MCPcopy Create free account

hub / github.com/LangZhong36/immortal-jellyfish-algorithm / functions

Functions148 in github.com/LangZhong36/immortal-jellyfish-algorithm

⨍ Functions 148◇ Types & classes 19
↓ 10 callersMethodargmin
(double[] arr)
java/src/main/java/ija/IJA.java:327
↓ 7 callersMethodclamp
(double v, double lo, double hi)
java/src/main/java/ija/IJA.java:323
↓ 7 callersMethodoptimize
Run IJA on the given objective function. Parameters ---------- objective : callable Scalar-valued functi
python/ija/algorithm.py:127
↓ 7 callersMethodseed
(long v)
java/src/main/java/ija/IJA.java:378
↓ 6 callersFunction_save
(fig, name)
python/experiments/visualize.py:67
↓ 6 callersFunctionclmp
cpp/src/ija.cpp:101
↓ 5 callersFunction_make_result
(best_fit, best_pos, curve)
python/compare/algorithms.py:18
↓ 5 callersFunctionrandn
cpp/src/ija.cpp:23
↓ 4 callersFunctionrandrng
cpp/src/ija.cpp:27
↓ 4 callersMethodsize
()
java/src/main/java/ija/EliteArchive.java:50
↓ 3 callersFunction_dark_ax
(ax)
python/experiments/visualize.py:59
↓ 3 callersFunctionlevy
cpp/src/ija.cpp:89
↓ 3 callersMethodlevySamples
(int size)
java/src/main/java/ija/IJA.java:269
↓ 3 callersFunctionlevy_flight
Generate Lévy-distributed steps via Mantegna's algorithm. Parameters ---------- beta : float Stability index, typically in (
python/ija/operators.py:14
↓ 3 callersFunctionrastrigin
F3 — Rastrigin: 10*d + sum(x_i^2 - 10*cos(2*pi*x_i)). Highly multimodal.
python/benchmarks/functions.py:34
↓ 2 callersFunction_rank_matrix
(results)
python/experiments/visualize.py:159
↓ 2 callersMethodarchiveBud
(double[] xi, double[] archMember, double[] lb, double[] ub)
java/src/main/java/ija/IJA.java:236
↓ 2 callersFunctionarchive_bud
Archive-based sexual reproduction (budding). Generates an offspring by a Lévy-scaled recombination with an archive member.
python/ija/operators.py:134
↓ 2 callersFunctionbench
cpp/src/ija.cpp:35
↓ 2 callersFunctionbudd
cpp/src/ija.cpp:165
↓ 2 callersMethoddistSq
(double[] a, double[] b)
java/src/main/java/ija/IJA.java:317
↓ 2 callersMethodgamma
(double x)
java/src/main/java/ija/IJA.java:283
↓ 2 callersFunctionget_phase
Return the lifecycle phase index (0–3) for a given progress ratio tau.
python/ija/lifecycle.py:18
↓ 2 callersMethodis_populated
(self)
python/ija/archive.py:69
↓ 2 callersFunctionoptm
cpp/src/ija.cpp:324
↓ 2 callersFunctionrandu
cpp/src/ija.cpp:19
↓ 2 callersMethodsample
Return a uniformly random archive member, or None if empty.
python/ija/archive.py:47
↓ 2 callersMethodsample
()
java/src/main/java/ija/EliteArchive.java:45
↓ 2 callersFunctionuarc
cpp/src/ija.cpp:213
↓ 2 callersMethoduniformArray
(int size, double val)
java/src/main/java/ija/IJA.java:349
↓ 2 callersMethodupdate
Merge new candidates into the archive and prune to max_size.
python/ija/archive.py:27
↓ 2 callersMethodupdate
(double[][] population, double[] fits)
java/src/main/java/ija/EliteArchive.java:22
↓ 1 callersMethod_diversity_guard
( self, population: np.ndarray, fitnesses: np.ndarray, lb: np.ndarray,
python/ija/algorithm.py:321
↓ 1 callersMethod_initialise
( self, objective: Callable, dim: int, lb: np.ndarray, ub: np.ndarray,
python/ija/algorithm.py:289
↓ 1 callersFunction_median_curve
(results, func_name)
python/experiments/visualize.py:75
↓ 1 callersFunction_normalise_curve
Normalise a convergence curve to x_out points by linear interpolation.
python/experiments/visualize.py:89
↓ 1 callersMethod_pick_lighthouse
( self, lighthouses: np.ndarray, fitnesses: np.ndarray )
python/ija/algorithm.py:310
↓ 1 callersMethod_select_lighthouses
( self, population: np.ndarray, fitnesses: np.ndarray )
python/ija/algorithm.py:302
↓ 1 callersFunctionaalph
cpp/src/ija.cpp:291
↓ 1 callersMethodackley
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:33
↓ 1 callersMethodadaptiveAlpha
(double tau)
java/src/main/java/ija/IJA.java:300
↓ 1 callersMethodadaptiveNEphyra
(double tau)
java/src/main/java/ija/IJA.java:305
↓ 1 callersFunctionadaptive_alpha
Step-size that decays from alpha_max to alpha_min as tau → 1.
python/ija/lifecycle.py:34
↓ 1 callersFunctionadaptive_n_ephyra
Number of ephyra offspring produced during strobilation. Starts large for diversity, shrinks as tau increases.
python/ija/lifecycle.py:55
↓ 1 callersFunctionapply_levy_exploration
Polyp-phase exploration: heavy-tailed random walk biased toward global best.
python/ija/operators.py:33
↓ 1 callersFunctionapply_lighthouse_attraction
Medusa-phase attraction toward an elite lighthouse position.
python/ija/operators.py:49
↓ 1 callersFunctionapply_pulse_swimming
Sinusoidal bell-contraction swimming with per-agent phase offset.
python/ija/operators.py:67
↓ 1 callersFunctionattn
cpp/src/ija.cpp:124
↓ 1 callersMethodbuild
()
java/src/main/java/ija/IJA.java:379
↓ 1 callersFunctioncallback
(iteration, best_fit, best_pos)
python/examples/quickstart.py:51
↓ 1 callersFunctioncompute_diversity
Normalised mean absolute deviation of the population across all dimensions. Returns a value in [0, 0.5]; values below 0.005 indicate stagnat
python/ija/operators.py:181
↓ 1 callersFunctioncrowding_distance
Compute scalar crowding distances in objective space (1-D case). Used to maintain diversity inside the elite archive.
python/ija/operators.py:196
↓ 1 callersMethoddiversityGuard
(double[][] pop, double[] fits, Function<double[], Double> obj,
java/src/main/java/ija/IJA.java:245
↓ 1 callersFunctiondvrg
cpp/src/ija.cpp:247
↓ 1 callersMethodevaluate
(int fid, double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:83
↓ 1 callersMethodevaluateAll
(Function<double[], Double> obj, double[][] pop)
java/src/main/java/ija/IJA.java:177
↓ 1 callersFunctionexample_basic
()
python/examples/quickstart.py:33
↓ 1 callersFunctionexample_custom_bounds
()
python/examples/quickstart.py:65
↓ 1 callersFunctionexample_reproducibility
()
python/examples/quickstart.py:79
↓ 1 callersFunctionexample_verbose_callback
()
python/examples/quickstart.py:45
↓ 1 callersFunctiongenerate_all
(skip_slow=False)
python/experiments/visualize.py:409
↓ 1 callersMethodgetPhase
(double tau)
java/src/main/java/ija/IJA.java:310
↓ 1 callersFunctiongneph
cpp/src/ija.cpp:313
↓ 1 callersFunctiongphase
cpp/src/ija.cpp:300
↓ 1 callersMethodgriewank
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:41
↓ 1 callersFunctioninit
cpp/src/ija.cpp:112
↓ 1 callersMethodinitialisePopulation
(int dim, double[] lb, double[] ub)
java/src/main/java/ija/IJA.java:169
↓ 1 callersMethodlevy
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:50
↓ 1 callersMethodlevyExploration
(double[] xi, double[] best, double[] lb, double[] ub)
java/src/main/java/ija/IJA.java:183
↓ 1 callersMethodlighthouseAttract
(double[] xi, double[] gs, double intensity, double alpha, double[] lb
java/src/main/java/ija/IJA.java:206
↓ 1 callersMethodlighthouseIntensity
(double distSq, double tau)
java/src/main/java/ija/IJA.java:296
↓ 1 callersFunctionlighthouse_intensity
Inverse-square light intensity with exponential temporal decay. I = I0 / (1 + kappa * d^2) * exp(-lambda * tau)
python/ija/lifecycle.py:42
↓ 1 callersFunctionlintens
cpp/src/ija.cpp:296
↓ 1 callersMethodmaxIter
(int v)
java/src/main/java/ija/IJA.java:369
↓ 1 callersMethodn
(int n)
java/src/main/java/ija/IJA.java:368
↓ 1 callersMethodoptimize
(Function<double[], Double> objective, int dim, double lb, double ub)
java/src/main/java/ija/IJA.java:51
↓ 1 callersFunctionplot_3d_trajectory
()
python/experiments/visualize.py:366
↓ 1 callersFunctionplot_average_rank_bar
(results)
python/experiments/visualize.py:232
↓ 1 callersFunctionplot_boxplots
(results)
python/experiments/visualize.py:272
↓ 1 callersFunctionplot_convergence_curves
(results)
python/experiments/visualize.py:100
↓ 1 callersFunctionplot_lifecycle_diagram
()
python/experiments/visualize.py:324
↓ 1 callersFunctionplot_rank_heatmap
(results)
python/experiments/visualize.py:177
↓ 1 callersFunctionplse
cpp/src/ija.cpp:136
↓ 1 callersFunctionprint_summary_table
(results)
python/experiments/run_all.py:103
↓ 1 callersMethodpulseSwim
(double[] xi, double tau, double phase, double[] lb, double[] ub)
java/src/main/java/ija/IJA.java:218
↓ 1 callersMethodrastrigin
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:27
↓ 1 callersMethodrosenbrock
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:17
↓ 1 callersFunctionrun_all_experiments
()
python/experiments/run_all.py:73
↓ 1 callersFunctionrun_single
(algo_name, spec, seed)
python/experiments/run_all.py:64
↓ 1 callersMethodschwefel
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:63
↓ 1 callersFunctionsenescence_refine
Fine-grained local search during senescence phase. Applies a tight Gaussian perturbation around the global best, with a spread that shri
python/ija/operators.py:157
↓ 1 callersFunctionsig
cpp/src/ija.cpp:287
↓ 1 callersFunctionsigmoid_transition
Smooth sigmoidal blend weight: 0 near start, 1 near end.
python/ija/lifecycle.py:29
↓ 1 callersMethodsortedIndicesDescending
(double[] arr)
java/src/main/java/ija/IJA.java:342
↓ 1 callersMethodsphere
(double[] x)
java/src/main/java/ija/BenchmarkFunctions.java:11
↓ 1 callersFunctionstrob
cpp/src/ija.cpp:183
↓ 1 callersFunctionstrobilate
Strobilation operator: produce n_ephyra candidate offspring and keep the best. Each ephyra is generated by adding a Lévy-scaled Gaussian per
python/ija/operators.py:85
↓ 1 callersMethodstrobilate
(double[] xi, double[] lb, double[] ub, int nEph)
java/src/main/java/ija/IJA.java:193
↓ 1 callersMethodtopKIndices
(double[] arr, int k)
java/src/main/java/ija/IJA.java:333
↓ 1 callersFunctiontransdifferentiate
Opposition-based restart (transdifferentiation). Computes the mirror image of the current position across the search space. Accepts the
python/ija/operators.py:113
next →1–100 of 148, ranked by callers