Exponential Equation

exponential_equation(first_constant, second_constant, precision=4)

Generates an exponential function to provide evaluations at variable inputs

Parameters

• first_constant (int or float) – Constant multiple of the resultant exponential function; if zero, it will be converted to a small, non-zero decimal value (e.g., 0.0001)

• second_constant (int or float) – Base rate of variable of the resultant exponential function; if zero, it will be converted to a small, non-zero decimal value (e.g., 0.0001)

• precision (int, default=4) – Maximum number of digits that can appear after the decimal place of the resultant roots

Raises

• TypeError – First two arguments must be integers or floats

• ValueError – Last argument must be a positive integer

Returns

evaluation – Function for evaluating an exponential equation when passed any integer or float argument

Return type

func

See also

exponential_derivatives(), exponential_integral(), exponential_roots(), exponential_model()

Notes

• Standard form of an exponential function: \(f(x) = a\cdot{b^x}\)

• Exponential Functions

Examples

Import exponential_equation function from regressions library

>>> from regressions.analyses.equations.exponential import exponential_equation

Create an exponential function with coefficients 2 and 3, then evaluate it at 10

>>> evaluation_first = exponential_equation(2, 3)
>>> print(evaluation_first(10))
118098.0

Create an exponential function with coefficients -2 and 3, then evaluate it at 10

>>> evaluation_second = exponential_equation(-2, 3)
>>> print(evaluation_second(10))
-118098.0

Create an exponential function with all inputs set to 0, then evaluate it at 10

>>> evaluation_zero = exponential_equation(0, 0)
>>> print(evaluation_zero(10))
0.0001