relative imports for all modules

hera_pspec/__init__.py

@@ -1,13 +1,13 @@
 """
 __init__.py file for hera_pspec
 """
-from hera_pspec import version, conversions, grouping, pspecbeam, plot, pstokes, testing
-from hera_pspec import uvpspec_utils as uvputils
+from . import version, conversions, grouping, pspecbeam, plot, pstokes, testing
+from . import uvpspec_utils as uvputils
 
-from hera_pspec.uvpspec import UVPSpec
-from hera_pspec.pspecdata import PSpecData
-from hera_pspec.container import PSpecContainer
-from hera_pspec.parameter import PSpecParam
-from hera_pspec.pspecbeam import PSpecBeamUV, PSpecBeamGauss, PSpecBeamFromArray
+from .uvpspec import UVPSpec
+from .pspecdata import PSpecData
+from .container import PSpecContainer
+from .parameter import PSpecParam
+from .pspecbeam import PSpecBeamUV, PSpecBeamGauss, PSpecBeamFromArray
 
 __version__ = version.version

hera_pspec/grouping.py

@@ -1,13 +1,12 @@
 import numpy as np
 from collections import OrderedDict as odict
-from hera_pspec import uvpspec_utils as uvputils
-from hera_pspec import utils, version
 import random
 import copy
 import argparse
 from astropy import stats as astats
 import os
 
+from . import utils, version, uvpspec_utils as uvputils
 
 def group_baselines(bls, Ngroups, keep_remainder=False, randomize=False,
                     seed=None):

hera_pspec/noise.py

@@ -1,10 +1,11 @@
 import numpy as np
 import os
-from hera_pspec import conversions, pspecbeam
 import copy
 import ast
 from collections import OrderedDict as odict
 
+from . import conversions, pspecbeam
+
 
 def calc_P_N(scalar, Tsys, t_int, Ncoherent=1, Nincoherent=None, form='Pk', k=None, component='real'):
     """

hera_pspec/pspecbeam.py

@@ -1,13 +1,13 @@
 import numpy as np
 import os
-import hera_pspec.conversions as conversions
-import hera_pspec.uvpspec_utils as uvputils
 import scipy.integrate as integrate
 from scipy.interpolate import interp1d
 from pyuvdata import UVBeam, utils as uvutils
 import aipy
 from collections import OrderedDict as odict
 
+from . import conversions as conversions, uvpspec_utils as uvputils
+
 
 def _compute_pspec_scalar(cosmo, beam_freqs, omega_ratio, pspec_freqs, 
                           num_steps=5000, taper='none', little_h=True, 

hera_pspec/pspecdata.py

@@ -4,8 +4,6 @@
 import copy, operator, itertools, sys
 from collections import OrderedDict as odict
 import hera_cal as hc
-from hera_pspec import uvpspec, utils, version, pspecbeam, container
-from hera_pspec import uvpspec_utils as uvputils
 from pyuvdata import utils as uvutils
 import datetime
 import time
@@ -16,6 +14,9 @@
 import json
 import uvtools.dspec as dspec
 
+from . import uvpspec, utils, version, pspecbeam, container, uvpspec_utils as uvputils
+
+
 class PSpecData(object):
 
     def __init__(self, dsets=[], wgts=None, dsets_std=None, labels=None,

hera_pspec/pstokes.py

@@ -4,9 +4,9 @@
 import numpy as np, os
 import pyuvdata
 import copy
-from hera_pspec import version
 from collections import OrderedDict as odict
 
+from . import version
 
 # Weights used in forming Stokes visibilities.
 # See pyuvdata.utils.polstr2num for conversion between polarization string

hera_pspec/testing.py

@@ -2,11 +2,11 @@
 import numpy as np
 import copy, operator, itertools
 from collections import OrderedDict as odict
-from hera_pspec import uvpspec, pspecdata, conversions, pspecbeam, utils
 from pyuvdata import UVData
 from hera_cal.utils import JD2LST
 from scipy import stats
-import hera_pspec.uvpspec_utils as uvputils
+
+from . import uvpspec, pspecdata, conversions, pspecbeam, utils, uvpspec_utils as uvputils
 
 
 def build_vanilla_uvpspec(beam=None):

hera_pspec/utils.py

@@ -3,13 +3,15 @@
 import itertools, argparse, glob
 import traceback, operator
 import aipy, uvtools
-from hera_pspec.conversions import Cosmo_Conversions
 from hera_cal import redcal
 from collections import OrderedDict as odict
 from pyuvdata import utils as uvutils
 from pyuvdata import UVData
 from datetime import datetime
 
+from .conversions import Cosmo_Conversions
+
+
 def cov(d1, w1, d2=None, w2=None, conj_1=False, conj_2=True):
     """
     Computes an empirical covariance matrix from data vectors. If d1 is of size

hera_pspec/uvpspec.py

@@ -1,15 +1,14 @@
 import numpy as np
 from collections import OrderedDict as odict
 import os, copy, shutil, operator, ast, fnmatch
-from hera_pspec import conversions, noise, version, pspecbeam, grouping, utils
-from hera_pspec import uvpspec_utils as uvputils
-from hera_pspec.parameter import PSpecParam
 from pyuvdata import uvutils as uvutils
 import h5py
 import operator
 import warnings
 import json
 
+from . import conversions, noise, version, pspecbeam, grouping, utils, uvpspec_utils as uvputils
+from .parameter import PSpecParam
 
 class UVPSpec(object):
     """

hera_pspec/uvpspec_utils.py

@@ -1,10 +1,11 @@
 import numpy as np
 import copy, operator
-from . import utils
 from collections import OrderedDict as odict
 from pyuvdata.utils import polstr2num, polnum2str
 import json
 
+from . import utils
+
 def subtract_uvp(uvp1, uvp2, run_check=True, verbose=False):
     """
     Subtract uvp2.data_array from uvp1.data_array. Subtract matching