip3 install pygraphblas==5.1.8.0
 ```
-Secondly you need to install cfpq_data_devtools package and other requirements:
+Secondly you need to install `cfpq_data_devtools` package and other requirements:
 
 ```bash
 cd deps/CFPQ_Data
 pip3 install -r requirements.txt
 python3 setup.py install --user
 
 cd ../../
+pip3 install pygraphblas==5.1.8.0 # optional (needed for legacy algorithms and their tests)
 pip3 install -r requirements.txt
 ```
 To check if the installation was successful you can run simple tests

cfpq_eval/README.md

@@ -8,27 +8,36 @@ integrating with both CFPQ_PyAlgo itself and third-party tools.
 Build and run a Docker container for evaluation using [Dockerfile-all-tools](../Dockerfile-all-tools).
 
 Build Docker image:
-```
-docker build -f Dockerfile-all-tools -t cfpq_eval .
+```bash
+cd .. # Should be run from CFPQ_PyAlgo project root directory
+
+# Load base image
+wget -O pearl.tar.gz https://figshare.com/ndownloader/files/42214812
+docker load --input pearl.tar.gz
+rm pearl.tar.gz
+
+# Build eval image
+docker build -f Dockerfile-all-tools -t cfpq/py_algo_eval .
 ```
 
 Run Docker container:
-```
-docker run -it cfpq_eval bash
+```bash
+docker run -it cfpq/py_algo_eval bash
 ```
 
 ## Running the Script
 
 For detailed information on evaluation script options, execute the following command:
 
-```
-# Should be run from CFPQ_PyAlgo project root directory in cfpq_eval Docker container
+```bash
+cd .. # Should be run from CFPQ_PyAlgo project root directory
 python3 -m cfpq_eval.eval_all_pairs_cflr --help
 ```
 
 The basic command usage is as follows:
 
 ```
+# Should be run in cfpq_eval Docker container
 python3 -m cfpq_eval.eval_all_pairs_cflr algo_config.csv data_config.csv results_path [--rounds ROUNDS] [--timeout TIMEOUT]
 ```