From fa0ff9d0e527f9e7b4dd8f26af4179f709493ac0 Mon Sep 17 00:00:00 2001
From: Jan Caron <j.caron@fz-juelich.de>
Date: Thu, 30 Oct 2014 00:51:11 +0100
Subject: [PATCH] Minor changes to reconstruction and example_joern
---
pyramid/reconstruction.py | 18 +++++++-----------
scripts/collaborations/example_joern.py | 2 +-
2 files changed, 8 insertions(+), 12 deletions(-)
diff --git a/pyramid/reconstruction.py b/pyramid/reconstruction.py
index 1eff2ea..d36544d 100644
--- a/pyramid/reconstruction.py
+++ b/pyramid/reconstruction.py
@@ -12,16 +12,16 @@ the distribution.
import numpy as np
-from scipy.sparse.linalg import cg
-from scipy.optimize import minimize, leastsq
-
from pyramid.kernel import Kernel
from pyramid.projector import SimpleProjector
from pyramid.phasemapper import PhaseMapperRDFC
-from pyramid.forwardmodel import ForwardModel
-from pyramid.costfunction import Costfunction, CFAdapterScipyCG
+from pyramid.costfunction import Costfunction
from pyramid.magdata import MagData
+from jutil import cg, minimizer
+
+from scipy.optimize import leastsq
+
import logging
@@ -113,13 +113,11 @@ def optimize_linear(data, regularisator=None, maxiter=1000, verbosity=0):
The reconstructed magnetic distribution as a :class:`~.MagData` object.
'''
- import jutil
LOG.debug('Calling optimize_sparse_cg')
# Set up necessary objects:
- fwd_model = ForwardModel(data)
cost = Costfunction(data, regularisator)
print cost(np.zeros(cost.n))
- x_opt = jutil.cg.conj_grad_minimize(cost)
+ x_opt = cg.conj_grad_minimize(cost)
print cost(x_opt)
# Create and return fitting MagData object:
mag_opt = MagData(data.a, np.zeros((3,)+data.dim))
@@ -148,15 +146,13 @@ def optimize_nonlin(data, first_guess=None, regularisator=None):
The reconstructed magnetic distribution as a :class:`~.MagData` object.
'''
- import jutil
LOG.debug('Calling optimize_cg')
if first_guess is None:
first_guess = MagData(data.a, np.zeros((3,)+data.dim))
x_0 = first_guess.mag_vec
- fwd_model = ForwardModel(data)
cost = Costfunction(data, regularisator)
assert len(x_0) == cost.n, (len(x_0), cost.m, cost.n)
- result = jutil.minimizer.minimize(cost, x_0, options={"conv_rel":1e-20}, tol={"max_iteration":1})
+ result = minimizer.minimize(cost, x_0, options={"conv_rel": 1e-20}, tol={"max_iteration": 1})
x_opt = result.x
print cost(x_opt)
mag_opt = MagData(data.a, np.zeros((3,)+data.dim))
diff --git a/scripts/collaborations/example_joern.py b/scripts/collaborations/example_joern.py
index e3b1a4d..4715511 100644
--- a/scripts/collaborations/example_joern.py
+++ b/scripts/collaborations/example_joern.py
@@ -41,7 +41,7 @@ smoothed_pictures = True
lam = 1E-4
order = 1
log = True
-PATH = './'
+PATH = '../../output/joern/'
dirname = PATH
###################################################################################################
# Read in files:
--
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