generated from feelpp/feelpp-project
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
efa41b4
commit 31bb284
Showing
2 changed files
with
85 additions
and
82 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,85 @@ | ||
| import numpy as np | ||
| import string | ||
| import pytest | ||
| from feelpp.benchmarking.reframe.parameters import ParameterFactory, LinspaceParameter, RangeParameter, GeomspaceParameter, SequenceParameter, RepeatParameter, GeometricParameter, ZipParameter | ||
| from feelpp.benchmarking.reframe.config.configParameters import Parameter | ||
|
|
||
| def createParameterDict(mode,param_config): | ||
| return { "name": "test_param", "mode": mode, mode: param_config } | ||
|
|
||
| def genericParameterTest(mode,param_config,expected): | ||
| param = ParameterFactory.create(Parameter(**createParameterDict(mode,param_config))) | ||
| result = list(param.parametrize()) | ||
| if not expected: | ||
| if mode == "linspace": | ||
| expected = np.linspace(param_config["min"],param_config["max"],param_config["n_steps"],endpoint=True) | ||
| elif mode == "geomspace": | ||
| expected = np.geomspace(param_config["min"],param_config["max"],param_config["n_steps"],endpoint=True) | ||
| elif mode == "geometric": | ||
| expected = param_config["start"] * (param_config["ratio"] ** np.arange(param_config["n_steps"])) | ||
| elif mode == "range": | ||
| expected = np.arange(start=param_config["min"], stop=param_config["max"]+param_config["step"],step=param_config["step"]) | ||
| elif mode == "sequence": | ||
| expected = param_config | ||
| elif mode == "repeat": | ||
| expected = [param_config["value"]]*param_config["count"] | ||
| assert np.array_equal(result, expected) | ||
| return | ||
| elif mode == "zip": | ||
| pass | ||
| else: | ||
| raise ValueError(f"Random Tests for mode {mode} not implemented...") | ||
|
|
||
| assert np.allclose(result, expected, atol=1e-12), f"Expected result does not match for {mode}" | ||
|
|
||
|
|
||
| def parameter_test_cases(): | ||
| return { | ||
| "linspace":[ | ||
| {"param_config":{"min": 0, "max": 10, "n_steps": 5}, "expected":[0.0, 2.5, 5.0, 7.5, 10.0]}, # Basic example | ||
| {"param_config":{"min": -5, "max": 5, "n_steps": 6}, "expected":[-5.0, -3.0, -1.0, 1.0, 3.0, 5.0]}, # oposed min-max | ||
| {"param_config":{"min": -5, "max": 0, "n_steps": 6}, "expected":[-5.0, -4.0, -3.0, -2.0, -1.0, -0.0]}, # negative | ||
| {"param_config":{"min": 10, "max": 0, "n_steps": 5}, "expected":[10.0, 7.5, 5.0, 2.5,0.0]}, # Decreasing | ||
| {"param_config":{"min": 0.0, "max": 0.01, "n_steps": 100}, "expected":np.linspace(0.0, 0.01, 100).tolist()}, # Many steps | ||
| {"param_config":{"min": 0.1, "max": 0.9, "n_steps": 5}, "expected":[0.1, 0.3, 0.5, 0.7, 0.9]}, # Uniform distribution | ||
| {"param_config":{"min": 0, "max": 1000, "n_steps": 1}, "expected":[0.0]}, # Single step (edge case) | ||
| {"param_config":{"min": np.random.uniform(-100,100), "max": np.random.uniform(-100,100), "n_steps": np.random.randint(2,100)}, "expected":None} #Random | ||
| ], | ||
| "geomspace":[ | ||
| {"param_config":{"min": 1, "max": 1000, "n_steps": 4}, "expected":[1, 10, 100, 1000]}, # Simple geometric space | ||
| {"param_config":{"min": 1, "max": 16, "n_steps": 5}, "expected":[1.0, 2.0, 4.0, 8.0, 16.0]}, # Geometric with powers of 2 | ||
| {"param_config":{"min": 1000, "max": 1, "n_steps": 4}, "expected":[1000.0, 100.0, 10.0, 1.0]}, # Decreasing | ||
| {"param_config":{"min": 0.5, "max": 10.75, "n_steps": 6}, "expected":[0.5, 0.92354422, 1.70586787, 3.15088883, 5.81997035, 10.75]}, # float values | ||
| {"param_config":{"min": -1000, "max": -1, "n_steps": 4}, "expected":[-1000.0, -100.0, -10.0, -1.0]}, #Negative | ||
| {"param_config":{"min": np.random.uniform(0,100), "max": np.random.uniform(0,100), "n_steps": np.random.randint(2,100)}, "expected":None} #Random | ||
| ], | ||
| "geometric":[ | ||
| {"param_config":{"start": 1, "ratio": 2, "n_steps": 4}, "expected":[1, 2, 4, 8]}, # Simple geometric space | ||
| {"param_config":{"start": np.random.uniform(-100,100), "ratio": np.random.uniform(-100,100), "n_steps": np.random.randint(1,100)}, "expected":None}, # Random | ||
| ], | ||
| "range":[ | ||
| {"param_config":{"min": np.random.uniform(-100,100), "max": np.random.uniform(-100,100), "step": np.random.uniform(-100,100)}, "expected":None}, #Random | ||
| ], | ||
| "sequence":[ | ||
| {"param_config":np.random.uniform(-100,100,100).tolist(), "expected":None}, #Random | ||
| ], | ||
| "repeat":[ | ||
| {"param_config":{"value":np.random.randint(100),"count":np.random.randint(100)},"expected":None}, #Random | ||
| {"param_config":{"value":np.random.uniform(-100,100),"count":np.random.randint(100)},"expected":None}, #Random | ||
| {"param_config":{"value":np.random.choice(list(string.ascii_letters)),"count":np.random.randint(100)},"expected":None}, #Random | ||
| {"param_config":{"value":[np.random.choice(list(string.ascii_letters))],"count":np.random.randint(100)},"expected":None}, #Random | ||
| {"param_config":{"value":{np.random.choice(list(string.ascii_letters)):np.random.choice(list(string.ascii_letters))},"count":np.random.randint(100)},"expected":None} #Random | ||
|
|
||
| ], | ||
| "zip":[] | ||
| } | ||
|
|
||
|
|
||
| @pytest.mark.parametrize("mode, param_config, expected", [ | ||
| (mode, test_case["param_config"], test_case["expected"]) | ||
| for mode, cases in parameter_test_cases().items() | ||
| for test_case in cases | ||
| ]) | ||
| def test_parameter_parametrization(mode, param_config, expected): | ||
| """Test parameterization for different modes.""" | ||
| genericParameterTest(mode, param_config, expected) |