Skip to content

changed deprecated numpy.float to float #168

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Apr 3, 2023
Merged

changed deprecated numpy.float to float #168

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions pygad.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1844,8 +1844,8 @@ def roulette_wheel_selection(self, fitness, num_parents):
if fitness_sum == 0:
raise ZeroDivisionError("Cannot proceed because the sum of fitness values is zero. Cannot divide by zero.")
probs = fitness / fitness_sum
probs_start = numpy.zeros(probs.shape, dtype=numpy.float) # An array holding the start values of the ranges of probabilities.
probs_end = numpy.zeros(probs.shape, dtype=numpy.float) # An array holding the end values of the ranges of probabilities.
probs_start = numpy.zeros(probs.shape, dtype=float) # An array holding the start values of the ranges of probabilities.
probs_end = numpy.zeros(probs.shape, dtype=float) # An array holding the end values of the ranges of probabilities.

curr = 0.0

Expand Down Expand Up @@ -1888,8 +1888,8 @@ def stochastic_universal_selection(self, fitness, num_parents):
if fitness_sum == 0:
raise ZeroDivisionError("Cannot proceed because the sum of fitness values is zero. Cannot divide by zero.")
probs = fitness / fitness_sum
probs_start = numpy.zeros(probs.shape, dtype=numpy.float) # An array holding the start values of the ranges of probabilities.
probs_end = numpy.zeros(probs.shape, dtype=numpy.float) # An array holding the end values of the ranges of probabilities.
probs_start = numpy.zeros(probs.shape, dtype=float) # An array holding the start values of the ranges of probabilities.
probs_end = numpy.zeros(probs.shape, dtype=float) # An array holding the end values of the ranges of probabilities.

curr = 0.0

Expand Down