[Python] Python - Scipy Optimize And Return Value In Flask-Restful

I'm trying to build a REST API using Flask which returns value from Scipy's minimize function. I am able to get a result but I want to expose it in an API call and this code is erroring:

import scipy.stats as sp
from scipy.optimize import minimize
from flask import Flask, g, Response
from flask_restful import Resource, Api, reqparse
import numpy as np

app = Flask(__name__)

api = Api(app)


class Minimize(Resource):
result = None

def _calculate_probability(self, spread, std_dev):
return sp.norm.sf(0.5, spread, scale=std_dev)

def _calculate_mse(self, std_dev):
spread_inputs = np.array(self.spreads)
model_probabilities = self._calculate_probability(spread_inputs, std_dev)
mse = np.sum((model_probabilities - self.expected_probabilities)**2) / len(spread_inputs)
return mse

def __init__(self, expected_probabilities, spreads, std_dev_guess):
self.std_dev_guess = std_dev_guess
self.spreads = spreads
self.expected_probabilities = expected_probabilities

def solve(self):
self.result = minimize(self._calculate_mse, self.std_dev_guess, method='BFGS')

def get(self):
return {'data': self.result}, 200

api.add_resource(Minimize, '/minimize')


I'm able to print an answer to the console:

spreads = [10.5, 9.5, 10, 8.5]
expected_probabilities = [0.8091, 0.7785, 0.7708, 0.7692]
minimizer = Minimize(expected_probabilities, spreads, 12.0)
minimizer.solve()
print(minimizer.get())


I get this:

probability-calculator_1 | ({'data': fun: 0.00018173060393236452
probability-calculator_1 | hess_inv: array([[1381.37379663]])
probability-calculator_1 | jac: array([-1.56055103e-06])
probability-calculator_1 | message: 'Optimization terminated successfully.'
probability-calculator_1 | nfev: 24
probability-calculator_1 | nit: 3
probability-calculator_1 | njev: 8
probability-calculator_1 | status: 0
probability-calculator_1 | success: True
probability-calculator_1 | x: array([11.70822653])}, 200)


But, when I do a GET request to localhost:5000/minimize, this is the error response:

TypeError: __init__() missing 3 required positional arguments: 'expected_probabilities', 'spreads', and
'std_dev_guess'


How do I define the API call so it returns the printed answer?

EDIT: So I have added another class to try and get a response to a POST request.

class MinimisedError(Resource):

def post(self):

parser = reqparse.RequestParser()
parser.add_argument('spread_inputs', action='append', required=True)
parser.add_argument('expected_probabilities',
action='append', required=True)
parser.add_argument('std_dev', required=True)

args = parser.parse_args()

minimizer = Minimize(args.spread_inputs,
args.expected_probabilities, float(args.std_dev))
minimizer.solve()

return {minimizer.get()}, 200

api.add_resource(MinimisedError, '/minimize')


When I try a POST with body

{
"expected_probabilities":[0.8091, 0.7785, 0.7708, 0.7692],
"spread_inputs":[10.5, 9.5, 10, 8.5],
"std_dev":12.0
}


I get this response:

numpy.core._exceptions.UFuncTypeError: ufunc 'subtract' did not contain a loop with signature matching types (dtype('<U32'), dtype('<U32')) -> dtype('<U32')

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