Minor updates to pipelines docs

curvesim/pipelines/__init__.py

@@ -4,9 +4,9 @@
 Pipelines iterate over pools with parameters set by
 :mod:`.param_samplers` and time-series data produced by :mod:`.price_samplers`.
 Each pipeline implements a "strategy" dictating what is done at each timestep
-(e.g., see :func:`.pipelines.arbitrage.strategy`).
+(e.g., see :func:`.arbitrage.strategy`).
 
-Typically, a pipeline takes in :class:`pool_data`; specifies a param_sampler,
+Typically, a pipeline takes in :class:`.PoolData`; specifies a param_sampler,
 price_sampler, and strategy; and returns metrics/results.
 """
 

curvesim/pipelines/arbitrage.py

@@ -43,25 +43,25 @@ def volume_limited_arbitrage(
 
     At each timestep, the pool is arbitraged as close to the prevailing market price
     as possible without surpassing a volume constraint. By default, volume is limited
-    to the total market volume at each timestep, multiplied by the ratio of historical
-    pool volume to total market volume over the whole simulation period (vol_mult).
+    to the total market volume at each timestep, scaled by the proportion of
+    volume attributable to the pool over the whole simulation period (vol_mult).
 
     Parameters
     ----------
     pool_data : :class:`.PoolData`
         Pool data object for the pool of interest.
 
     variable_params : dict, defaults to broad range of A/fee values
-        Pool parameters to vary across simulations. keys: pool parameters,
-        values: iterables of ints
+        Pool parameters to vary across simulations.
+        keys: pool parameters, values: iterables of ints
 
         Example
         --------
         >>> variable_params = {"A": [100, 1000], "fee": [10**6, 4*10**6]}
 
     fixed_params : dict, optional
-        Pool parameters set before all simulations. keys: pool parameters,
-        values: ints
+        Pool parameters set before all simulations.
+        keys: pool parameters, values: ints
 
         Example
         --------

curvesim/pipelines/templates.py

@@ -6,10 +6,13 @@ def run_pipeline(param_sampler, price_sampler, strategy, ncpu=4):
     """
     Core function for running pipelines.
 
+    Typically called within a function specifying the pipeline components
+    (see, e.g., :func:`.volume_limited_arbitrage()`)
+
     Parameters
     ----------
     param_sampler : iterator
-        An terator that returns pool parameters (see :mod:`.param_samplers`).
+        An iterator that returns pool parameters (see :mod:`.param_samplers`).
 
     price_sampler : iterator
         An iterator that returns (minimally) a time-series of prices