From 42d9419188f21f109c396ae7804fd3cdfa52ad7e Mon Sep 17 00:00:00 2001
From: Bas Nijholt <basnijholt@gmail.com>
Date: Thu, 22 Nov 2018 13:42:22 +0100
Subject: [PATCH] test all the different loss functions in each test
---
adaptive/learner/learner1D.py | 1 +
adaptive/tests/test_learners.py | 28 ++++++++++++++++++++--------
2 files changed, 21 insertions(+), 8 deletions(-)
diff --git a/adaptive/learner/learner1D.py b/adaptive/learner/learner1D.py
index 4f705c90..c0262ed6 100644
--- a/adaptive/learner/learner1D.py
+++ b/adaptive/learner/learner1D.py
@@ -123,6 +123,7 @@ def triangle_loss(xs, ys):
def curvature_loss_function(area_factor=1, euclid_factor=0.02, horizontal_factor=0.02):
+ # XXX: add a doc-string
@uses_nth_neighbors(1)
def curvature_loss(xs, ys):
xs_middle = xs[1:3]
diff --git a/adaptive/tests/test_learners.py b/adaptive/tests/test_learners.py
index a518f264..0f8b1e95 100644
--- a/adaptive/tests/test_learners.py
+++ b/adaptive/tests/test_learners.py
@@ -15,14 +15,15 @@ import numpy as np
import pytest
import scipy.spatial
-from ..learner import (AverageLearner, BalancingLearner, DataSaver,
+import adaptive
+from adaptive.learner import (AverageLearner, BalancingLearner, DataSaver,
IntegratorLearner, Learner1D, Learner2D, LearnerND)
-from ..runner import simple
+from adaptive.runner import simple
try:
import skopt
- from ..learner import SKOptLearner
+ from adaptive.learner import SKOptLearner
except ModuleNotFoundError:
SKOptLearner = None
@@ -75,26 +76,37 @@ def maybe_skip(learner):
# returns a random value for that parameter.
-@learn_with(Learner1D, bounds=(-1, 1))
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.default_loss)
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.uniform_loss)
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.curvature_loss_function())
def quadratic(x, m: uniform(0, 10), b: uniform(0, 1)):
return m * x**2 + b
-@learn_with(Learner1D, bounds=(-1, 1))
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.default_loss)
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.uniform_loss)
+@learn_with(Learner1D, bounds=(-1, 1), loss_per_interval=adaptive.learner.learner1D.curvature_loss_function())
def linear_with_peak(x, d: uniform(-1, 1)):
a = 0.01
return x + a**2 / (a**2 + (x - d)**2)
-@learn_with(LearnerND, bounds=((-1, 1), (-1, 1)))
-@learn_with(Learner2D, bounds=((-1, 1), (-1, 1)))
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.default_loss)
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.std_loss)
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.uniform_loss)
+@learn_with(Learner2D, bounds=((-1, 1), (-1, 1)), loss_per_triangle=adaptive.learner.learner2D.default_loss)
+@learn_with(Learner2D, bounds=((-1, 1), (-1, 1)), loss_per_triangle=adaptive.learner.learner2D.uniform_loss)
+@learn_with(Learner2D, bounds=((-1, 1), (-1, 1)), loss_per_triangle=adaptive.learner.learner2D.minimize_triangle_surface_loss)
+@learn_with(Learner2D, bounds=((-1, 1), (-1, 1)), loss_per_triangle=adaptive.learner.learner2D.resolution_loss_function())
def ring_of_fire(xy, d: uniform(0.2, 1)):
a = 0.2
x, y = xy
return x + math.exp(-(x**2 + y**2 - d**2)**2 / a**4)
-@learn_with(LearnerND, bounds=((-1, 1), (-1, 1), (-1, 1)))
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.default_loss)
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.std_loss)
+@learn_with(LearnerND, bounds=((-1, 1), (-1, 1), (-1, 1)), loss_per_simplex=adaptive.learner.learnerND.uniform_loss)
def sphere_of_fire(xyz, d: uniform(0.2, 1)):
a = 0.2
x, y, z = xyz
--
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