__init__.py 2.74 KB
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## NIFTY (Numerical Information Field Theory) has been developed at the
## Max-Planck-Institute for Astrophysics.
##
## Copyright (C) 2013 Max-Planck-Society
##
## Author: Marco Selig
## Project homepage: <http://www.mpa-garching.mpg.de/ift/nifty/>
##
## This program is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
## See the GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program. If not, see <http://www.gnu.org/licenses/>.

from __future__ import division
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import matplotlib as mpl
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mpl.use('Agg')

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from .version import __version__

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import dummys

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# it is important to import config before d2o such that NIFTy is able to
# pre-create d2o's configuration object with the corrected path
from config import about,\
                   dependency_injector,\
                   nifty_configuration,\
                   d2o_configuration
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from d2o import distributed_data_object, d2o_librarian
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from nifty_cmaps import ncmap
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from field import Field
from space import Space

# this line exists for compatibility reasons
# TODO: Remove this once the transition to field types is done.
from space import Space as point_space
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from nifty_random import random
from nifty_simple_math import *
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from nifty_utilities import *
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from field_types import FieldType,\
                        FieldArray
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from operators import *
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from power import PowerSpace,\
                  RGPowerSpace,\
                  LMPowerSpace

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## optional submodule `rg`
try:
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    from rg import RGSpace,\
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                    power_backward_conversion_rg,\
                    power_forward_conversion_rg
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    from nifty_paradict import rg_space_paradict
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except(ImportError):
    pass

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## optional submodule `lm`
try:
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    from lm import LMSpace,\
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                    power_backward_conversion_lm,\
                    power_forward_conversion_lm
    from nifty_paradict import lm_space_paradict

    try:
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        from lm import GLSpace
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        from nifty_paradict import gl_space_paradict
    except(ImportError):
        pass
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    try:
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        from lm import HPSpace
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        from nifty_paradict import hp_space_paradict
    except(ImportError):
        pass
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except(ImportError):
    pass

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from demos import get_demo_dir
from pickling import _pickle_method, _unpickle_method

#import pyximport; pyximport.install(pyimport = True)
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from transforms import tf as transformator