Specify the name of the objectives and variables in the constructor

README.md

@@ -23,15 +23,31 @@ This repository is an effort to standardize the interface of the **generators**
 Each type of generator (e.g., Nelder-Nead, different flavors of GA, BO, etc.) will be a Python class that defines the following methods:
 
 - **Constructor:**
-  `__init__(self, *args, **kwargs)`:
+  `__init__(self, variables: Dict[str,List[float]], objectives: Dict[str,str], *args, **kwargs)`:
 
-  The constructor will include variable positional and keyword arguments to
+  The contructor has two mandatory arguments:
+
+  - `objectives` is a dictionary that lists the objectives to be optimized for. Each objective is a floating point number (objectives are scalars).
+    - The keys of this dictionary are the names of the objective. (The same names have to be used in the dictionaries passed to `tell`.)
+    - The values can either be `'MINIMIZE'` or `'MAXIMIZE'` to indicate whether the objective is to be maximized or minimized.
+
+  - `variables` is a dictionary that lists the quantities that the generator can vary in order to optimize (i.e. either maximize or minimize) the objectives. Each variable is a floating point number (variables are scalars).
+    - The keys of this dictionary are the names of the variables. (The same names have to be used in the dictionaries passed to `tell`, and are used in the dictionaries returned by `tell`.)
+    - The values are lists of two elements that specify the range of each variable.
+
+  The constructor will also include variable positional and keyword arguments to
   accommodate the different options that each type of generator has.
 
+  Examples:
+
+    ```python
+    >>> generator = NelderMead( variables={"x": [-5.0, 5.0], "y": [-3.0, 2.0]}, objectives={"f": "MAXIMIZE"})
+    ```
+
 - `ask(num_points: Optional[int] = None) -> List[Dict]`:
 
   Returns set of points in the input space, to be evaluated next. Each element of the list is a separate point.
-  Keys of the dictionary correspond to the name of each input variable.
+  Keys of the dictionary include the name of each variable specified in the constructor. Values of the dictionaries are **scalars**.
 
   - When `num_points` is not passed: the generator decides how many points to return.
     Different generators will return different number of points, by default. For instance, the simplex would return 1 or 3 points. A genetic algorithm could return the whole population. Batched Bayesian optimization would return the batch size (i.e., number of points that can be processed in parallel), which would be specified in the constructor.
@@ -50,9 +66,9 @@ Each type of generator (e.g., Nelder-Nead, different flavors of GA, BO, etc.) wi
     [{"x": 1.2, "y": 0.8}, {"x": -0.2, "y": 0.4}, {"x": 4.3, "y": -0.1}]
     ```
 
-- `tell(points: List[Dict])`:
+- `tell(points: List[Dict[str,Any]])`:
 
-  Feeds data (past evaluations) to the generator. Each element of the list is a separate point. Keys of the dictionary correspond to the name of each input and output variable.
+  Feeds data (past evaluations) to the generator. Each element of the list is a separate point. Keys of the dictionary must include to the name of each variable and objective specified in the contructor.
 
   Example: