From b81cb2050693bcd3e9f19aba2a768fcaec02d272 Mon Sep 17 00:00:00 2001
From: Theo Steininger <theo.steininger@ultimanet.de>
Date: Tue, 18 Jul 2017 15:04:23 +0200
Subject: [PATCH] Added dtype option to prober.

---
 nifty/minimization/line_searching/line_search.py | 3 ---
 nifty/probing/prober/prober.py                   | 5 ++++-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/nifty/minimization/line_searching/line_search.py b/nifty/minimization/line_searching/line_search.py
index 6debbc5d2..93ede56af 100644
--- a/nifty/minimization/line_searching/line_search.py
+++ b/nifty/minimization/line_searching/line_search.py
@@ -44,9 +44,6 @@ class LineSearch(Loggable, object):
     __metaclass__ = abc.ABCMeta
 
     def __init__(self):
-
-
-
         self.line_energy = None
         self.f_k_minus_1 = None
         self.preferred_initial_step_size = None
diff --git a/nifty/probing/prober/prober.py b/nifty/probing/prober/prober.py
index b2f85f543..f292c495f 100644
--- a/nifty/probing/prober/prober.py
+++ b/nifty/probing/prober/prober.py
@@ -37,7 +37,8 @@ class Prober(object):
     """
 
     def __init__(self, domain=None, distribution_strategy=None, probe_count=8,
-                 random_type='pm1', compute_variance=False):
+                 random_type='pm1', probe_dtype=np.float,
+                 compute_variance=False):
 
         self._domain = utilities.parse_domain(domain)
         self._distribution_strategy = \
@@ -45,6 +46,7 @@ class Prober(object):
         self._probe_count = self._parse_probe_count(probe_count)
         self._random_type = self._parse_random_type(random_type)
         self.compute_variance = bool(compute_variance)
+        self.probe_dtype = np.dtype(probe_dtype)
 
     # ---Properties---
 
@@ -104,6 +106,7 @@ class Prober(object):
         """ a random-probe generator """
         f = Field.from_random(random_type=self.random_type,
                               domain=self.domain,
+                              dtype=self.probe_dtype,
                               distribution_strategy=self.distribution_strategy)
         uid = np.random.randint(1e18)
         return (uid, f)
-- 
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