From bf0107b1e8763ef98eb32dab2b05dd53b9669c83 Mon Sep 17 00:00:00 2001
From: Bas Nijholt <basnijholt@gmail.com>
Date: Fri, 8 Sep 2017 14:17:25 +0200
Subject: [PATCH] 2D: remove dtype argument from __init__, fix it to float
---
adaptive/learner.py | 6 ++----
1 file changed, 2 insertions(+), 4 deletions(-)
diff --git a/adaptive/learner.py b/adaptive/learner.py
index 57d53900..e5e88f29 100644
--- a/adaptive/learner.py
+++ b/adaptive/learner.py
@@ -582,8 +582,6 @@ class Learner2D(BaseLearner):
bounds : list of 2-tuples
A list ``[(a1, b1), (a2, b2)]`` containing bounds,
one per dimension.
- dtype : dtype, optional
- Type of data from function. Default: float (real-valued)
Attributes
----------
@@ -614,14 +612,14 @@ class Learner2D(BaseLearner):
it, your function needs to be slow enough to compute.
"""
- def __init__(self, function, bounds, dtype=float):
+ def __init__(self, function, bounds):
self.function = function
self.ndim = len(bounds)
if self.ndim != 2:
raise ValueError("Only 2-D sampling supported.")
self.bounds = tuple([(float(a), float(b)) for a, b in bounds])
self._points = np.zeros([100, self.ndim])
- self._values = np.zeros([100], dtype)
+ self._values = np.zeros([100], dtype=float)
self.n = 0
self.nstack = 10
self._stack = []
--
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