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Merge pull request #307 from ahmedfgad/master
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Add OpenSSF Action
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ahmedfgad authored Dec 10, 2024
2 parents a9d09b4 + 1b52346 commit a4897fd
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73 changes: 73 additions & 0 deletions .github/workflows/scorecard.yml
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# This workflow uses actions that are not certified by GitHub. They are provided
# by a third-party and are governed by separate terms of service, privacy
# policy, and support documentation.

name: Scorecard supply-chain security
on:
# For Branch-Protection check. Only the default branch is supported. See
# https://github.com/ossf/scorecard/blob/main/docs/checks.md#branch-protection
branch_protection_rule:
# To guarantee Maintained check is occasionally updated. See
# https://github.com/ossf/scorecard/blob/main/docs/checks.md#maintained
schedule:
- cron: '42 5 * * 2'
push:
branches: [ "master" ]

# Declare default permissions as read only.
permissions: read-all

jobs:
analysis:
name: Scorecard analysis
runs-on: ubuntu-latest
permissions:
# Needed to upload the results to code-scanning dashboard.
security-events: write
# Needed to publish results and get a badge (see publish_results below).
id-token: write
# Uncomment the permissions below if installing in a private repository.
# contents: read
# actions: read

steps:
- name: "Checkout code"
uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
with:
persist-credentials: false

- name: "Run analysis"
uses: ossf/scorecard-action@0864cf19026789058feabb7e87baa5f140aac736 # v2.3.1
with:
results_file: results.sarif
results_format: sarif
# (Optional) "write" PAT token. Uncomment the `repo_token` line below if:
# - you want to enable the Branch-Protection check on a *public* repository, or
# - you are installing Scorecard on a *private* repository
# To create the PAT, follow the steps in https://github.com/ossf/scorecard-action?tab=readme-ov-file#authentication-with-fine-grained-pat-optional.
# repo_token: ${{ secrets.SCORECARD_TOKEN }}

# Public repositories:
# - Publish results to OpenSSF REST API for easy access by consumers
# - Allows the repository to include the Scorecard badge.
# - See https://github.com/ossf/scorecard-action#publishing-results.
# For private repositories:
# - `publish_results` will always be set to `false`, regardless
# of the value entered here.
publish_results: true

# Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
# format to the repository Actions tab.
- name: "Upload artifact"
uses: actions/upload-artifact@97a0fba1372883ab732affbe8f94b823f91727db # v3.pre.node20
with:
name: SARIF file
path: results.sarif
retention-days: 5

# Upload the results to GitHub's code scanning dashboard (optional).
# Commenting out will disable upload of results to your repo's Code Scanning dashboard
- name: "Upload to code-scanning"
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: results.sarif
15 changes: 12 additions & 3 deletions pygad/pygad.py
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Expand Up @@ -1135,9 +1135,8 @@ def __init__(self,

# Validate delay_after_gen
if type(delay_after_gen) in GA.supported_int_float_types:
if delay_after_gen != 0.0:
if not self.suppress_warnings:
warnings.warn("The 'delay_after_gen' parameter is deprecated starting from PyGAD 3.3.0. To delay or pause the evolution after each generation, assign a callback function/method to the 'on_generation' parameter to adds some time delay.")
if not self.suppress_warnings:
warnings.warn("The 'delay_after_gen' parameter is deprecated starting from PyGAD 3.3.0. To delay or pause the evolution after each generation, assign a callback function/method to the 'on_generation' parameter to adds some time delay.")
if delay_after_gen >= 0.0:
self.delay_after_gen = delay_after_gen
else:
Expand Down Expand Up @@ -1914,6 +1913,16 @@ def run(self):
# Measuring the fitness of each chromosome in the population. Save the fitness in the last_generation_fitness attribute.
self.last_generation_fitness = self.cal_pop_fitness()

# Know whether the problem is SOO or MOO.
if type(self.last_generation_fitness[0]) in GA.supported_int_float_types:
# Single-objective problem.
# If the problem is SOO, the parent selection type cannot be nsga2 or tournament_nsga2.
if self.parent_selection_type in ['nsga2', 'tournament_nsga2']:
raise TypeError(f"Incorrect parent selection type. The fitness function returned a single numeric fitness value which means the problem is single-objective. But the parent selection type {self.parent_selection_type} is used which only works for multi-objective optimization problems.")
elif type(self.last_generation_fitness[0]) in [list, tuple, numpy.ndarray]:
# Multi-objective problem.
pass

best_solution, best_solution_fitness, best_match_idx = self.best_solution(pop_fitness=self.last_generation_fitness)

# Appending the best solution in the initial population to the best_solutions list.
Expand Down

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