Organizing and building a numpy array for a dynamic equation input

Question

I'm not sure if my post question makes lots of sense; however, I'm building an input array for a class/function that takes in a lot of user inputed data and outputs a numpy array.

# I'm trying to build an input array that should include following information:
'''
* zone_id - id from db - int  
* model size - int
  * type of analysis - one of the following:
    * type 1 - int or string
    * type 2 - int or string
    * type 3 - int or string
  * model purposes:
    * default: ONE, TWO, THREE #this is just a title of the purpose
    * Custom: default + others (anywhere from 0 to 15 purposes)
  * Modeling step 1: some socio economic factors #produces results 1
  * Modeling step 2: 
    * Default: equation coefficients for retail/non retail
    * Custom: equation coefficients for each extra activities as defined by
      the user
    * produces results 2

Example array:
  def_array = (zone_id, model_size, analysis_type,
               model_purpose[],
               socio_economics[],
               socio_coefficients[] )
'''
# Numerical example:
  my_arr = [np.array([ 10001, 1, 2,
                     [ 'ONE', 'TWO', 'THREE', 'FOUR', 'FIVE' ],
                     [ {'retail':500, 'non_retail':300, 'school':300', 'other':900} ],
                     [ {'retail':500, 'non_retail':300, 'school':300', 'other':900} ],
                     [ {'ONE':{'retail':.5, 'non_retail':1.7, 'school':.4', 'other':4.7},
                       {'TWO':{'retail':.2, 'non_retail':2.5, 'school':.5', 'other':4.3},
                       {'THREE':{'retail':.3, 'non_retail':2.3, 'school':.6', 'other':2.2},
                       {'FOUR':{'retail':.4, 'non_retail':1.1, 'school':.7', 'other':1.0},
                       {'FIVE':{'retail':7, 'non_retail':2, 'school':3', 'other':1} ] ])

# this array will be inserted into 3 functions and together should return the following array:
arr_results = [np.array([ 10001, one_1, TWO_1, THREE_1, FOUR_1, FIVE_1, ONE_2, TWO_2, THREE_2, FOUR_2, FIVE_2],
                        [10002, .... ,] ])

• What are/is my best option(s) in defining the input array(s)?

Answer 1

Numpy arrays are the wrong datatype here: they are designed for numeric manipulations of large amounts of similar data (e.g. large matrices). It looks like you could just use a dict:

options = {
    "zone_id": 10001,
    "model_size": 1,
    "analysis_type": 2,
    "model_purposes": [ "ONE", ... ]
    ...
}

You could then pass this on to a function, either as the dictionary or by unpacking it into names arguments using **:

def do_stuff(zone_id=10001, model_size=1, ...):
    ...

do_stuff(**options)

---

If you want a more complicated options datatype (e.g. if some of the options need to be calculated on the fly or depend on others), you could use a specialised Options class (though be warned, this is almost certainly overkill);

class Options:
    def __init__(self):
        # set some default values
        self.zone_id = 10001

    def populate_values(self):
        # maybe handle some user input?
        self.name = input("name: ")

    # use a property to calculate model_size on the fly
    @property
    def model_size(self):
        return 2-1

and then

options = Options()
options.populate_values()
print(options.model_size)