From d24cc30bd0e552747768428fc3ac655e38b88d4e Mon Sep 17 00:00:00 2001
From: Martin Reinecke <martin@mpa-garching.mpg.de>
Date: Mon, 2 Jul 2018 14:40:45 +0200
Subject: [PATCH] more MPI fixes
---
demos/getting_started_1.py | 2 +-
nifty5/library/point_sources.py | 22 +++++++++++-----------
2 files changed, 12 insertions(+), 12 deletions(-)
diff --git a/demos/getting_started_1.py b/demos/getting_started_1.py
index 54399816f..fa3e88469 100644
--- a/demos/getting_started_1.py
+++ b/demos/getting_started_1.py
@@ -14,7 +14,7 @@ def make_chess_mask():
def make_random_mask():
mask = ift.from_random('pm1', position_space)
mask = (mask+1)/2
- return mask.val
+ return mask.to_global_data()
if __name__ == '__main__':
diff --git a/nifty5/library/point_sources.py b/nifty5/library/point_sources.py
index eb7e4325a..9e97ca502 100644
--- a/nifty5/library/point_sources.py
+++ b/nifty5/library/point_sources.py
@@ -21,40 +21,40 @@ class PointSources(Model):
@property
@memo
def value(self):
- points = self.position['points'].to_global_data()
+ points = self.position['points'].local_data
points = np.clip(points, None, 8.2)
- points = Field(self.position['points'].domain, points)
+ points = Field.from_local_data(self.position['points'].domain, points)
return self.IG(points, self._alpha, self._q)
@property
@memo
def gradient(self):
- u = self.position['points']
- inner = norm.pdf(u.val)
- outer_inv = invgamma.pdf(invgamma.ppf(norm.cdf(u.val),
+ u = self.position['points'].local_data
+ inner = norm.pdf(u)
+ outer_inv = invgamma.pdf(invgamma.ppf(norm.cdf(u),
self._alpha,
scale=self._q),
self._alpha, scale=self._q)
# FIXME
outer_inv = np.clip(outer_inv, 1e-20, None)
outer = 1/outer_inv
- grad = Field(u.domain, val=inner*outer)
+ grad = Field.from_local_data(u.domain, inner*outer)
grad = makeOp(MultiField({'points': grad}))
return SelectionOperator(grad.target, 'points')*grad
@staticmethod
def IG(field, alpha, q):
- foo = invgamma.ppf(norm.cdf(field.val), alpha, scale=q)
- return Field(field.domain, val=foo)
+ foo = invgamma.ppf(norm.cdf(field.local_data), alpha, scale=q)
+ return Field.from_local_data(field.domain, foo)
@staticmethod
def IG_prime(field, alpha, q):
- inner = norm.pdf(field.val)
- outer = invgamma.pdf(invgamma.ppf(norm.cdf(field.val), alpha, scale=q), alpha, scale=q)
+ inner = norm.pdf(field.local_data)
+ outer = invgamma.pdf(invgamma.ppf(norm.cdf(field.local_data), alpha, scale=q), alpha, scale=q)
# # FIXME
# outer = np.clip(outer, 1e-20, None)
outer = 1/outer
- return Field(field.domain, val=inner*outer)
+ return Field.from_local_data(field.domain, inner*outer)
@staticmethod
def inverseIG(u, alpha, q):
--
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