Add Constraint about piecewise_linear_fit_py HOT 4 CLOSED

I could potentially create a constrained fit where each breakpoint is subjected to per-determined constraints. The following code sets up this constraint lower and upper limits, just as an example.

# for two breakpoints; arbitrary example 
# 0.1 <= breakpoint[0] <= 0.15
# 0.5 <= breakpoint[1] <= 0.7
g = np.zeros((2, 2)  # constraints
g[0, 0] = 0.1
g[0, 1] = 0.15
g[1, 0] = 0.5
g[1, 1] = 0.7

Then the optimization would find the best breakpoint subject to g.

Do I understand this correctly?

from piecewise_linear_fit_py.

For now this could be done using a custom optimizer like https://jekel.me/piecewise_linear_fit_py/examples.html#use-custom-optimization-routine where you manually specify the bounds.

I'll try to include an optional bounds parameter in the fitting routines for this case.

from piecewise_linear_fit_py.

@adussarps I'm not sure if I understand your request to constrain linear coefficients, but I added an option to constrain the search space for breakpoints. Does this example solver your issue? or are you looking to add constraints for each slope (and the change from the previous slope)?

from piecewise_linear_fit_py.

Yes it's fine thanks!!

from piecewise_linear_fit_py.