update readme

README.md

@@ -49,105 +49,40 @@ Optionally, you can add a message passing mode to each protocol. For example,
 ```
 make run-binary MODE=rrob
 ```
-There are currently four message passing modes:
+There are currently three message passing modes:
 
 `rand:` each round, some randomly selected validators propagate their most recent message to other randomly selected validators, who then create new messages.
 
 `rrob:` each round, the creator of the last round's block sends it to the next receiver, who then creates a block.
 
 `full:` each round, all validators receive all other validators previous messages, and then all create messages.
 
-`nofinal:` each round, two simultaneous round-robin message propagations occur at the same time. This results in validators never being able to finalize later blocks (they may finalize initial blocks, depending on weight distribution).
-
-`binary:` unlike the above message propagation schemes, this changes the protocol to cbc-casper with binary data structures! Instead of a blockchain, this protocol just comes to consensus on a single bit.
-
 By default, a gif and associated images of the simulation will be saved in `graphs/graph_num_0/`. These settings can be modified, along with the number of validators, the number of messages that propagate per round, and the report interval in the `config.ini`.
 
 ### Advanced
 Advanced simulations can be run with a little command line wizardy.
 - First ensure that you are using the virtual environment via: `. venv/bin/activate`
 - Simulations can then be run via `casper.py`. The following are example usages:
 ```
+# get help and all options for casper.py
+python casper.py --help
+
 # run a simulation with 100 validators and random message propagation
-python casper.py rand --validators 100
+python casper.py --protocol blockchain --msg-mode rand --validators 100
 
 # run a simulation without displaying the viewgraphs, but instead save them and create a GIF
-python casper.py rand --hide-display --save
+python casper.py --protocol blockchain --msg-mode rand --display false --save true
 
 # run a simulation with 20 validators and 1000 rounds of round robin message propagation,
 # reporting every 100 rounds
-python casper.py rrob --validators 6 --rounds 300 --report-interval 100
-
-# get help and all options for casper.py
-python casper.py --help
-```
-
-## Write Simulations
-Simulations can be created/managed by `SimulationRunner`. See `casper.py` for sample usage.
+python casper.py --protocol blockchain --msg-mode rrob --validators 6 --rounds 300 --report-interval 100
 
-More sample simulations with data collection will be added soon.
 
-## Run Experiments
-An Experiment runs a type of simulation some number of times, collects some
-specified data on on each simulation and on aggregate of the simulations and
-outputs the results in `.json` and `.csv ` formats for further analysis and visualizations.
-Experimental output is written to `out/{experiment_name-timestamp}/`
-
-The parameters of an experiment are specified via a `.json` file and are run
-using the python script, `run_experiment.py`. For example:
-
-```
-python run_experiment.py experiments/blockchain/fast_test.json
 ```
 
-The following are the fields that make up an experiment to be defined in a `.json` file:
-
-`msg_mode` (string): Specifies the message generation/propagation scheme. The
-available schemes are "rand", "rrob", "full", and "nofinal".
-
-`protocol` (string): Specifies the protocol to test. Available protocols are
-"blockchain", "integer", and "binary".
-
-`network` (string): Specifies the network model test. Available networks are
-"no-delay", "constant", "linear", and "gaussian".
-
-`num_simulations` (number): Specifies the number of simulations to run. Each
-simulation starts with a fresh setup -- messages, validators, etc.
-
-`rounds_per_sim` (number): Specifies the number of rounds of the message
-propagation scheme to run per simulation.
-
-`report_interval` (number): Specifies at which intervals of the message
-propagation to collect data. For example, if `rounds_per_sim` is 100 and `report_interval` is 20,
-the experiment will collect data at round 20, 40, 60, 80, and 100.
-
-`data` (list): Specifies which types of data to collect from the simulations as
-strings. The available types of data are the methods of `Analyzer`. New types of data
-can be added by simply adding a method to Analyzer and referencing the method
-name in `data` of an experiment.
-
-`validator_info` (object): Specifies the parameters for generating a validator
-set for each simulation.
-
-`validator_info.gen_type` (string): Specifies the type of validator generation
-scheme. The available schemes are "gauss" and "weights".
-
-`validator_info.num_validators` (number): [*only "gauss" `gen_type`*]
-Specifies the number of validators per validator set.
-
-`validator_info.mu` (number): [*only "gauss" `gen_type`*]
-Specifies the mean of the gaussian distribution used to generate validator weights.
-
-`validator_info.sigma` (number): [*only "gauss" `gen_type`*]
-Specifies the standard deviation of the gaussian distribution used to generate validator weights.
-
-`validator_info.min_weight` (number): [*only "gauss" `gen_type`*]
-Specifies the absolute minimum validator weight can result from the "gauss"
-`gen_type`
+## Write Simulations
 
-`validator_info.weights` (array): [*only "weights" `gen_type`*]
-Specifies an explicit set of validator weights to be used in each simulation.
-It is formatted as a json array with positive numbers as values.
+COMING SOON...
 
 ## Run Tests
 To run all tests: