test_uvdata.py
# -*- mode: python; coding: utf-8 -*-
# Copyright (c) 2018 Radio Astronomy Software Group
# Licensed under the 2-clause BSD License
"""Tests for uvdata object."""
from __future__ import absolute_import, division, print_function
import pytest
import os
import copy
import itertools
import numpy as np
from astropy.time import Time
from astropy.coordinates import Angle
from astropy.utils import iers
from pyuvdata import UVData, UVCal
import pyuvdata.utils as uvutils
import pyuvdata.tests as uvtest
from pyuvdata.data import DATA_PATH
from collections import Counter
@pytest.fixture(scope='function')
def uvdata_props():
required_parameters = ['_data_array', '_nsample_array',
'_flag_array', '_Ntimes', '_Nbls',
'_Nblts', '_Nfreqs', '_Npols', '_Nspws',
'_uvw_array', '_time_array', '_ant_1_array',
'_ant_2_array', '_lst_array',
'_baseline_array', '_freq_array',
'_polarization_array', '_spw_array',
'_integration_time', '_channel_width',
'_object_name', '_telescope_name',
'_instrument', '_telescope_location',
'_history', '_vis_units', '_Nants_data',
'_Nants_telescope', '_antenna_names',
'_antenna_numbers', '_antenna_positions',
'_phase_type']
required_properties = ['data_array', 'nsample_array',
'flag_array', 'Ntimes', 'Nbls',
'Nblts', 'Nfreqs', 'Npols', 'Nspws',
'uvw_array', 'time_array', 'ant_1_array',
'ant_2_array', 'lst_array',
'baseline_array', 'freq_array',
'polarization_array', 'spw_array',
'integration_time', 'channel_width',
'object_name', 'telescope_name',
'instrument', 'telescope_location',
'history', 'vis_units', 'Nants_data',
'Nants_telescope', 'antenna_names',
'antenna_numbers', 'antenna_positions',
'phase_type']
extra_parameters = ['_extra_keywords',
'_x_orientation', '_antenna_diameters',
'_blt_order',
'_gst0', '_rdate', '_earth_omega', '_dut1',
'_timesys', '_uvplane_reference_time',
'_phase_center_ra', '_phase_center_dec',
'_phase_center_epoch', '_phase_center_frame',
'_eq_coeffs', '_eq_coeffs_convention']
extra_properties = ['extra_keywords', 'x_orientation', 'antenna_diameters',
'blt_order', 'gst0',
'rdate', 'earth_omega', 'dut1', 'timesys',
'uvplane_reference_time',
'phase_center_ra', 'phase_center_dec',
'phase_center_epoch', 'phase_center_frame',
'eq_coeffs', 'eq_coeffs_convention']
other_properties = ['telescope_location_lat_lon_alt',
'telescope_location_lat_lon_alt_degrees',
'phase_center_ra_degrees', 'phase_center_dec_degrees',
'pyuvdata_version_str']
uv_object = UVData()
class DataHolder():
def __init__(self, uv_object, required_parameters, required_properties,
extra_parameters, extra_properties, other_properties):
self.uv_object = uv_object
self.required_parameters = required_parameters
self.required_properties = required_properties
self.extra_parameters = extra_parameters
self.extra_properties = extra_properties
self.other_properties = other_properties
uvdata_props = DataHolder(uv_object, required_parameters, required_properties,
extra_parameters, extra_properties, other_properties)
# yields the data we need but will continue to the del call after tests
yield uvdata_props
# some post-test object cleanup
del(uvdata_props)
return
@pytest.fixture(scope="function")
def resample_in_time_file():
# read in test file for the resampling in time functions
uv_object = UVData()
testfile = os.path.join(DATA_PATH, "zen.2458661.23480.HH.uvh5")
uv_object.read(testfile)
yield uv_object
# cleanup
del uv_object
return
@pytest.fixture(scope="function")
def bda_test_file():
# read in test file for BDA-like data
uv_object = UVData()
testfile = os.path.join(DATA_PATH, "simulated_bda_file.uvh5")
uv_object.read(testfile)
yield uv_object
# cleanup
del uv_object
return
@pytest.fixture(scope='function')
def uvdata_data():
uv_object = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uvtest.checkWarnings(uv_object.read_uvfits, [testfile],
message='Telescope EVLA is not')
class DataHolder():
def __init__(self, uv_object):
self.uv_object = uv_object
self.uv_object2 = copy.deepcopy(uv_object)
uvdata_data = DataHolder(uv_object)
# yields the data we need but will continue to the del call after tests
yield uvdata_data
# some post-test object cleanup
del(uvdata_data)
return
@pytest.fixture(scope='function')
def uvdata_baseline():
uv_object = UVData()
uv_object.Nants_telescope = 128
uv_object2 = UVData()
uv_object2.Nants_telescope = 2049
class DataHolder():
def __init__(self, uv_object, uv_object2):
self.uv_object = uv_object
self.uv_object2 = uv_object2
uvdata_baseline = DataHolder(uv_object, uv_object2)
# yields the data we need but will continue to the del call after tests
yield uvdata_baseline
# Post test clean-up
del(uvdata_baseline)
return
@pytest.fixture
def uv1_2_set_uvws():
testfile = os.path.join(DATA_PATH, 'zen.2458661.23480.HH.uvh5')
uv1 = UVData()
uv1.read_uvh5(testfile)
# uvws in the file are wrong. reset them.
uv1.set_uvws_from_antenna_positions()
uv2 = uv1.copy()
yield uv1, uv2
del uv1, uv2
return
@pytest.fixture()
def uv_phase_time_split(uv1_2_set_uvws):
uv_phase, uv_raw = uv1_2_set_uvws
uv_phase.reorder_blts(order="time", minor_order="baseline")
uv_raw.reorder_blts(order="time", minor_order="baseline")
uv_phase.phase(ra=0, dec=0, epoch="J2000", use_ant_pos=True)
times = np.unique(uv_phase.time_array)
time_set_1, time_set_2 = times[::2], times[1::2]
uv_phase_1 = uv_phase.select(times=time_set_1, inplace=False)
uv_phase_2 = uv_phase.select(times=time_set_2, inplace=False)
uv_raw_1 = uv_raw.select(times=time_set_1, inplace=False)
uv_raw_2 = uv_raw.select(times=time_set_2, inplace=False)
yield uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
del uv_phase_1, uv_phase_2, uv_raw_1, uv_raw_2, uv_phase, uv_raw
def test_parameter_iter(uvdata_props):
"""Test expected parameters."""
all = []
for prop in uvdata_props.uv_object:
all.append(prop)
for a in uvdata_props.required_parameters + uvdata_props.extra_parameters:
assert a in all, 'expected attribute ' + a + ' not returned in object iterator'
def test_required_parameter_iter(uvdata_props):
"""Test expected required parameters."""
# at first it's a metadata_only object, so need to modify required_parameters
required = []
for prop in uvdata_props.uv_object.required():
required.append(prop)
expected_required = copy.copy(uvdata_props.required_parameters)
expected_required.remove('_data_array')
expected_required.remove('_nsample_array')
expected_required.remove('_flag_array')
for a in expected_required:
assert a in required, 'expected attribute ' + a + ' not returned in required iterator'
uvdata_props.uv_object.data_array = 1
uvdata_props.uv_object.nsample_array = 1
uvdata_props.uv_object.flag_array = 1
required = []
for prop in uvdata_props.uv_object.required():
required.append(prop)
for a in uvdata_props.required_parameters:
assert a in required, 'expected attribute ' + a + ' not returned in required iterator'
def test_extra_parameter_iter(uvdata_props):
"""Test expected optional parameters."""
extra = []
for prop in uvdata_props.uv_object.extra():
extra.append(prop)
for a in uvdata_props.extra_parameters:
assert a in extra, 'expected attribute ' + a + ' not returned in extra iterator'
def test_unexpected_parameters(uvdata_props):
"""Test for extra parameters."""
expected_parameters = uvdata_props.required_parameters + uvdata_props.extra_parameters
attributes = [i for i in uvdata_props.uv_object.__dict__.keys() if i[0] == '_']
for a in attributes:
assert a in expected_parameters, 'unexpected parameter ' + a + ' found in UVData'
def test_unexpected_attributes(uvdata_props):
"""Test for extra attributes."""
expected_attributes = uvdata_props.required_properties + \
uvdata_props.extra_properties + uvdata_props.other_properties
attributes = [i for i in uvdata_props.uv_object.__dict__.keys() if i[0] != '_']
for a in attributes:
assert a in expected_attributes, 'unexpected attribute ' + a + ' found in UVData'
def test_properties(uvdata_props):
"""Test that properties can be get and set properly."""
prop_dict = dict(list(zip(uvdata_props.required_properties + uvdata_props.extra_properties,
uvdata_props.required_parameters + uvdata_props.extra_parameters)))
for k, v in prop_dict.items():
rand_num = np.random.rand()
setattr(uvdata_props.uv_object, k, rand_num)
this_param = getattr(uvdata_props.uv_object, v)
try:
assert rand_num == this_param.value
except AssertionError:
print('setting {prop_name} to a random number failed'.format(prop_name=k))
raise
def test_metadata_only_property(uvdata_data):
uvdata_data.uv_object.data_array = None
assert uvdata_data.uv_object.metadata_only is False
pytest.raises(ValueError, uvdata_data.uv_object.check)
uvdata_data.uv_object.flag_array = None
assert uvdata_data.uv_object.metadata_only is False
pytest.raises(ValueError, uvdata_data.uv_object.check)
uvdata_data.uv_object.nsample_array = None
assert uvdata_data.uv_object.metadata_only is True
def test_equality(uvdata_data):
"""Basic equality test."""
assert uvdata_data.uv_object == uvdata_data.uv_object
@pytest.mark.filterwarnings("ignore:Telescope location derived from obs")
def test_check(uvdata_data):
"""Test simple check function."""
assert uvdata_data.uv_object.check()
# Check variety of special cases
uvdata_data.uv_object.Nants_data += 1
pytest.raises(ValueError, uvdata_data.uv_object.check)
uvdata_data.uv_object.Nants_data -= 1
uvdata_data.uv_object.Nbls += 1
pytest.raises(ValueError, uvdata_data.uv_object.check)
uvdata_data.uv_object.Nbls -= 1
uvdata_data.uv_object.Ntimes += 1
pytest.raises(ValueError, uvdata_data.uv_object.check)
uvdata_data.uv_object.Ntimes -= 1
# Check case where all data is autocorrelations
# Currently only test files that have autos are fhd files
testdir = os.path.join(DATA_PATH, 'fhd_vis_data/')
file_list = [testdir + '1061316296_flags.sav',
testdir + '1061316296_vis_XX.sav',
testdir + '1061316296_params.sav',
testdir + '1061316296_layout.sav',
testdir + '1061316296_settings.txt']
uvdata_data.uv_object.read_fhd(file_list)
uvdata_data.uv_object.select(blt_inds=np.where(uvdata_data.uv_object.ant_1_array
== uvdata_data.uv_object.ant_2_array)[0])
assert uvdata_data.uv_object.check()
# test auto and cross corr uvw_array
uvd = UVData()
uvd.read_miriad(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcA"))
autos = np.isclose(uvd.ant_1_array - uvd.ant_2_array, 0.0)
auto_inds = np.where(autos)[0]
cross_inds = np.where(~autos)[0]
# make auto have non-zero uvw coords, assert ValueError
uvd.uvw_array[auto_inds[0], 0] = 0.1
pytest.raises(ValueError, uvd.check)
# make cross have |uvw| zero, assert ValueError
uvd.read_miriad(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcA"))
uvd.uvw_array[cross_inds[0]][:] = 0.0
pytest.raises(ValueError, uvd.check)
def test_nants_data_telescope_larger(uvdata_data):
# make sure it's okay for Nants_telescope to be strictly greater than Nants_data
uvdata_data.uv_object.Nants_telescope += 1
# add dummy information for "new antenna" to pass object check
uvdata_data.uv_object.antenna_names = np.concatenate(
(uvdata_data.uv_object.antenna_names, ["dummy_ant"]))
uvdata_data.uv_object.antenna_numbers = np.concatenate(
(uvdata_data.uv_object.antenna_numbers, [20]))
uvdata_data.uv_object.antenna_positions = np.concatenate(
(uvdata_data.uv_object.antenna_positions, np.zeros((1, 3))), axis=0)
assert uvdata_data.uv_object.check()
def test_ant1_array_not_in_antnums(uvdata_data):
# make sure an error is raised if antennas in ant_1_array not in antenna_numbers
# remove antennas from antenna_names & antenna_numbers by hand
uvdata_data.uv_object.antenna_names = uvdata_data.uv_object.antenna_names[1:]
uvdata_data.uv_object.antenna_numbers = uvdata_data.uv_object.antenna_numbers[1:]
uvdata_data.uv_object.antenna_positions = uvdata_data.uv_object.antenna_positions[1:, :]
uvdata_data.uv_object.Nants_telescope = uvdata_data.uv_object.antenna_numbers.size
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object.check()
assert str(cm.value).startswith('All antennas in ant_1_array must be in antenna_numbers')
def test_ant2_array_not_in_antnums(uvdata_data):
# make sure an error is raised if antennas in ant_2_array not in antenna_numbers
# remove antennas from antenna_names & antenna_numbers by hand
uvdata_data.uv_object.antenna_names = uvdata_data.uv_object.antenna_names[:-1]
uvdata_data.uv_object.antenna_numbers = uvdata_data.uv_object.antenna_numbers[:-1]
uvdata_data.uv_object.antenna_positions = uvdata_data.uv_object.antenna_positions[:-1, :]
uvdata_data.uv_object.Nants_telescope = uvdata_data.uv_object.antenna_numbers.size
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object.check()
assert str(cm.value).startswith('All antennas in ant_2_array must be in antenna_numbers')
def test_converttofiletype(uvdata_data):
fhd_obj = uvdata_data.uv_object._convert_to_filetype('fhd')
uvdata_data.uv_object._convert_from_filetype(fhd_obj)
assert uvdata_data.uv_object == uvdata_data.uv_object2
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object._convert_to_filetype('foo')
assert str(cm.value).startswith("filetype must be uvfits, miriad, fhd, or uvh5")
def test_baseline_to_antnums(uvdata_baseline):
"""Test baseline to antnum conversion for 256 & larger conventions."""
assert uvdata_baseline.uv_object.baseline_to_antnums(67585) == (0, 0)
with pytest.raises(Exception) as cm:
uvdata_baseline.uv_object2.baseline_to_antnums(67585)
assert str(cm.value).startswith('error Nants={Nants}>2048'
' not supported'.format(Nants=uvdata_baseline.uv_object2.Nants_telescope))
ant_pairs = [(10, 20), (280, 310)]
for pair in ant_pairs:
if np.max(np.array(pair)) < 255:
bl = uvdata_baseline.uv_object.antnums_to_baseline(
pair[0], pair[1], attempt256=True)
ant_pair_out = uvdata_baseline.uv_object.baseline_to_antnums(bl)
assert pair == ant_pair_out
bl = uvdata_baseline.uv_object.antnums_to_baseline(
pair[0], pair[1], attempt256=False)
ant_pair_out = uvdata_baseline.uv_object.baseline_to_antnums(bl)
assert pair == ant_pair_out
def test_baseline_to_antnums_vectorized(uvdata_baseline):
"""Test vectorized antnum to baseline conversion."""
ant_1 = [10, 280]
ant_2 = [20, 310]
baseline_array = uvdata_baseline.uv_object.antnums_to_baseline(ant_1, ant_2)
assert np.array_equal(baseline_array, [88085, 641335])
ant_1_out, ant_2_out = uvdata_baseline.uv_object.baseline_to_antnums(baseline_array.tolist())
assert np.array_equal(ant_1, ant_1_out)
assert np.array_equal(ant_2, ant_2_out)
def test_antnums_to_baselines(uvdata_baseline):
"""Test antums to baseline conversion for 256 & larger conventions."""
assert uvdata_baseline.uv_object.antnums_to_baseline(0, 0) == 67585
assert uvdata_baseline.uv_object.antnums_to_baseline(257, 256) == 594177
assert uvdata_baseline.uv_object.baseline_to_antnums(594177) == (257, 256)
# Check attempt256
assert uvdata_baseline.uv_object.antnums_to_baseline(0, 0, attempt256=True) == 257
assert uvdata_baseline.uv_object.antnums_to_baseline(257, 256) == 594177
uvtest.checkWarnings(uvdata_baseline.uv_object.antnums_to_baseline, [257, 256],
{'attempt256': True}, message='found > 256 antennas')
pytest.raises(Exception, uvdata_baseline.uv_object2.antnums_to_baseline, 0, 0)
# check a len-1 array returns as an array
ant1 = np.array([1])
ant2 = np.array([2])
assert isinstance(uvdata_baseline.uv_object.antnums_to_baseline(ant1, ant2), np.ndarray)
def test_known_telescopes():
"""Test known_telescopes method returns expected results."""
uv_object = UVData()
known_telescopes = ['PAPER', 'HERA', 'MWA']
# calling np.sort().tolist() because [].sort() acts inplace and returns None
# Before test had None == None
assert np.sort(known_telescopes).tolist() == np.sort(uv_object.known_telescopes()).tolist()
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_HERA_diameters():
miriad_file = os.path.join(DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv_in = UVData()
uv_in.read_miriad(miriad_file)
uv_in.telescope_name = 'HERA'
uvtest.checkWarnings(uv_in.set_telescope_params, message='antenna_diameters '
'is not set. Using known values for HERA.')
assert uv_in.telescope_name == 'HERA'
assert uv_in.antenna_diameters is not None
uv_in.check()
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_generic_read():
uv_in = UVData()
uvfits_file = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_in.read(uvfits_file, read_data=False)
unique_times = np.unique(uv_in.time_array)
pytest.raises(ValueError, uv_in.read, uvfits_file, times=unique_times[0:2],
time_range=[unique_times[0], unique_times[1]])
pytest.raises(ValueError, uv_in.read, uvfits_file,
antenna_nums=uv_in.antenna_numbers[0],
antenna_names=uv_in.antenna_names[1])
pytest.raises(ValueError, uv_in.read, 'foo')
@pytest.mark.parametrize(
"phase_kwargs",
[
{"ra": 0., "dec": 0., "epoch": "J2000"},
{"ra": Angle('5d').rad, "dec": Angle('30d').rad, "phase_frame": "gcrs"},
{"ra": Angle('180d').rad, "dec": Angle('90d'),
"epoch": Time('2010-01-01T00:00:00', format='isot', scale='utc')
},
]
)
def test_phase_unphaseHERA(uv1_2_set_uvws, phase_kwargs):
"""
Read in drift data, phase to an RA/DEC, unphase and check for object equality.
"""
uv1, UV_raw = uv1_2_set_uvws
uv1.phase(**phase_kwargs)
uv1.unphase_to_drift()
# check that phase + unphase gets back to raw
assert UV_raw == uv1
def test_phase_unphaseHERA_one_bl(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check that phase + unphase work with one baseline
UV_raw_small = UV_raw.select(blt_inds=[0], inplace=False)
UV_phase_small = copy.deepcopy(UV_raw_small)
UV_phase_small.phase(Angle('23h').rad, Angle('15d').rad)
UV_phase_small.unphase_to_drift()
assert UV_raw_small == UV_phase_small
def test_phase_unphaseHERA_antpos(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check that they match if you phase & unphase using antenna locations
# first replace the uvws with the right values
antenna_enu = uvutils.ENU_from_ECEF((UV_raw.antenna_positions + UV_raw.telescope_location),
*UV_raw.telescope_location_lat_lon_alt)
uvw_calc = np.zeros_like(UV_raw.uvw_array)
unique_times, unique_inds = np.unique(UV_raw.time_array, return_index=True)
for ind, jd in enumerate(unique_times):
inds = np.where(UV_raw.time_array == jd)[0]
for bl_ind in inds:
ant1_index = np.where(UV_raw.antenna_numbers == UV_raw.ant_1_array[bl_ind])[0][0]
ant2_index = np.where(UV_raw.antenna_numbers == UV_raw.ant_2_array[bl_ind])[0][0]
uvw_calc[bl_ind, :] = antenna_enu[ant2_index, :] - antenna_enu[ant1_index, :]
UV_raw_new = copy.deepcopy(UV_raw)
UV_raw_new.uvw_array = uvw_calc
UV_phase.phase(0., 0., epoch="J2000", use_ant_pos=True)
UV_phase2 = copy.deepcopy(UV_raw_new)
UV_phase2.phase(0., 0., epoch="J2000")
# The uvw's only agree to ~1mm. should they be better?
assert np.allclose(UV_phase2.uvw_array, UV_phase.uvw_array, atol=1e-3)
# the data array are just multiplied by the w's for phasing, so a difference
# at the 1e-3 level makes the data array different at that level too.
# -> change the tolerance on data_array for this test
UV_phase2._data_array.tols = (0, 1e-3 * np.amax(np.abs(UV_phase2.data_array)))
assert UV_phase2 == UV_phase
# check that phase + unphase gets back to raw using antpos
UV_phase.unphase_to_drift(use_ant_pos=True)
assert UV_raw_new == UV_phase
def test_phase_unphaseHERA_zenith_timestamp(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check that phasing to zenith with one timestamp has small changes
# (it won't be identical because of precession/nutation changing the coordinate axes)
# use gcrs rather than icrs to reduce differences (don't include abberation)
UV_raw_small = UV_raw.select(times=UV_raw.time_array[0], inplace=False)
UV_phase_simple_small = copy.deepcopy(UV_raw_small)
UV_phase_simple_small.phase_to_time(time=Time(UV_raw.time_array[0], format='jd'),
phase_frame='gcrs')
# it's unclear to me how close this should be...
assert np.allclose(UV_phase_simple_small.uvw_array, UV_raw_small.uvw_array, atol=1e-1)
def test_phase_to_time_jd_input(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
UV_phase.phase_to_time(UV_raw.time_array[0])
UV_phase.unphase_to_drift()
assert UV_phase == UV_raw
def test_phase_to_time_error(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check error if not passing a Time object to phase_to_time
with pytest.raises(TypeError) as cm:
UV_phase.phase_to_time('foo')
assert str(cm.value).startswith("time must be an astropy.time.Time object")
def test_unphase_drift_data_error(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check error if not passing a Time object to phase_to_time
with pytest.raises(ValueError) as cm:
UV_phase.unphase_to_drift()
assert str(cm.value).startswith("The data is already drift scanning;")
@pytest.mark.parametrize(
"phase_func,phase_kwargs,err_msg",
[("unphase_to_drift", {},
"The phasing type of the data is unknown. Set the phase_type"),
("phase", {"ra": 0, "dec": 0, "epoch": "J2000", "allow_rephase": False},
"The phasing type of the data is unknown. Set the phase_type"),
("phase_to_time", {"time": 0, "allow_rephase": False},
"The phasing type of the data is unknown. Set the phase_type")
]
)
def test_unknown_phase_unphaseHERA_errors(
uv1_2_set_uvws, phase_func, phase_kwargs, err_msg
):
UV_phase, UV_raw = uv1_2_set_uvws
# Set phase type to unkown on some tests, ignore on others.
UV_phase.set_unknown_phase_type()
# if this is phase_to_time, use this index set in the dictionary and
# assign the value of the time_array associated with that index
# this is a little hacky, but we cannot acces UV_phase.time_array in the
# parametrize
if phase_func == "phase_to_time":
phase_kwargs["time"] = UV_phase.time_array[phase_kwargs["time"]]
with pytest.raises(ValueError) as cm:
getattr(UV_phase, phase_func)(**phase_kwargs)
assert str(cm.value).startswith(err_msg)
@pytest.mark.parametrize(
"phase_func,phase_kwargs,err_msg",
[("phase", {"ra": 0, "dec": 0, "epoch": "J2000", "allow_rephase": False},
"The data is already phased;"),
("phase_to_time", {"time": 0, "allow_rephase": False},
"The data is already phased;")
]
)
def test_phase_rephaseHERA_errors(
uv1_2_set_uvws, phase_func, phase_kwargs, err_msg
):
UV_phase, UV_raw = uv1_2_set_uvws
# Set phase type to unkown on some tests, ignore on others.
UV_phase.phase(0., 0., epoch="J2000")
# if this is phase_to_time, use this index set in the dictionary and
# assign the value of the time_array associated with that index
# this is a little hacky, but we cannot acces UV_phase.time_array in the
# parametrize
if phase_func == "phase_to_time":
phase_kwargs["time"] = UV_phase.time_array[phase_kwargs["time"]]
with pytest.raises(ValueError) as cm:
getattr(UV_phase, phase_func)(**phase_kwargs)
assert str(cm.value).startswith(err_msg)
def test_phase_unphaseHERA_bad_frame(uv1_2_set_uvws):
UV_phase, UV_raw = uv1_2_set_uvws
# check errors when trying to phase to an unsupported frame
with pytest.raises(ValueError) as cm:
UV_phase.phase(0., 0., epoch="J2000", phase_frame='cirs')
assert str(cm.value).startswith("phase_frame can only be set to icrs or gcrs.")
def test_phasing():
"""Use MWA files phased to 2 different places to test phasing."""
file1 = os.path.join(DATA_PATH, '1133866760.uvfits')
file2 = os.path.join(DATA_PATH, '1133866760_rephase.uvfits')
uvd1 = UVData()
uvd2 = UVData()
uvd1.read_uvfits(file1)
uvd2.read_uvfits(file2)
uvd1_drift = copy.deepcopy(uvd1)
uvd1_drift.unphase_to_drift(phase_frame='gcrs')
uvd1_drift_antpos = copy.deepcopy(uvd1)
uvd1_drift_antpos.unphase_to_drift(phase_frame='gcrs', use_ant_pos=True)
uvd2_drift = copy.deepcopy(uvd2)
uvd2_drift.unphase_to_drift(phase_frame='gcrs')
uvd2_drift_antpos = copy.deepcopy(uvd2)
uvd2_drift_antpos.unphase_to_drift(phase_frame='gcrs', use_ant_pos=True)
# the tolerances here are empirical -- based on what was seen in the
# external phasing test. See the phasing memo in docs/references for
# details.
assert np.allclose(uvd1_drift.uvw_array, uvd2_drift.uvw_array, atol=2e-2)
assert np.allclose(uvd1_drift_antpos.uvw_array, uvd2_drift_antpos.uvw_array)
uvd2_rephase = uvd2.copy()
uvd2_rephase.phase(uvd1.phase_center_ra,
uvd1.phase_center_dec,
uvd1.phase_center_epoch,
orig_phase_frame='gcrs',
phase_frame='gcrs')
uvd2_rephase_antpos = uvd2.copy()
uvd2_rephase_antpos.phase(uvd1.phase_center_ra,
uvd1.phase_center_dec,
uvd1.phase_center_epoch,
orig_phase_frame='gcrs',
phase_frame='gcrs',
use_ant_pos=True)
# the tolerances here are empirical -- based on what was seen in the
# external phasing test. See the phasing memo in docs/references for
# details.
assert np.allclose(uvd1.uvw_array, uvd2_rephase.uvw_array, atol=2e-2)
assert np.allclose(uvd1.uvw_array, uvd2_rephase_antpos.uvw_array, atol=5e-3)
# rephase the drift objects to the original pointing and verify that they
# match
uvd1_drift.phase(uvd1.phase_center_ra, uvd1.phase_center_dec,
uvd1.phase_center_epoch, phase_frame='gcrs')
uvd1_drift_antpos.phase(uvd1.phase_center_ra, uvd1.phase_center_dec,
uvd1.phase_center_epoch, phase_frame='gcrs',
use_ant_pos=True)
# the tolerances here are empirical -- caused by one unphase/phase cycle.
# the antpos-based phasing differences are based on what was seen in the
# external phasing test. See the phasing memo in docs/references for
# details.
assert np.allclose(uvd1.uvw_array, uvd1_drift.uvw_array, atol=1e-4)
assert np.allclose(uvd1.uvw_array, uvd1_drift_antpos.uvw_array, atol=5e-3)
uvd2_drift.phase(uvd2.phase_center_ra, uvd2.phase_center_dec,
uvd2.phase_center_epoch, phase_frame='gcrs')
uvd2_drift_antpos.phase(uvd2.phase_center_ra, uvd2.phase_center_dec,
uvd2.phase_center_epoch, phase_frame='gcrs',
use_ant_pos=True)
# the tolerances here are empirical -- caused by one unphase/phase cycle.
# the antpos-based phasing differences are based on what was seen in the
# external phasing test. See the phasing memo in docs/references for
# details.
assert np.allclose(uvd2.uvw_array, uvd2_drift.uvw_array, atol=1e-4)
assert np.allclose(uvd2.uvw_array, uvd2_drift_antpos.uvw_array, atol=2e-2)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_set_phase_unknown():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
uv_object.set_unknown_phase_type()
assert uv_object.phase_type == 'unknown'
assert not uv_object._phase_center_epoch.required
assert not uv_object._phase_center_ra.required
assert not uv_object._phase_center_dec.required
assert uv_object.check()
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_select_blts():
uv_object = UVData()
testfile = os.path.join(DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv_object.read_miriad(testfile)
old_history = uv_object.history
blt_inds = np.array([172, 182, 132, 227, 144, 44, 16, 104, 385, 134, 326, 140, 116,
218, 178, 391, 111, 276, 274, 308, 38, 64, 317, 76, 239, 246,
34, 39, 83, 184, 208, 60, 374, 295, 118, 337, 261, 21, 375,
396, 355, 187, 95, 122, 186, 113, 260, 264, 156, 13, 228, 291,
302, 72, 137, 216, 299, 341, 207, 256, 223, 250, 268, 147, 73,
32, 142, 383, 221, 203, 258, 286, 324, 265, 170, 236, 8, 275,
304, 117, 29, 167, 15, 388, 171, 82, 322, 248, 160, 85, 66,
46, 272, 328, 323, 152, 200, 119, 359, 23, 363, 56, 219, 257,
11, 307, 336, 289, 136, 98, 37, 163, 158, 80, 125, 40, 298,
75, 320, 74, 57, 346, 121, 129, 332, 238, 93, 18, 330, 339,
381, 234, 176, 22, 379, 199, 266, 100, 90, 292, 205, 58, 222,
350, 109, 273, 191, 368, 88, 101, 65, 155, 2, 296, 306, 398,
369, 378, 254, 67, 249, 102, 348, 392, 20, 28, 169, 262, 269,
287, 86, 300, 143, 177, 42, 290, 284, 123, 189, 175, 97, 340,
242, 342, 331, 282, 235, 344, 63, 115, 78, 30, 226, 157, 133,
71, 35, 212, 333])
selected_data = uv_object.data_array[np.sort(blt_inds), :, :, :]
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(blt_inds=blt_inds)
assert len(blt_inds) == uv_object2.Nblts
# verify that histories are different
assert not uvutils._check_histories(old_history, uv_object2.history)
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baseline-times using pyuvdata.',
uv_object2.history)
assert np.all(selected_data == uv_object2.data_array)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(blt_inds=blt_inds[np.newaxis, :])
assert len(blt_inds) == uv_object2.Nblts
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baseline-times using pyuvdata.',
uv_object2.history)
assert np.all(selected_data == uv_object2.data_array)
# check that just doing the metadata works properly
uv_object3 = copy.deepcopy(uv_object)
uv_object3.data_array = None
uv_object3.flag_array = None
uv_object3.nsample_array = None
assert uv_object3.metadata_only is True
uv_object4 = uv_object3.select(blt_inds=blt_inds, inplace=False)
for param in uv_object4:
param_name = getattr(uv_object4, param).name
if param_name not in ['data_array', 'flag_array', 'nsample_array']:
assert getattr(uv_object4, param) == getattr(uv_object2, param)
else:
assert getattr(uv_object4, param_name) is None
# also check with inplace=True
uv_object3.select(blt_inds=blt_inds)
assert uv_object3 == uv_object4
# check for warnings & errors with the metadata_only keyword
uv_object3 = copy.deepcopy(uv_object)
with pytest.raises(ValueError) as cm:
uvtest.checkWarnings(uv_object3.select,
func_kwargs={'blt_inds': blt_inds, 'metadata_only': True},
message='The metadata_only option has been replaced',
category=DeprecationWarning)
assert str(cm.value).startswith('The metadata_only option can only be True')
# check for errors associated with out of bounds indices
pytest.raises(ValueError, uv_object.select, blt_inds=np.arange(-10, -5))
pytest.raises(ValueError, uv_object.select,
blt_inds=np.arange(uv_object.Nblts + 1, uv_object.Nblts + 10))
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_antennas():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
unique_ants = np.unique(
uv_object.ant_1_array.tolist() + uv_object.ant_2_array.tolist())
ants_to_keep = np.array([0, 19, 11, 24, 3, 23, 1, 20, 21])
blts_select = [(a1 in ants_to_keep) & (a2 in ants_to_keep) for (a1, a2) in
zip(uv_object.ant_1_array, uv_object.ant_2_array)]
Nblts_selected = np.sum(blts_select)
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(antenna_nums=ants_to_keep)
assert len(ants_to_keep) == uv_object2.Nants_data
assert Nblts_selected == uv_object2.Nblts
for ant in ants_to_keep:
assert ant in uv_object2.ant_1_array or ant in uv_object2.ant_2_array
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in ants_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific antennas using pyuvdata.',
uv_object2.history)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(antenna_nums=ants_to_keep[np.newaxis, :])
assert len(ants_to_keep) == uv_object2.Nants_data
assert Nblts_selected == uv_object2.Nblts
for ant in ants_to_keep:
assert ant in uv_object2.ant_1_array or ant in uv_object2.ant_2_array
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in ants_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific antennas using pyuvdata.',
uv_object2.history)
# now test using antenna_names to specify antennas to keep
uv_object3 = copy.deepcopy(uv_object)
ants_to_keep = np.array(sorted(list(ants_to_keep)))
ant_names = []
for a in ants_to_keep:
ind = np.where(uv_object3.antenna_numbers == a)[0][0]
ant_names.append(uv_object3.antenna_names[ind])
uv_object3.select(antenna_names=ant_names)
assert uv_object2 == uv_object3
# check that it also works with higher dimension array
uv_object3 = copy.deepcopy(uv_object)
ants_to_keep = np.array(sorted(list(ants_to_keep)))
ant_names = []
for a in ants_to_keep:
ind = np.where(uv_object3.antenna_numbers == a)[0][0]
ant_names.append(uv_object3.antenna_names[ind])
uv_object3.select(antenna_names=[ant_names])
assert uv_object2 == uv_object3
# test removing metadata associated with antennas that are no longer present
# also add (different) antenna_diameters to test downselection
uv_object.antenna_diameters = 1. * np.ones((uv_object.Nants_telescope,), dtype=np.float)
for i in range(uv_object.Nants_telescope):
uv_object.antenna_diameters += i
uv_object4 = copy.deepcopy(uv_object)
uv_object4.select(antenna_nums=ants_to_keep, keep_all_metadata=False)
assert uv_object4.Nants_telescope == 9
assert set(uv_object4.antenna_numbers) == set(ants_to_keep)
for a in ants_to_keep:
idx1 = uv_object.antenna_numbers.tolist().index(a)
idx2 = uv_object4.antenna_numbers.tolist().index(a)
assert uv_object.antenna_names[idx1] == uv_object4.antenna_names[idx2]
assert np.allclose(uv_object.antenna_positions[idx1, :],
uv_object4.antenna_positions[idx2, :])
assert uv_object.antenna_diameters[idx1], uv_object4.antenna_diameters[idx2]
# remove antenna_diameters from object
uv_object.antenna_diameters = None
# check for errors associated with antennas not included in data, bad names or providing numbers and names
pytest.raises(ValueError, uv_object.select,
antenna_nums=np.max(unique_ants) + np.arange(1, 3))
pytest.raises(ValueError, uv_object.select, antenna_names='test1')
pytest.raises(ValueError, uv_object.select,
antenna_nums=ants_to_keep, antenna_names=ant_names)
def sort_bl(p):
"""Sort a tuple that starts with a pair of antennas, and may have stuff after."""
if p[1] >= p[0]:
return p
return (p[1], p[0]) + p[2:]
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_bls():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
first_ants = [6, 2, 7, 2, 21, 27, 8]
second_ants = [0, 20, 8, 1, 2, 3, 22]
new_unique_ants = np.unique(first_ants + second_ants)
ant_pairs_to_keep = list(zip(first_ants, second_ants))
sorted_pairs_to_keep = [sort_bl(p) for p in ant_pairs_to_keep]
blts_select = [sort_bl((a1, a2)) in sorted_pairs_to_keep for (a1, a2) in
zip(uv_object.ant_1_array, uv_object.ant_2_array)]
Nblts_selected = np.sum(blts_select)
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(bls=ant_pairs_to_keep)
sorted_pairs_object2 = [sort_bl(p) for p in zip(
uv_object2.ant_1_array, uv_object2.ant_2_array)]
assert len(new_unique_ants) == uv_object2.Nants_data
assert Nblts_selected == uv_object2.Nblts
for ant in new_unique_ants:
assert ant in uv_object2.ant_1_array or ant in uv_object2.ant_2_array
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in new_unique_ants
for pair in sorted_pairs_to_keep:
assert pair in sorted_pairs_object2
for pair in sorted_pairs_object2:
assert pair in sorted_pairs_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baselines using pyuvdata.',
uv_object2.history)
# check select with polarizations
first_ants = [6, 2, 7, 2, 21, 27, 8]
second_ants = [0, 20, 8, 1, 2, 3, 22]
pols = ['RR', 'RR', 'RR', 'RR', 'RR', 'RR', 'RR']
new_unique_ants = np.unique(first_ants + second_ants)
bls_to_keep = list(zip(first_ants, second_ants, pols))
sorted_bls_to_keep = [sort_bl(p) for p in bls_to_keep]
blts_select = [sort_bl((a1, a2, 'RR')) in sorted_bls_to_keep for (a1, a2) in
zip(uv_object.ant_1_array, uv_object.ant_2_array)]
Nblts_selected = np.sum(blts_select)
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(bls=bls_to_keep)
sorted_pairs_object2 = [sort_bl(p) + ('RR',) for p in zip(
uv_object2.ant_1_array, uv_object2.ant_2_array)]
assert len(new_unique_ants) == uv_object2.Nants_data
assert Nblts_selected == uv_object2.Nblts
for ant in new_unique_ants:
assert ant in uv_object2.ant_1_array or ant in uv_object2.ant_2_array
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in new_unique_ants
for bl in sorted_bls_to_keep:
assert bl in sorted_pairs_object2
for bl in sorted_pairs_object2:
assert bl in sorted_bls_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baselines, polarizations using pyuvdata.',
uv_object2.history)
# check that you can use numpy integers with out errors:
first_ants = list(map(np.int32, [6, 2, 7, 2, 21, 27, 8]))
second_ants = list(map(np.int32, [0, 20, 8, 1, 2, 3, 22]))
ant_pairs_to_keep = list(zip(first_ants, second_ants))
uv_object2 = uv_object.select(bls=ant_pairs_to_keep, inplace=False)
sorted_pairs_object2 = [sort_bl(p) for p in zip(
uv_object2.ant_1_array, uv_object2.ant_2_array)]
assert len(new_unique_ants) == uv_object2.Nants_data
assert Nblts_selected == uv_object2.Nblts
for ant in new_unique_ants:
assert ant in uv_object2.ant_1_array or ant in uv_object2.ant_2_array
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in new_unique_ants
for pair in sorted_pairs_to_keep:
assert pair in sorted_pairs_object2
for pair in sorted_pairs_object2:
assert pair in sorted_pairs_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baselines using pyuvdata.',
uv_object2.history)
# check that you can specify a single pair without errors
uv_object2.select(bls=(0, 6))
sorted_pairs_object2 = [sort_bl(p) for p in zip(
uv_object2.ant_1_array, uv_object2.ant_2_array)]
assert list(set(sorted_pairs_object2)) == [(0, 6)]
# check for errors associated with antenna pairs not included in data and bad inputs
with pytest.raises(ValueError) as cm:
uv_object.select(bls=list(zip(first_ants, second_ants)) + [0, 6])
assert str(cm.value).startswith('bls must be a list of tuples of antenna numbers')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=[(uv_object.antenna_names[0], uv_object.antenna_names[1])])
assert str(cm.value).startswith('bls must be a list of tuples of antenna numbers')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=(5, 1))
assert str(cm.value).startswith('Antenna number 5 is not present in the '
'ant_1_array or ant_2_array')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=(0, 5))
assert str(cm.value).startswith('Antenna number 5 is not present in the '
'ant_1_array or ant_2_array')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=(27, 27))
assert str(cm.value).startswith('Antenna pair (27, 27) does not have any data')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=(6, 0, 'RR'), polarizations='RR')
assert str(cm.value).startswith('Cannot provide length-3 tuples and also '
'specify polarizations.')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=(6, 0, 8))
assert str(cm.value).startswith('The third element in each bl must be a '
'polarization string')
with pytest.raises(ValueError) as cm:
uv_object.select(bls=[])
assert str(cm.value).startswith('bls must be a list of tuples of antenna numbers')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_times():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
unique_times = np.unique(uv_object.time_array)
times_to_keep = unique_times[[0, 3, 5, 6, 7, 10, 14]]
Nblts_selected = np.sum([t in times_to_keep for t in uv_object.time_array])
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(times=times_to_keep)
assert len(times_to_keep) == uv_object2.Ntimes
assert Nblts_selected == uv_object2.Nblts
for t in times_to_keep:
assert t in uv_object2.time_array
for t in np.unique(uv_object2.time_array):
assert t in times_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific times using pyuvdata.',
uv_object2.history)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(times=times_to_keep[np.newaxis, :])
assert len(times_to_keep) == uv_object2.Ntimes
assert Nblts_selected == uv_object2.Nblts
for t in times_to_keep:
assert t in uv_object2.time_array
for t in np.unique(uv_object2.time_array):
assert t in times_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific times using pyuvdata.',
uv_object2.history)
# check for errors associated with times not included in data
pytest.raises(ValueError, uv_object.select, times=[np.min(unique_times) - uv_object.integration_time[0]])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_time_range():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
unique_times = np.unique(uv_object.time_array)
mean_time = np.mean(unique_times)
time_range = [np.min(unique_times), mean_time]
times_to_keep = unique_times[np.nonzero((unique_times <= time_range[1])
& (unique_times >= time_range[0]))]
Nblts_selected = np.nonzero((uv_object.time_array <= time_range[1])
& (uv_object.time_array >= time_range[0]))[0].size
uv_object2 = uv_object.copy()
uv_object2.select(time_range=time_range)
assert times_to_keep.size == uv_object2.Ntimes
assert Nblts_selected == uv_object2.Nblts
for t in times_to_keep:
assert t in uv_object2.time_array
for t in np.unique(uv_object2.time_array):
assert t in times_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific times using pyuvdata.',
uv_object2.history)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_time_range_no_data():
"""Check for error associated with times not included in data."""
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read(testfile)
unique_times = np.unique(uv_object.time_array)
with pytest.raises(ValueError) as cm:
uv_object.select(time_range=[np.min(unique_times) - uv_object.integration_time[0] * 2,
np.min(unique_times) - uv_object.integration_time[0]])
assert str(cm.value).startswith('No elements in time range')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_time_and_time_range():
"""Check for error setting times and time_range."""
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read(testfile)
unique_times = np.unique(uv_object.time_array)
mean_time = np.mean(unique_times)
time_range = [np.min(unique_times), mean_time]
times_to_keep = unique_times[[0, 3, 5, 6, 7, 10, 14]]
with pytest.raises(ValueError) as cm:
uv_object.select(time_range=time_range, times=times_to_keep)
assert str(cm.value).startswith('Only one of "times" and "time_range" can be set')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_time_range_one_elem():
"""Check for error if time_range not length 2."""
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read(testfile)
unique_times = np.unique(uv_object.time_array)
mean_time = np.mean(unique_times)
time_range = [np.min(unique_times), mean_time]
with pytest.raises(ValueError) as cm:
uv_object.select(time_range=time_range[0])
assert str(cm.value).startswith('time_range must be length 2')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_frequencies():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
freqs_to_keep = uv_object.freq_array[0, np.arange(12, 22)]
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(frequencies=freqs_to_keep)
assert len(freqs_to_keep) == uv_object2.Nfreqs
for f in freqs_to_keep:
assert f in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in freqs_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata.',
uv_object2.history)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(frequencies=freqs_to_keep[np.newaxis, :])
assert len(freqs_to_keep) == uv_object2.Nfreqs
for f in freqs_to_keep:
assert f in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in freqs_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata.',
uv_object2.history)
# check that selecting one frequency works
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(frequencies=freqs_to_keep[0])
assert 1 == uv_object2.Nfreqs
assert freqs_to_keep[0] in uv_object2.freq_array
for f in uv_object2.freq_array:
assert f in [freqs_to_keep[0]]
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata.',
uv_object2.history)
# check for errors associated with frequencies not included in data
pytest.raises(ValueError, uv_object.select, frequencies=[
np.max(uv_object.freq_array) + uv_object.channel_width])
# check for warnings and errors associated with unevenly spaced or non-contiguous frequencies
uv_object2 = copy.deepcopy(uv_object)
uvtest.checkWarnings(uv_object2.select, [], {'frequencies': uv_object2.freq_array[0, [0, 5, 6]]},
message='Selected frequencies are not evenly spaced')
write_file_uvfits = os.path.join(DATA_PATH, 'test/select_test.uvfits')
write_file_miriad = os.path.join(DATA_PATH, 'test/select_test.uv')
pytest.raises(ValueError, uv_object2.write_uvfits, write_file_uvfits)
pytest.raises(ValueError, uv_object2.write_miriad, write_file_miriad)
uv_object2 = copy.deepcopy(uv_object)
uvtest.checkWarnings(uv_object2.select, [], {'frequencies': uv_object2.freq_array[0, [0, 2, 4]]},
message='Selected frequencies are not contiguous')
pytest.raises(ValueError, uv_object2.write_uvfits, write_file_uvfits)
pytest.raises(ValueError, uv_object2.write_miriad, write_file_miriad)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_freq_chans():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
chans_to_keep = np.arange(12, 22)
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(freq_chans=chans_to_keep)
assert len(chans_to_keep) == uv_object2.Nfreqs
for chan in chans_to_keep:
assert uv_object.freq_array[0, chan] in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in uv_object.freq_array[0, chans_to_keep]
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata.',
uv_object2.history)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(freq_chans=chans_to_keep[np.newaxis, :])
assert len(chans_to_keep) == uv_object2.Nfreqs
for chan in chans_to_keep:
assert uv_object.freq_array[0, chan] in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in uv_object.freq_array[0, chans_to_keep]
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata.',
uv_object2.history)
# Test selecting both channels and frequencies
freqs_to_keep = uv_object.freq_array[0, np.arange(20, 30)] # Overlaps with chans
all_chans_to_keep = np.arange(12, 30)
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(frequencies=freqs_to_keep, freq_chans=chans_to_keep)
assert len(all_chans_to_keep) == uv_object2.Nfreqs
for chan in all_chans_to_keep:
assert uv_object.freq_array[0, chan] in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in uv_object.freq_array[0, all_chans_to_keep]
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_polarizations():
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
pols_to_keep = [-1, -2]
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(polarizations=pols_to_keep)
assert len(pols_to_keep) == uv_object2.Npols
for p in pols_to_keep:
assert p in uv_object2.polarization_array
for p in np.unique(uv_object2.polarization_array):
assert p in pols_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific polarizations using pyuvdata.',
uv_object2.history)
# check that it also works with higher dimension array
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(polarizations=[pols_to_keep])
assert len(pols_to_keep) == uv_object2.Npols
for p in pols_to_keep:
assert p in uv_object2.polarization_array
for p in np.unique(uv_object2.polarization_array):
assert p in pols_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific polarizations using pyuvdata.',
uv_object2.history)
# check for errors associated with polarizations not included in data
pytest.raises(ValueError, uv_object2.select, polarizations=[-3, -4])
# check for warnings and errors associated with unevenly spaced polarizations
uvtest.checkWarnings(uv_object.select, [], {'polarizations': uv_object.polarization_array[[0, 1, 3]]},
message='Selected polarization values are not evenly spaced')
write_file_uvfits = os.path.join(DATA_PATH, 'test/select_test.uvfits')
pytest.raises(ValueError, uv_object.write_uvfits, write_file_uvfits)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select():
# now test selecting along all axes at once
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
blt_inds = np.array([1057, 461, 1090, 354, 528, 654, 882, 775, 369, 906, 748,
875, 296, 773, 554, 395, 1003, 476, 762, 976, 1285, 874,
717, 383, 1281, 924, 264, 1163, 297, 857, 1258, 1000, 180,
1303, 1139, 393, 42, 135, 789, 713, 527, 1218, 576, 100,
1311, 4, 653, 724, 591, 889, 36, 1033, 113, 479, 322,
118, 898, 1263, 477, 96, 935, 238, 195, 531, 124, 198,
992, 1131, 305, 154, 961, 6, 1175, 76, 663, 82, 637,
288, 1152, 845, 1290, 379, 1225, 1240, 733, 1172, 937, 1325,
817, 416, 261, 1316, 957, 723, 215, 237, 270, 1309, 208,
17, 1028, 895, 574, 166, 784, 834, 732, 1022, 1068, 1207,
356, 474, 313, 137, 172, 181, 925, 201, 190, 1277, 1044,
1242, 702, 567, 557, 1032, 1352, 504, 545, 422, 179, 780,
280, 890, 774, 884])
ants_to_keep = np.array([11, 6, 20, 26, 2, 27, 7, 14])
ant_pairs_to_keep = [(2, 11), (20, 26), (6, 7), (3, 27), (14, 6)]
sorted_pairs_to_keep = [sort_bl(p) for p in ant_pairs_to_keep]
freqs_to_keep = uv_object.freq_array[0, np.arange(31, 39)]
unique_times = np.unique(uv_object.time_array)
times_to_keep = unique_times[[0, 2, 6, 8, 10, 13, 14]]
pols_to_keep = [-1, -3]
# Independently count blts that should be selected
blts_blt_select = [i in blt_inds for i in np.arange(uv_object.Nblts)]
blts_ant_select = [(a1 in ants_to_keep) & (a2 in ants_to_keep) for (a1, a2) in
zip(uv_object.ant_1_array, uv_object.ant_2_array)]
blts_pair_select = [sort_bl((a1, a2)) in sorted_pairs_to_keep for (a1, a2) in
zip(uv_object.ant_1_array, uv_object.ant_2_array)]
blts_time_select = [t in times_to_keep for t in uv_object.time_array]
Nblts_select = np.sum([bi & (ai & pi) & ti for (bi, ai, pi, ti) in
zip(blts_blt_select, blts_ant_select, blts_pair_select,
blts_time_select)])
uv_object2 = copy.deepcopy(uv_object)
uv_object2.select(blt_inds=blt_inds, antenna_nums=ants_to_keep,
bls=ant_pairs_to_keep, frequencies=freqs_to_keep,
times=times_to_keep, polarizations=pols_to_keep)
assert Nblts_select == uv_object2.Nblts
for ant in np.unique(uv_object2.ant_1_array.tolist() + uv_object2.ant_2_array.tolist()):
assert ant in ants_to_keep
assert len(freqs_to_keep) == uv_object2.Nfreqs
for f in freqs_to_keep:
assert f in uv_object2.freq_array
for f in np.unique(uv_object2.freq_array):
assert f in freqs_to_keep
for t in np.unique(uv_object2.time_array):
assert t in times_to_keep
assert len(pols_to_keep) == uv_object2.Npols
for p in pols_to_keep:
assert p in uv_object2.polarization_array
for p in np.unique(uv_object2.polarization_array):
assert p in pols_to_keep
assert uvutils._check_histories(old_history + ' Downselected to '
'specific baseline-times, antennas, '
'baselines, times, frequencies, '
'polarizations using pyuvdata.',
uv_object2.history)
# test that a ValueError is raised if the selection eliminates all blts
pytest.raises(ValueError, uv_object.select,
times=unique_times[0], antenna_nums=1)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_not_inplace():
# Test non-inplace select
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
old_history = uv_object.history
uv1 = uv_object.select(freq_chans=np.arange(32), inplace=False)
uv1 += uv_object.select(freq_chans=np.arange(32, 64), inplace=False)
assert uvutils._check_histories(old_history + ' Downselected to '
'specific frequencies using pyuvdata. '
'Combined data along frequency axis '
'using pyuvdata.', uv1.history)
uv1.history = old_history
assert uv1 == uv_object
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_conjugate_bls():
uv1 = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv1.read_uvfits(testfile)
# file comes in with ant1<ant2
assert(np.min(uv1.ant_2_array - uv1.ant_1_array) >= 0)
# check everything swapped & conjugated when go to ant2<ant1
uv2 = copy.deepcopy(uv1)
uv2.conjugate_bls(convention='ant2<ant1')
assert(np.min(uv2.ant_1_array - uv2.ant_2_array) >= 0)
assert(np.allclose(uv1.ant_1_array, uv2.ant_2_array))
assert(np.allclose(uv1.ant_2_array, uv2.ant_1_array))
assert(np.allclose(uv1.uvw_array, -1 * uv2.uvw_array,
rtol=uv1._uvw_array.tols[0], atol=uv1._uvw_array.tols[1]))
# complicated because of the polarization swaps
# polarization_array = [-1 -2 -3 -4]
assert(np.allclose(uv1.data_array[:, :, :, :2],
np.conj(uv2.data_array[:, :, :, :2]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[:, :, :, 2],
np.conj(uv2.data_array[:, :, :, 3]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[:, :, :, 3],
np.conj(uv2.data_array[:, :, :, 2]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
# check everything returned to original values with original convention
uv2.conjugate_bls(convention='ant1<ant2')
assert(uv1 == uv2)
# conjugate a particular set of blts
blts_to_conjugate = np.arange(uv2.Nblts // 2)
blts_not_conjugated = np.arange(uv2.Nblts // 2, uv2.Nblts)
uv2.conjugate_bls(convention=blts_to_conjugate)
assert(np.allclose(uv1.ant_1_array[blts_to_conjugate], uv2.ant_2_array[blts_to_conjugate]))
assert(np.allclose(uv1.ant_2_array[blts_to_conjugate], uv2.ant_1_array[blts_to_conjugate]))
assert(np.allclose(uv1.ant_1_array[blts_not_conjugated], uv2.ant_1_array[blts_not_conjugated]))
assert(np.allclose(uv1.ant_2_array[blts_not_conjugated], uv2.ant_2_array[blts_not_conjugated]))
assert(np.allclose(uv1.uvw_array[blts_to_conjugate],
-1 * uv2.uvw_array[blts_to_conjugate],
rtol=uv1._uvw_array.tols[0], atol=uv1._uvw_array.tols[1]))
assert(np.allclose(uv1.uvw_array[blts_not_conjugated],
uv2.uvw_array[blts_not_conjugated],
rtol=uv1._uvw_array.tols[0], atol=uv1._uvw_array.tols[1]))
# complicated because of the polarization swaps
# polarization_array = [-1 -2 -3 -4]
assert(np.allclose(uv1.data_array[blts_to_conjugate, :, :, :2],
np.conj(uv2.data_array[blts_to_conjugate, :, :, :2]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[blts_not_conjugated, :, :, :2],
uv2.data_array[blts_not_conjugated, :, :, :2],
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[blts_to_conjugate, :, :, 2],
np.conj(uv2.data_array[blts_to_conjugate, :, :, 3]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[blts_not_conjugated, :, :, 2],
uv2.data_array[blts_not_conjugated, :, :, 2],
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[blts_to_conjugate, :, :, 3],
np.conj(uv2.data_array[blts_to_conjugate, :, :, 2]),
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
assert(np.allclose(uv1.data_array[blts_not_conjugated, :, :, 3],
uv2.data_array[blts_not_conjugated, :, :, 3],
rtol=uv1._data_array.tols[0], atol=uv1._data_array.tols[1]))
# check uv half plane conventions
uv2.conjugate_bls(convention='u<0', use_enu=False)
assert(np.max(uv2.uvw_array[:, 0]) <= 0)
uv2.conjugate_bls(convention='u>0', use_enu=False)
assert(np.min(uv2.uvw_array[:, 0]) >= 0)
uv2.conjugate_bls(convention='v<0', use_enu=False)
assert(np.max(uv2.uvw_array[:, 1]) <= 0)
uv2.conjugate_bls(convention='v>0', use_enu=False)
assert(np.min(uv2.uvw_array[:, 1]) >= 0)
# unphase to drift to test using ENU positions
uv2.unphase_to_drift(use_ant_pos=True)
uv2.conjugate_bls(convention='u<0')
assert(np.max(uv2.uvw_array[:, 0]) <= 0)
uv2.conjugate_bls(convention='u>0')
assert(np.min(uv2.uvw_array[:, 0]) >= 0)
uv2.conjugate_bls(convention='v<0')
assert(np.max(uv2.uvw_array[:, 1]) <= 0)
uv2.conjugate_bls(convention='v>0')
assert(np.min(uv2.uvw_array[:, 1]) >= 0)
# test errors
with pytest.raises(ValueError) as cm:
uv2.conjugate_bls(convention='foo')
assert str(cm.value).startswith('convention must be one of')
with pytest.raises(ValueError) as cm:
uv2.conjugate_bls(convention=np.arange(5) - 1)
assert str(cm.value).startswith('If convention is an index array')
with pytest.raises(ValueError) as cm:
uv2.conjugate_bls(convention=[uv2.Nblts])
assert str(cm.value).startswith('If convention is an index array')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_reorder_pols():
# Test function to fix polarization order
uv1 = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv1.read_uvfits(testfile)
uv2 = copy.deepcopy(uv1)
# reorder uv2 manually
order = [1, 3, 2, 0]
uv2.polarization_array = uv2.polarization_array[order]
uv2.data_array = uv2.data_array[:, :, :, order]
uv2.nsample_array = uv2.nsample_array[:, :, :, order]
uv2.flag_array = uv2.flag_array[:, :, :, order]
uv1.reorder_pols(order=order)
assert uv1 == uv2
# Restore original order
uv1.read_uvfits(testfile)
uv2.reorder_pols()
assert uv1 == uv2
uv1.reorder_pols(order='AIPS')
# check that we have aips ordering
aips_pols = np.array([-1, -2, -3, -4]).astype(int)
assert np.all(uv1.polarization_array == aips_pols)
uv2 = copy.deepcopy(uv1)
uv2.reorder_pols(order='CASA')
# check that we have casa ordering
casa_pols = np.array([-1, -3, -4, -2]).astype(int)
assert np.all(uv2.polarization_array == casa_pols)
order = np.array([0, 2, 3, 1])
assert np.all(uv2.data_array == uv1.data_array[:, :, :, order])
assert np.all(uv2.flag_array == uv1.flag_array[:, :, :, order])
uv2.reorder_pols(order='AIPS')
# check that we have aips ordering again
assert uv1 == uv2
# check error on unknown order
pytest.raises(ValueError, uv2.reorder_pols, {'order': 'foo'})
# check error if order is an array of the wrong length
with pytest.raises(ValueError) as cm:
uv2.reorder_pols(order=[3, 2, 1])
assert str(cm.value).startswith('If order is an index array, it must')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_reorder_blts():
uv1 = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv1.read_uvfits(testfile)
# test default reordering in detail
uv2 = copy.deepcopy(uv1)
uv2.reorder_blts()
assert(uv2.blt_order == ('time', 'baseline'))
assert(np.min(np.diff(uv2.time_array)) >= 0)
for this_time in np.unique(uv2.time_array):
bls_2 = uv2.baseline_array[np.where(uv2.time_array == this_time)]
bls_1 = uv1.baseline_array[np.where(uv2.time_array == this_time)]
assert(bls_1.shape == bls_2.shape)
assert(np.min(np.diff(bls_2)) >= 0)
bl_inds = [np.where(bls_1 == bl)[0][0] for bl in bls_2]
assert(np.allclose(bls_1[bl_inds], bls_2))
uvw_1 = uv1.uvw_array[np.where(uv2.time_array == this_time)[0], :]
uvw_2 = uv2.uvw_array[np.where(uv2.time_array == this_time)[0], :]
assert(uvw_1.shape == uvw_2.shape)
assert(np.allclose(uvw_1[bl_inds, :], uvw_2))
data_1 = uv1.data_array[np.where(uv2.time_array == this_time)[0], :, :, :]
data_2 = uv2.data_array[np.where(uv2.time_array == this_time)[0], :, :, :]
assert(data_1.shape == data_2.shape)
assert(np.allclose(data_1[bl_inds, :, :, :], data_2))
# check that ordering by time, ant1 is identical to time, baseline
uv3 = copy.deepcopy(uv1)
uv3.reorder_blts(order='time', minor_order='ant1')
assert(uv3.blt_order == ('time', 'ant1'))
assert(np.min(np.diff(uv3.time_array)) >= 0)
uv3.blt_order = uv2.blt_order
assert(uv2 == uv3)
uv3.reorder_blts(order='time', minor_order='ant2')
assert(uv3.blt_order == ('time', 'ant2'))
assert(np.min(np.diff(uv3.time_array)) >= 0)
# check that loopback works
uv3.reorder_blts()
assert(uv2 == uv3)
# sort with a specified index array
new_order = np.lexsort((uv3.baseline_array, uv3.time_array))
uv3.reorder_blts(order=new_order)
assert(uv3.blt_order is None)
assert(np.min(np.diff(uv3.time_array)) >= 0)
uv3.blt_order = ('time', 'baseline')
assert(uv2 == uv3)
# test sensible defaulting if minor order = major order
uv3.reorder_blts(order='time', minor_order='time')
assert(uv2 == uv3)
# test all combinations of major, minor order
uv3.reorder_blts(order='baseline')
assert(uv3.blt_order == ('baseline', 'time'))
assert(np.min(np.diff(uv3.baseline_array)) >= 0)
uv3.reorder_blts(order='ant1')
assert(uv3.blt_order == ('ant1', 'ant2'))
assert(np.min(np.diff(uv3.ant_1_array)) >= 0)
uv3.reorder_blts(order='ant1', minor_order='time')
assert(uv3.blt_order == ('ant1', 'time'))
assert(np.min(np.diff(uv3.ant_1_array)) >= 0)
uv3.reorder_blts(order='ant1', minor_order='baseline')
assert(uv3.blt_order == ('ant1', 'baseline'))
assert(np.min(np.diff(uv3.ant_1_array)) >= 0)
uv3.reorder_blts(order='ant2')
assert(uv3.blt_order == ('ant2', 'ant1'))
assert(np.min(np.diff(uv3.ant_2_array)) >= 0)
uv3.reorder_blts(order='ant2', minor_order='time')
assert(uv3.blt_order == ('ant2', 'time'))
assert(np.min(np.diff(uv3.ant_2_array)) >= 0)
uv3.reorder_blts(order='ant2', minor_order='baseline')
assert(uv3.blt_order == ('ant2', 'baseline'))
assert(np.min(np.diff(uv3.ant_2_array)) >= 0)
uv3.reorder_blts(order='bda')
assert(uv3.blt_order == ('bda',))
assert(np.min(np.diff(uv3.integration_time)) >= 0)
assert(np.min(np.diff(uv3.baseline_array)) >= 0)
# test doing conjugation along with a reorder
# the file is already conjugated this way, so should be equal
uv3.reorder_blts(order='time', conj_convention='ant1<ant2')
assert(uv2 == uv3)
# test errors
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order='foo')
assert str(cm.value).startswith('order must be one of')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order=np.arange(5))
assert str(cm.value).startswith('If order is an index array, it must')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order=np.arange(5, dtype=np.float))
assert str(cm.value).startswith('If order is an index array, it must')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order=np.arange(uv3.Nblts), minor_order='time')
assert str(cm.value).startswith('Minor order cannot be set if order is an index array')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order='bda', minor_order='time')
assert str(cm.value).startswith('minor_order cannot be specified if order is')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order='baseline', minor_order='ant1')
assert str(cm.value).startswith('minor_order conflicts with order')
with pytest.raises(ValueError) as cm:
uv3.reorder_blts(order='time', minor_order='foo')
assert str(cm.value).startswith('minor_order can only be one of')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_sum_vis():
# check sum_vis
uv_full = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
uv_half = copy.deepcopy(uv_full)
uv_half.data_array = uv_full.data_array / 2
uv_summed = uv_half.sum_vis(uv_half)
assert np.array_equal(uv_summed.data_array, uv_full.data_array)
assert uvutils._check_histories(uv_half.history + ' Visibilities summed '
'using pyuvdata.', uv_summed.history)
# check diff_vis
uv_diffed = uv_full.diff_vis(uv_half)
assert np.array_equal(uv_diffed.data_array, uv_half.data_array)
assert uvutils._check_histories(uv_full.history + ' Visibilities '
'differenced using pyuvdata.',
uv_diffed.history)
# check in place
uv_summed.diff_vis(uv_half, inplace=True)
assert np.array_equal(uv_summed.data_array, uv_half.data_array)
# check error messages
with pytest.raises(ValueError) as cm:
uv_full.sum_vis('foo')
assert str(cm.value).startswith('Only UVData (or subclass) objects can be')
uv_full.instrument = 'foo'
with pytest.raises(ValueError) as cm:
uv_full.sum_vis(uv_half, inplace=True)
assert str(cm.value).startswith('UVParameter instrument '
'does not match')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_add():
uv_full = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
# Add frequencies
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
uv1 += uv2
# Check history is correct, before replacing and doing a full object check
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific frequencies using pyuvdata. '
'Combined data along frequency axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add frequencies - out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
uv2 += uv1
uv2.history = uv_full.history
assert uv2 == uv_full
# Add polarizations
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add polarizations - out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv2 += uv1
uv2.history = uv_full.history
assert uv2 == uv_full
# Add times
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add baselines
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
ant_list = list(range(15)) # Roughly half the antennas in the data
# All blts where ant_1 is in list
ind1 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] in ant_list]
ind2 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] not in ant_list]
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific baseline-times using pyuvdata. '
'Combined data along baseline-time axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add baselines - out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv3 = copy.deepcopy(uv_full)
ants = uv_full.get_ants()
ants1 = ants[0:6]
ants2 = ants[6:12]
ants3 = ants[12:]
# All blts where ant_1 is in list
ind1 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] in ants1]
ind2 = [i for i in range(uv2.Nblts) if uv2.ant_1_array[i] in ants2]
ind3 = [i for i in range(uv3.Nblts) if uv3.ant_1_array[i] in ants3]
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv3.select(blt_inds=ind3)
uv3.data_array = uv3.data_array[-1::-1, :, :, :]
uv3.nsample_array = uv3.nsample_array[-1::-1, :, :, :]
uv3.flag_array = uv3.flag_array[-1::-1, :, :, :]
uv3.uvw_array = uv3.uvw_array[-1::-1, :]
uv3.time_array = uv3.time_array[-1::-1]
uv3.lst_array = uv3.lst_array[-1::-1]
uv3.ant_1_array = uv3.ant_1_array[-1::-1]
uv3.ant_2_array = uv3.ant_2_array[-1::-1]
uv3.baseline_array = uv3.baseline_array[-1::-1]
uv1 += uv3
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific baseline-times using pyuvdata. '
'Combined data along baseline-time axis '
'using pyuvdata. Combined data along '
'baseline-time axis using pyuvdata.',
uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add multiple axes
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv_ref = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2],
polarizations=uv1.polarization_array[0:2])
uv2.select(times=times[len(times) // 2:],
polarizations=uv2.polarization_array[2:4])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times, polarizations using '
'pyuvdata. Combined data along '
'baseline-time, polarization axis '
'using pyuvdata.', uv1.history)
blt_ind1 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[0:len(times) // 2]])
blt_ind2 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[len(times) // 2:]])
# Zero out missing data in reference object
uv_ref.data_array[blt_ind1, :, :, 2:] = 0.0
uv_ref.nsample_array[blt_ind1, :, :, 2:] = 0.0
uv_ref.flag_array[blt_ind1, :, :, 2:] = True
uv_ref.data_array[blt_ind2, :, :, 0:2] = 0.0
uv_ref.nsample_array[blt_ind2, :, :, 0:2] = 0.0
uv_ref.flag_array[blt_ind2, :, :, 0:2] = True
uv1.history = uv_full.history
assert uv1 == uv_ref
# Another combo
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv_ref = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2], freq_chans=np.arange(0, 32))
uv2.select(times=times[len(times) // 2:], freq_chans=np.arange(32, 64))
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times, frequencies using '
'pyuvdata. Combined data along '
'baseline-time, frequency axis using '
'pyuvdata.', uv1.history)
blt_ind1 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[0:len(times) // 2]])
blt_ind2 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[len(times) // 2:]])
# Zero out missing data in reference object
uv_ref.data_array[blt_ind1, :, 32:, :] = 0.0
uv_ref.nsample_array[blt_ind1, :, 32:, :] = 0.0
uv_ref.flag_array[blt_ind1, :, 32:, :] = True
uv_ref.data_array[blt_ind2, :, 0:32, :] = 0.0
uv_ref.nsample_array[blt_ind2, :, 0:32, :] = 0.0
uv_ref.flag_array[blt_ind2, :, 0:32, :] = True
uv1.history = uv_full.history
assert uv1 == uv_ref
# Add without inplace
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1 = uv1 + uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Check warnings
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(33, 64))
uvtest.checkWarnings(uv1.__add__, [uv2],
message='Combined frequencies are not evenly spaced')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=[0])
uv2.select(freq_chans=[3])
uvtest.checkWarnings(uv1.__iadd__, [uv2],
message='Combined frequencies are not contiguous')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=[0])
uv2.select(freq_chans=[1])
uv2.freq_array += uv2._channel_width.tols[1] / 2.
uvtest.checkWarnings(uv1.__iadd__, [uv2],
nwarnings=0)
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[3])
uvtest.checkWarnings(uv1.__iadd__, [uv2],
message='Combined polarizations are not evenly spaced')
# Combining histories
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv2.history += ' testing the history. AIPS WTSCAL = 1.0'
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization '
'axis using pyuvdata. testing the history.',
uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# test add of autocorr-only and crosscorr-only objects
uv_full = UVData()
uv_full.read_miriad(os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcA'))
bls = uv_full.get_antpairs()
autos = [bl for bl in bls if bl[0] == bl[1]]
cross = sorted(set(bls) - set(autos))
uv_auto = uv_full.select(bls=autos, inplace=False)
uv_cross = uv_full.select(bls=cross, inplace=False)
uv1 = uv_auto + uv_cross
assert uv1.Nbls == uv_auto.Nbls + uv_cross.Nbls
uv2 = uv_cross + uv_auto
assert uv2.Nbls == uv_auto.Nbls + uv_cross.Nbls
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_add_drift():
uv_full = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
uv_full.unphase_to_drift()
# Add frequencies
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
uv1 += uv2
# Check history is correct, before replacing and doing a full object check
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific frequencies using pyuvdata. '
'Combined data along frequency '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add polarizations
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add times
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add baselines
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
ant_list = list(range(15)) # Roughly half the antennas in the data
# All blts where ant_1 is in list
ind1 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] in ant_list]
ind2 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] not in ant_list]
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific baseline-times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add multiple axes
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv_ref = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2],
polarizations=uv1.polarization_array[0:2])
uv2.select(times=times[len(times) // 2:],
polarizations=uv2.polarization_array[2:4])
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times, polarizations using '
'pyuvdata. Combined data along '
'baseline-time, polarization '
'axis using pyuvdata.', uv1.history)
blt_ind1 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[0:len(times) // 2]])
blt_ind2 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[len(times) // 2:]])
# Zero out missing data in reference object
uv_ref.data_array[blt_ind1, :, :, 2:] = 0.0
uv_ref.nsample_array[blt_ind1, :, :, 2:] = 0.0
uv_ref.flag_array[blt_ind1, :, :, 2:] = True
uv_ref.data_array[blt_ind2, :, :, 0:2] = 0.0
uv_ref.nsample_array[blt_ind2, :, :, 0:2] = 0.0
uv_ref.flag_array[blt_ind2, :, :, 0:2] = True
uv1.history = uv_full.history
assert uv1 == uv_ref
# Another combo
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv_ref = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2], freq_chans=np.arange(0, 32))
uv2.select(times=times[len(times) // 2:], freq_chans=np.arange(32, 64))
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times, frequencies using '
'pyuvdata. Combined data along '
'baseline-time, frequency '
'axis using pyuvdata.', uv1.history)
blt_ind1 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[0:len(times) // 2]])
blt_ind2 = np.array([ind for ind in range(uv_full.Nblts) if
uv_full.time_array[ind] in times[len(times) // 2:]])
# Zero out missing data in reference object
uv_ref.data_array[blt_ind1, :, 32:, :] = 0.0
uv_ref.nsample_array[blt_ind1, :, 32:, :] = 0.0
uv_ref.flag_array[blt_ind1, :, 32:, :] = True
uv_ref.data_array[blt_ind2, :, 0:32, :] = 0.0
uv_ref.nsample_array[blt_ind2, :, 0:32, :] = 0.0
uv_ref.flag_array[blt_ind2, :, 0:32, :] = True
uv1.history = uv_full.history
assert uv1 == uv_ref
# Add without inplace
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1 = uv1 + uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Check warnings
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(33, 64))
uvtest.checkWarnings(uv1.__add__, [uv2],
message='Combined frequencies are not evenly spaced')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=[0])
uv2.select(freq_chans=[3])
uvtest.checkWarnings(uv1.__iadd__, [uv2],
message='Combined frequencies are not contiguous')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[3])
uvtest.checkWarnings(uv1.__iadd__, [uv2],
message='Combined polarizations are not evenly spaced')
# Combining histories
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv2.history += ' testing the history. AIPS WTSCAL = 1.0'
uv1 += uv2
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization '
'axis using pyuvdata. testing the history.',
uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_break_add():
# Test failure modes of add function
uv_full = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
# Wrong class
uv1 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
pytest.raises(ValueError, uv1.__iadd__, np.zeros(5))
# One phased, one not
uv2 = copy.deepcopy(uv_full)
uv2.unphase_to_drift()
pytest.raises(ValueError, uv1.__iadd__, uv2)
# Different units
uv2 = copy.deepcopy(uv_full)
uv2.select(freq_chans=np.arange(32, 64))
uv2.vis_units = "Jy"
pytest.raises(ValueError, uv1.__iadd__, uv2)
# Overlapping data
uv2 = copy.deepcopy(uv_full)
pytest.raises(ValueError, uv1.__iadd__, uv2)
# Different integration_time
uv2 = copy.deepcopy(uv_full)
uv2.select(freq_chans=np.arange(32, 64))
uv2.integration_time *= 2
pytest.raises(ValueError, uv1.__iadd__, uv2)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_error_drift_and_rephase(test_func, extra_kwargs):
uv_full = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
with pytest.raises(ValueError) as cm:
getattr(uv_full, test_func)(uv_full, phase_center_radec=(0, 45),
unphase_to_drift=True,
**extra_kwargs
)
assert str(cm.value).startswith('phase_center_radec cannot be set if '
'unphase_to_drift is True.')
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_this_phased_unphase_to_drift(
uv_phase_time_split, test_func, extra_kwargs
):
(
uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
) = uv_phase_time_split
func_kwargs = {"unphase_to_drift": True,
"inplace": False,
}
func_kwargs.update(extra_kwargs)
uv_out = uvtest.checkWarnings(
getattr(uv_phase_1, test_func),
func_args=[uv_raw_2],
func_kwargs=func_kwargs,
message=['Unphasing this UVData object to drift']
)
# the histories will be different here
# but everything else should match.
uv_out.history = copy.deepcopy(uv_raw.history)
# ensure baseline time order is the same
# because fast_concat will not order for us
uv_out.reorder_blts(order='time', minor_order='baseline')
assert uv_out.phase_type == 'drift'
assert uv_out == uv_raw
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_other_phased_unphase_to_drift(
uv_phase_time_split, test_func, extra_kwargs
):
(
uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
) = uv_phase_time_split
func_kwargs = {"unphase_to_drift": True,
"inplace": False,
}
func_kwargs.update(extra_kwargs)
uv_out = uvtest.checkWarnings(
getattr(uv_raw_1, test_func),
func_args=[uv_phase_2],
func_kwargs=func_kwargs,
message=['Unphasing other UVData object to drift']
)
# the histories will be different here
# but everything else should match.
uv_out.history = copy.deepcopy(uv_raw.history)
# ensure baseline time order is the same
# because fast_concat will not order for us
uv_out.reorder_blts(order='time', minor_order='baseline')
assert uv_out.phase_type == 'drift'
assert uv_out == uv_raw
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_this_rephase_new_phase_center(
uv_phase_time_split, test_func, extra_kwargs
):
(
uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
) = uv_phase_time_split
phase_center_radec = (Angle('0d').rad, Angle('-30d').rad)
# phase each half to different spots
uv_raw_1.phase(ra=0,
dec=0,
use_ant_pos=True,
)
uv_raw_2.phase(ra=phase_center_radec[0],
dec=phase_center_radec[1],
use_ant_pos=True
)
# phase original to phase_center_radec
uv_raw.phase(ra=phase_center_radec[0],
dec=phase_center_radec[1],
use_ant_pos=True
)
func_kwargs = {"inplace": False,
"phase_center_radec": phase_center_radec,
"use_ant_pos": True
}
func_kwargs.update(extra_kwargs)
uv_out = uvtest.checkWarnings(
getattr(uv_raw_1, test_func),
func_args=[uv_raw_2],
func_kwargs=func_kwargs,
message=['Phasing this UVData object to phase_center_radec']
)
# the histories will be different here
# but everything else should match.
uv_out.history = copy.deepcopy(uv_raw.history)
# ensure baseline time order is the same
# because fast_concat will not order for us
uv_out.reorder_blts(order='time', minor_order='baseline')
assert (uv_out.phase_center_ra, uv_out.phase_center_dec) == phase_center_radec
assert uv_out == uv_raw
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_other_rephase_new_phase_center(
uv_phase_time_split, test_func, extra_kwargs
):
(
uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
) = uv_phase_time_split
phase_center_radec = (Angle('0d').rad, Angle('-30d').rad)
# phase each half to different spots
uv_raw_1.phase(ra=phase_center_radec[0],
dec=phase_center_radec[1],
use_ant_pos=True,
)
uv_raw_2.phase(ra=0,
dec=0,
use_ant_pos=True,
)
# phase original to phase_center_radec
uv_raw.phase(ra=phase_center_radec[0],
dec=phase_center_radec[1],
use_ant_pos=True,
)
func_kwargs = {"inplace": False,
"phase_center_radec": phase_center_radec,
"use_ant_pos": True,
}
func_kwargs.update(extra_kwargs)
uv_out = uvtest.checkWarnings(
getattr(uv_raw_1, test_func),
func_args=[uv_raw_2],
func_kwargs=func_kwargs,
message=['Phasing other UVData object to phase_center_radec']
)
# the histories will be different here
# but everything else should match.
uv_out.history = copy.deepcopy(uv_raw.history)
# ensure baseline time order is the same
# because fast_concat will not order for us
uv_out.reorder_blts(order='time', minor_order='baseline')
assert uv_out.phase_type == "phased"
assert (uv_out.phase_center_ra, uv_out.phase_center_dec) == phase_center_radec
assert uv_out == uv_raw
@pytest.mark.parametrize("test_func,extra_kwargs",
[("__add__", {}),
("fast_concat", {"axis": "blt"})
]
)
def test_add_error_too_long_phase_center(
uv_phase_time_split, test_func, extra_kwargs
):
(
uv_phase_1, uv_phase_2, uv_phase, uv_raw_1, uv_raw_2, uv_raw
) = uv_phase_time_split
phase_center_radec = (Angle('0d').rad, Angle('-30d').rad, 7)
func_kwargs = {"inplace": False,
"phase_center_radec": phase_center_radec,
}
func_kwargs.update(extra_kwargs)
with pytest.raises(ValueError) as cm:
getattr(uv_phase_1, test_func)(uv_phase_2, **func_kwargs)
assert str(cm.value).startswith('phase_center_radec should have length 2.')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_fast_concat():
uv_full = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
# Add frequencies
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
uv1.fast_concat(uv2, 'freq', inplace=True)
# Check history is correct, before replacing and doing a full object check
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific frequencies using pyuvdata. '
'Combined data along frequency axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add frequencies - out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
uvtest.checkWarnings(uv2.fast_concat, [uv1, 'freq'], {'inplace': True},
message='Combined frequencies are not evenly spaced')
assert uv2.Nfreqs == uv_full.Nfreqs
assert uv2._freq_array != uv_full._freq_array
assert uv2._data_array != uv_full._data_array
# reorder frequencies and test that they are equal
index_array = np.argsort(uv2.freq_array[0, :])
uv2.freq_array = uv2.freq_array[:, index_array]
uv2.data_array = uv2.data_array[:, :, index_array, :]
uv2.nsample_array = uv2.nsample_array[:, :, index_array, :]
uv2.flag_array = uv2.flag_array[:, :, index_array, :]
uv2.history = uv_full.history
assert uv2._freq_array == uv_full._freq_array
assert uv2 == uv_full
# Add polarizations
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv1.fast_concat(uv2, 'polarization', inplace=True)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add polarizations - out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uvtest.checkWarnings(uv2.fast_concat, [uv1, 'polarization'], {'inplace': True},
message='Combined polarizations are not evenly spaced')
assert uv2._polarization_array != uv_full._polarization_array
assert uv2._data_array != uv_full._data_array
# reorder pols
uv2.reorder_pols()
uv2.history = uv_full.history
assert uv2 == uv_full
# Add times
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1.fast_concat(uv2, 'blt', inplace=True)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Add baselines
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
# divide in half to keep in order
ind1 = np.arange(uv1.Nblts // 2)
ind2 = np.arange(uv1.Nblts // 2, uv1.Nblts)
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv1.fast_concat(uv2, 'blt', inplace=True)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific baseline-times using pyuvdata. '
'Combined data along baseline-time axis '
'using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1, uv_full
# Add baselines out of order
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv2.fast_concat(uv1, 'blt', inplace=True)
# test freq & pol arrays equal
assert uv2._freq_array == uv_full._freq_array
assert uv2._polarization_array == uv_full._polarization_array
# test Nblt length arrays not equal but same shape
assert uv2._ant_1_array != uv_full._ant_1_array
assert uv2.ant_1_array.shape == uv_full.ant_1_array.shape
assert uv2._ant_2_array != uv_full._ant_2_array
assert uv2.ant_2_array.shape == uv_full.ant_2_array.shape
assert uv2._uvw_array != uv_full._uvw_array
assert uv2.uvw_array.shape == uv_full.uvw_array.shape
assert uv2._time_array != uv_full._time_array
assert uv2.time_array.shape == uv_full.time_array.shape
assert uv2._baseline_array != uv_full._baseline_array
assert uv2.baseline_array.shape == uv_full.baseline_array.shape
assert uv2._data_array != uv_full._data_array
assert uv2.data_array.shape == uv_full.data_array.shape
# reorder blts to enable comparison
uv2.reorder_blts()
assert uv2.blt_order == ('time', 'baseline')
uv2.blt_order = None
uv2.history = uv_full.history
assert uv2 == uv_full
# add baselines such that Nants_data needs to change
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
ant_list = list(range(15)) # Roughly half the antennas in the data
# All blts where ant_1 is in list
ind1 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] in ant_list]
ind2 = [i for i in range(uv1.Nblts) if uv1.ant_1_array[i] not in ant_list]
uv1.select(blt_inds=ind1)
uv2.select(blt_inds=ind2)
uv2.fast_concat(uv1, 'blt', inplace=True)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific baseline-times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv2.history)
# test freq & pol arrays equal
assert uv2._freq_array == uv_full._freq_array
assert uv2._polarization_array == uv_full._polarization_array
# test Nblt length arrays not equal but same shape
assert uv2._ant_1_array != uv_full._ant_1_array
assert uv2.ant_1_array.shape == uv_full.ant_1_array.shape
assert uv2._ant_2_array != uv_full._ant_2_array
assert uv2.ant_2_array.shape == uv_full.ant_2_array.shape
assert uv2._uvw_array != uv_full._uvw_array
assert uv2.uvw_array.shape == uv_full.uvw_array.shape
assert uv2._time_array != uv_full._time_array
assert uv2.time_array.shape == uv_full.time_array.shape
assert uv2._baseline_array != uv_full._baseline_array
assert uv2.baseline_array.shape == uv_full.baseline_array.shape
assert uv2._data_array != uv_full._data_array
assert uv2.data_array.shape == uv_full.data_array.shape
# reorder blts to enable comparison
uv2.reorder_blts()
assert uv2.blt_order == ('time', 'baseline')
uv2.blt_order = None
uv2.history = uv_full.history
assert uv2 == uv_full
# Add multiple axes
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2],
polarizations=uv1.polarization_array[0:2])
uv2.select(times=times[len(times) // 2:],
polarizations=uv2.polarization_array[2:4])
pytest.raises(ValueError, uv1.fast_concat, uv2, 'blt', inplace=True)
# Another combo
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2], freq_chans=np.arange(0, 32))
uv2.select(times=times[len(times) // 2:], freq_chans=np.arange(32, 64))
pytest.raises(ValueError, uv1.fast_concat, uv2, 'blt', inplace=True)
# Add without inplace
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
times = np.unique(uv_full.time_array)
uv1.select(times=times[0:len(times) // 2])
uv2.select(times=times[len(times) // 2:])
uv1 = uv1.fast_concat(uv2, 'blt', inplace=False)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific times using pyuvdata. '
'Combined data along baseline-time '
'axis using pyuvdata.', uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# Check warnings
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(33, 64))
uvtest.checkWarnings(uv1.fast_concat, [uv2, 'freq'],
message='Combined frequencies are not evenly spaced')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=[0])
uv2.select(freq_chans=[3])
uvtest.checkWarnings(uv1.fast_concat, [uv2, 'freq'],
message='Combined frequencies are not contiguous')
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=[0])
uv2.select(freq_chans=[1])
uv2.freq_array += uv2._channel_width.tols[1] / 2.
uvtest.checkWarnings(uv1.fast_concat, [uv2, 'freq'],
nwarnings=0)
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[3])
uvtest.checkWarnings(uv1.fast_concat, [uv2, 'polarization'],
message='Combined polarizations are not evenly spaced')
# Combining histories
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(polarizations=uv1.polarization_array[0:2])
uv2.select(polarizations=uv2.polarization_array[2:4])
uv2.history += ' testing the history. AIPS WTSCAL = 1.0'
uv1.fast_concat(uv2, 'polarization', inplace=True)
assert uvutils._check_histories(uv_full.history + ' Downselected to '
'specific polarizations using pyuvdata. '
'Combined data along polarization '
'axis using pyuvdata. testing the history.',
uv1.history)
uv1.history = uv_full.history
assert uv1 == uv_full
# test add of autocorr-only and crosscorr-only objects
uv_full = UVData()
uv_full.read_miriad(os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcA'))
bls = uv_full.get_antpairs()
autos = [bl for bl in bls if bl[0] == bl[1]]
cross = sorted(set(bls) - set(autos))
uv_auto = uv_full.select(bls=autos, inplace=False)
uv_cross = uv_full.select(bls=cross, inplace=False)
uv1 = uv_auto.fast_concat(uv_cross, 'blt')
assert uv1.Nbls == uv_auto.Nbls + uv_cross.Nbls
uv2 = uv_cross.fast_concat(uv_auto, 'blt')
assert uv2.Nbls == uv_auto.Nbls + uv_cross.Nbls
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_fast_concat_errors():
uv_full = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_full.read_uvfits(testfile)
uv1 = copy.deepcopy(uv_full)
uv2 = copy.deepcopy(uv_full)
uv1.select(freq_chans=np.arange(0, 32))
uv2.select(freq_chans=np.arange(32, 64))
pytest.raises(ValueError, uv1.fast_concat, uv2, 'foo', inplace=True)
cal = UVCal()
pytest.raises(ValueError, uv1.fast_concat, cal, 'freq', inplace=True)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds():
# Test function to interpret key as antpair, pol
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# Get an antpair/pol combo
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pol = uv.polarization_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
ind1, ind2, indp = uv._key2inds((ant1, ant2, pol))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal([0], indp[0])
# Any of these inputs can also be a tuple of a tuple, so need to be checked twice.
ind1, ind2, indp = uv._key2inds(((ant1, ant2, pol),))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal([0], indp[0])
# Combo with pol as string
ind1, ind2, indp = uv._key2inds((ant1, ant2, uvutils.polnum2str(pol)))
assert np.array_equal([0], indp[0])
ind1, ind2, indp = uv._key2inds(((ant1, ant2, uvutils.polnum2str(pol)),))
assert np.array_equal([0], indp[0])
# Check conjugation
ind1, ind2, indp = uv._key2inds((ant2, ant1, pol))
assert np.array_equal(bltind, ind2)
assert np.array_equal(np.array([]), ind1)
assert np.array_equal([0], indp[1])
# Conjugation with pol as string
ind1, ind2, indp = uv._key2inds((ant2, ant1, uvutils.polnum2str(pol)))
assert np.array_equal(bltind, ind2)
assert np.array_equal(np.array([]), ind1)
assert np.array_equal([0], indp[1])
assert np.array_equal([], indp[0])
# Antpair only
ind1, ind2, indp = uv._key2inds((ant1, ant2))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.arange(uv.Npols), indp[0])
ind1, ind2, indp = uv._key2inds(((ant1, ant2)))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.arange(uv.Npols), indp[0])
# Baseline number only
ind1, ind2, indp = uv._key2inds(uv.antnums_to_baseline(ant1, ant2))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.arange(uv.Npols), indp[0])
ind1, ind2, indp = uv._key2inds((uv.antnums_to_baseline(ant1, ant2),))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.arange(uv.Npols), indp[0])
# Pol number only
ind1, ind2, indp = uv._key2inds(pol)
assert np.array_equal(np.arange(uv.Nblts), ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([0]), indp[0])
ind1, ind2, indp = uv._key2inds((pol))
assert np.array_equal(np.arange(uv.Nblts), ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([0]), indp[0])
# Pol string only
ind1, ind2, indp = uv._key2inds('LL')
assert np.array_equal(np.arange(uv.Nblts), ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([1]), indp[0])
ind1, ind2, indp = uv._key2inds(('LL'))
assert np.array_equal(np.arange(uv.Nblts), ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([1]), indp[0])
# Test invalid keys
pytest.raises(KeyError, uv._key2inds, 'I') # pol str not in data
pytest.raises(KeyError, uv._key2inds, -8) # pol num not in data
pytest.raises(KeyError, uv._key2inds, 6) # bl num not in data
pytest.raises(KeyError, uv._key2inds, (1, 1)) # ant pair not in data
pytest.raises(KeyError, uv._key2inds, (1, 1, 'rr')) # ant pair not in data
pytest.raises(KeyError, uv._key2inds, (0, 1, 'xx')) # pol not in data
# Test autos are handled correctly
uv.ant_2_array[0] = uv.ant_1_array[0]
ind1, ind2, indp = uv._key2inds((ant1, ant1, pol))
assert np.array_equal(ind1, [0])
assert np.array_equal(ind2, [])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
ind1, ind2, indp = uv._key2inds((ant2, ant1))
# Pols in data are 'rr', 'll', 'rl', 'lr'
# So conjugated order should be [0, 1, 3, 2]
assert np.array_equal(bltind, ind2)
assert np.array_equal(np.array([]), ind1)
assert np.array_equal(np.array([]), indp[0])
assert np.array_equal([0, 1, 3, 2], indp[1])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols_fringe():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
uv.select(polarizations=['rl'])
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
# Mix one instance of this baseline.
uv.ant_1_array[0] = ant2
uv.ant_2_array[0] = ant1
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
ind1, ind2, indp = uv._key2inds((ant1, ant2))
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([0]), indp[0])
assert np.array_equal(np.array([]), indp[1])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols_bl_fringe():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
uv.select(polarizations=['rl'])
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
# Mix one instance of this baseline.
uv.ant_1_array[0] = ant2
uv.ant_2_array[0] = ant1
uv.baseline_array[0] = uvutils.antnums_to_baseline(ant2, ant1, uv.Nants_telescope)
bl = uvutils.antnums_to_baseline(ant1, ant2, uv.Nants_telescope)
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
ind1, ind2, indp = uv._key2inds(bl)
assert np.array_equal(bltind, ind1)
assert np.array_equal(np.array([]), ind2)
assert np.array_equal(np.array([0]), indp[0])
assert np.array_equal(np.array([]), indp[1])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols_missing_data():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
uv.select(polarizations=['rl'])
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pytest.raises(KeyError, uv._key2inds, (ant2, ant1))
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols_bls():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
bl = uvutils.antnums_to_baseline(ant2, ant1, uv.Nants_telescope)
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
ind1, ind2, indp = uv._key2inds(bl)
# Pols in data are 'rr', 'll', 'rl', 'lr'
# So conjugated order should be [0, 1, 3, 2]
assert np.array_equal(bltind, ind2)
assert np.array_equal(np.array([]), ind1)
assert np.array_equal(np.array([]), indp[0])
assert np.array_equal([0, 1, 3, 2], indp[1])
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_key2inds_conj_all_pols_missing_data_bls():
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
uv.select(polarizations=['rl'])
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
bl = uvutils.antnums_to_baseline(ant2, ant1, uv.Nants_telescope)
pytest.raises(KeyError, uv._key2inds, bl)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_smart_slicing():
# Test function to slice data
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# ind1 reg, ind2 empty, pol reg
ind1 = 10 * np.arange(9)
ind2 = []
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []))
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
assert not d.flags.writeable
# Ensure a view was returned
uv.data_array[ind1[1], 0, 0, indp[0]] = 5.43
assert d[1, 0, 0] == uv.data_array[ind1[1], 0, 0, indp[0]]
# force copy
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []), force_copy=True)
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
assert d.flags.writeable
# Ensure a copy was returned
uv.data_array[ind1[1], 0, 0, indp[0]] = 4.3
assert d[1, 0, 0] != uv.data_array[ind1[1], 0, 0, indp[0]]
# ind1 reg, ind2 empty, pol not reg
ind1 = 10 * np.arange(9)
ind2 = []
indp = [0, 1, 3]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []))
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
assert not d.flags.writeable
# Ensure a copy was returned
uv.data_array[ind1[1], 0, 0, indp[0]] = 1.2
assert d[1, 0, 0] != uv.data_array[ind1[1], 0, 0, indp[0]]
# ind1 not reg, ind2 empty, pol reg
ind1 = [0, 4, 5]
ind2 = []
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []))
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
assert not d.flags.writeable
# Ensure a copy was returned
uv.data_array[ind1[1], 0, 0, indp[0]] = 8.2
assert d[1, 0, 0] != uv.data_array[ind1[1], 0, 0, indp[0]]
# ind1 not reg, ind2 empty, pol not reg
ind1 = [0, 4, 5]
ind2 = []
indp = [0, 1, 3]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []))
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
assert not d.flags.writeable
# Ensure a copy was returned
uv.data_array[ind1[1], 0, 0, indp[0]] = 3.4
assert d[1, 0, 0] != uv.data_array[ind1[1], 0, 0, indp[0]]
# ind1 empty, ind2 reg, pol reg
# Note conjugation test ensures the result is a copy, not a view.
ind1 = []
ind2 = 10 * np.arange(9)
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, ([], indp))
dcheck = uv.data_array[ind2, :, :, :]
dcheck = np.squeeze(np.conj(dcheck[:, :, :, indp]))
assert np.all(d == dcheck)
# ind1 empty, ind2 reg, pol not reg
ind1 = []
ind2 = 10 * np.arange(9)
indp = [0, 1, 3]
d = uv._smart_slicing(uv.data_array, ind1, ind2, ([], indp))
dcheck = uv.data_array[ind2, :, :, :]
dcheck = np.squeeze(np.conj(dcheck[:, :, :, indp]))
assert np.all(d == dcheck)
# ind1 empty, ind2 not reg, pol reg
ind1 = []
ind2 = [1, 4, 5, 10]
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, ([], indp))
dcheck = uv.data_array[ind2, :, :, :]
dcheck = np.squeeze(np.conj(dcheck[:, :, :, indp]))
assert np.all(d == dcheck)
# ind1 empty, ind2 not reg, pol not reg
ind1 = []
ind2 = [1, 4, 5, 10]
indp = [0, 1, 3]
d = uv._smart_slicing(uv.data_array, ind1, ind2, ([], indp))
dcheck = uv.data_array[ind2, :, :, :]
dcheck = np.squeeze(np.conj(dcheck[:, :, :, indp]))
assert np.all(d == dcheck)
# ind1, ind2 not empty, pol reg
ind1 = np.arange(20)
ind2 = np.arange(30, 40)
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, indp))
dcheck = np.append(uv.data_array[ind1, :, :, :],
np.conj(uv.data_array[ind2, :, :, :]), axis=0)
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
# ind1, ind2 not empty, pol not reg
ind1 = np.arange(20)
ind2 = np.arange(30, 40)
indp = [0, 1, 3]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, indp))
dcheck = np.append(uv.data_array[ind1, :, :, :],
np.conj(uv.data_array[ind2, :, :, :]), axis=0)
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
# test single element
ind1 = [45]
ind2 = []
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []))
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp], axis=1)
assert np.all(d == dcheck)
# test single element
ind1 = []
ind2 = [45]
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, ([], indp))
assert np.all(d == np.conj(dcheck))
# Full squeeze
ind1 = [45]
ind2 = []
indp = [0, 1]
d = uv._smart_slicing(uv.data_array, ind1, ind2, (indp, []), squeeze='full')
dcheck = uv.data_array[ind1, :, :, :]
dcheck = np.squeeze(dcheck[:, :, :, indp])
assert np.all(d == dcheck)
# Test invalid squeeze
pytest.raises(ValueError, uv._smart_slicing, uv.data_array, ind1, ind2,
(indp, []), squeeze='notasqueeze')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_data():
# Test get_data function for easy access to data
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# Get an antpair/pol combo
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pol = uv.polarization_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
dcheck = np.squeeze(uv.data_array[bltind, :, :, 0])
d = uv.get_data(ant1, ant2, pol)
assert np.all(dcheck == d)
d = uv.get_data(ant1, ant2, uvutils.polnum2str(pol))
assert np.all(dcheck == d)
d = uv.get_data((ant1, ant2, pol))
assert np.all(dcheck == d)
with pytest.raises(ValueError) as cm:
uv.get_data((ant1, ant2, pol), (ant1, ant2, pol))
assert str(cm.value).startswith('no more than 3 key values can be passed')
# Check conjugation
d = uv.get_data(ant2, ant1, pol)
assert np.all(dcheck == np.conj(d))
# Check cross pol conjugation
d = uv.get_data(ant2, ant1, uv.polarization_array[2])
d1 = uv.get_data(ant1, ant2, uv.polarization_array[3])
assert np.all(d == np.conj(d1))
# Antpair only
dcheck = np.squeeze(uv.data_array[bltind, :, :, :])
d = uv.get_data(ant1, ant2)
assert np.all(dcheck == d)
# Pol number only
dcheck = np.squeeze(uv.data_array[:, :, :, 0])
d = uv.get_data(pol)
assert np.all(dcheck == d)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_flags():
# Test function for easy access to flags
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# Get an antpair/pol combo
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pol = uv.polarization_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
dcheck = np.squeeze(uv.flag_array[bltind, :, :, 0])
d = uv.get_flags(ant1, ant2, pol)
assert np.all(dcheck == d)
d = uv.get_flags(ant1, ant2, uvutils.polnum2str(pol))
assert np.all(dcheck == d)
d = uv.get_flags((ant1, ant2, pol))
assert np.all(dcheck == d)
with pytest.raises(ValueError) as cm:
uv.get_flags((ant1, ant2, pol), (ant1, ant2, pol))
assert str(cm.value).startswith('no more than 3 key values can be passed')
# Check conjugation
d = uv.get_flags(ant2, ant1, pol)
assert np.all(dcheck == d)
assert d.dtype == np.bool
# Antpair only
dcheck = np.squeeze(uv.flag_array[bltind, :, :, :])
d = uv.get_flags(ant1, ant2)
assert np.all(dcheck == d)
# Pol number only
dcheck = np.squeeze(uv.flag_array[:, :, :, 0])
d = uv.get_flags(pol)
assert np.all(dcheck == d)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_nsamples():
# Test function for easy access to nsample array
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# Get an antpair/pol combo
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pol = uv.polarization_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
dcheck = np.squeeze(uv.nsample_array[bltind, :, :, 0])
d = uv.get_nsamples(ant1, ant2, pol)
assert np.all(dcheck == d)
d = uv.get_nsamples(ant1, ant2, uvutils.polnum2str(pol))
assert np.all(dcheck == d)
d = uv.get_nsamples((ant1, ant2, pol))
assert np.all(dcheck == d)
with pytest.raises(ValueError) as cm:
uv.get_nsamples((ant1, ant2, pol), (ant1, ant2, pol))
assert str(cm.value).startswith('no more than 3 key values can be passed')
# Check conjugation
d = uv.get_nsamples(ant2, ant1, pol)
assert np.all(dcheck == d)
# Antpair only
dcheck = np.squeeze(uv.nsample_array[bltind, :, :, :])
d = uv.get_nsamples(ant1, ant2)
assert np.all(dcheck == d)
# Pol number only
dcheck = np.squeeze(uv.nsample_array[:, :, :, 0])
d = uv.get_nsamples(pol)
assert np.all(dcheck == d)
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_antpair2ind():
# Test for baseline-time axis indexer
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv.read_miriad(testfile)
# get indices
inds = uv.antpair2ind(0, 1, ordered=False)
np.testing.assert_array_equal(inds, np.array([1, 22, 43, 64, 85, 106, 127, 148, 169,
190, 211, 232, 253, 274, 295, 316,
337, 358, 379]))
assert inds.dtype == np.int
# conjugate (and use key rather than arg expansion)
inds2 = uv.antpair2ind((1, 0), ordered=False)
np.testing.assert_array_equal(inds, inds2)
# test ordered
inds3 = uv.antpair2ind(1, 0, ordered=True)
assert inds3.size == 0
inds3 = uv.antpair2ind(0, 1, ordered=True)
np.testing.assert_array_equal(inds, inds3)
# test autos w/ and w/o ordered
inds4 = uv.antpair2ind(0, 0, ordered=True)
inds5 = uv.antpair2ind(0, 0, ordered=False)
np.testing.assert_array_equal(inds4, inds5)
# test exceptions
pytest.raises(ValueError, uv.antpair2ind, 1)
pytest.raises(ValueError, uv.antpair2ind, 'bar', 'foo')
pytest.raises(ValueError, uv.antpair2ind, 0, 1, 'foo')
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_times():
# Test function for easy access to times, to work in conjunction with get_data
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# Get an antpair/pol combo (pol shouldn't actually effect result)
ant1 = uv.ant_1_array[0]
ant2 = uv.ant_2_array[0]
pol = uv.polarization_array[0]
bltind = np.where((uv.ant_1_array == ant1) & (uv.ant_2_array == ant2))[0]
dcheck = uv.time_array[bltind]
d = uv.get_times(ant1, ant2, pol)
assert np.all(dcheck == d)
d = uv.get_times(ant1, ant2, uvutils.polnum2str(pol))
assert np.all(dcheck == d)
d = uv.get_times((ant1, ant2, pol))
assert np.all(dcheck == d)
with pytest.raises(ValueError) as cm:
uv.get_times((ant1, ant2, pol), (ant1, ant2, pol))
assert str(cm.value).startswith('no more than 3 key values can be passed')
# Check conjugation
d = uv.get_times(ant2, ant1, pol)
assert np.all(dcheck == d)
# Antpair only
d = uv.get_times(ant1, ant2)
assert np.all(dcheck == d)
# Pol number only
d = uv.get_times(pol)
assert np.all(d == uv.time_array)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_antpairpol_iter():
# Test generator
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
pol_dict = {uvutils.polnum2str(uv.polarization_array[i]): i for i in range(uv.Npols)}
keys = []
pols = set()
bls = set()
for key, d in uv.antpairpol_iter():
keys += key
bl = uv.antnums_to_baseline(key[0], key[1])
blind = np.where(uv.baseline_array == bl)[0]
bls.add(bl)
pols.add(key[2])
dcheck = np.squeeze(uv.data_array[blind, :, :, pol_dict[key[2]]])
assert np.all(dcheck == d)
assert len(bls) == len(uv.get_baseline_nums())
assert len(pols) == uv.Npols
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_ants():
# Test function to get unique antennas in data
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
ants = uv.get_ants()
for ant in ants:
assert (ant in uv.ant_1_array) or (ant in uv.ant_2_array)
for ant in uv.ant_1_array:
assert ant in ants
for ant in uv.ant_2_array:
assert ant in ants
def test_get_ENU_antpos():
uvd = UVData()
uvd.read_miriad(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcA"))
# no center, no pick data ants
antpos, ants = uvd.get_ENU_antpos(center=False, pick_data_ants=False)
assert len(ants) == 113
assert np.isclose(antpos[0, 0], 19.340211050751535)
assert ants[0] == 0
# test default behavior
antpos2, ants = uvd.get_ENU_antpos()
assert np.all(antpos == antpos2)
# center
antpos, ants = uvd.get_ENU_antpos(center=True, pick_data_ants=False)
assert np.isclose(antpos[0, 0], 22.472442651767714)
# pick data ants
antpos, ants = uvd.get_ENU_antpos(center=True, pick_data_ants=True)
assert ants[0] == 9
assert np.isclose(antpos[0, 0], -0.0026981323386223721)
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_telescope_loc_XYZ_check():
# test that improper telescope locations can still be read
miriad_file = os.path.join(DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv = UVData()
uv.read(miriad_file)
uv.telescope_location = uvutils.XYZ_from_LatLonAlt(*uv.telescope_location)
fname = DATA_PATH + "/test/test.uv"
uv.write_miriad(fname, run_check=False, check_extra=False, clobber=True)
# try to read file without checks (passing is implicit)
uv.read(fname, run_check=False)
# try to read without checks: assert it fails
pytest.raises(ValueError, uv.read, fname)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_pols():
# Test function to get unique polarizations in string format
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
pols = uv.get_pols()
pols_data = ['rr', 'll', 'lr', 'rl']
assert sorted(pols) == sorted(pols_data)
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_get_pols_x_orientation():
miriad_file = os.path.join(DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv_in = UVData()
uv_in.read(miriad_file)
uv_in.x_orientation = 'east'
pols = uv_in.get_pols()
pols_data = ['en']
assert pols == pols_data
uv_in.x_orientation = 'north'
pols = uv_in.get_pols()
pols_data = ['ne']
assert pols == pols_data
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_get_feedpols():
# Test function to get unique antenna feed polarizations in data. String format.
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
pols = uv.get_feedpols()
pols_data = ['r', 'l']
assert sorted(pols) == sorted(pols_data)
# Test break when pseudo-Stokes visibilities are present
uv.polarization_array[0] = 1 # pseudo-Stokes I
pytest.raises(ValueError, uv.get_feedpols)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_parse_ants():
# Test function to get correct antenna pairs and polarizations
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# All baselines
ant_str = 'all'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
assert isinstance(ant_pairs_nums, type(None))
assert isinstance(polarizations, type(None))
# Auto correlations
ant_str = 'auto'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
assert Counter(ant_pairs_nums) == Counter([])
assert isinstance(polarizations, type(None))
# Cross correlations
ant_str = 'cross'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
assert Counter(uv.get_antpairs()) == Counter(ant_pairs_nums)
assert isinstance(polarizations, type(None))
# pseudo-Stokes params
ant_str = 'pI,pq,pU,pv'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
pols_expected = [4, 3, 2, 1]
assert isinstance(ant_pairs_nums, type(None))
assert Counter(polarizations) == Counter(pols_expected)
# Unparsible string
ant_str = 'none'
pytest.raises(ValueError, uv.parse_ants, ant_str)
# Single antenna number
ant_str = '0'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(0, 1), (0, 2), (0, 3), (0, 6), (0, 7), (0, 8),
(0, 11), (0, 14), (0, 18), (0, 19), (0, 20),
(0, 21), (0, 22), (0, 23), (0, 24), (0, 26),
(0, 27)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Single antenna number not in the data
ant_str = '10'
ant_pairs_nums, polarizations = uvtest.checkWarnings(uv.parse_ants,
[ant_str], {},
nwarnings=1,
message='Warning: Antenna')
assert isinstance(ant_pairs_nums, type(None))
assert isinstance(polarizations, type(None))
# Single antenna number with polarization, both not in the data
ant_str = '10x'
ant_pairs_nums, polarizations = uvtest.checkWarnings(uv.parse_ants,
[ant_str], {},
nwarnings=2,
message=['Warning: Antenna', 'Warning: Polarization'])
assert isinstance(ant_pairs_nums, type(None))
assert isinstance(polarizations, type(None))
# Multiple antenna numbers as list
ant_str = '22,26'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(0, 22), (0, 26), (1, 22), (1, 26), (2, 22), (2, 26),
(3, 22), (3, 26), (6, 22), (6, 26), (7, 22),
(7, 26), (8, 22), (8, 26), (11, 22), (11, 26),
(14, 22), (14, 26), (18, 22), (18, 26),
(19, 22), (19, 26), (20, 22), (20, 26),
(21, 22), (21, 26), (22, 23), (22, 24),
(22, 26), (22, 27), (23, 26), (24, 26),
(26, 27)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Single baseline
ant_str = '1_3'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 3)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Single baseline with polarization
ant_str = '1l_3r'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 3)]
pols_expected = [-4]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Single baseline with single polarization in first entry
ant_str = '1l_3,2x_3'
ant_pairs_nums, polarizations = uvtest.checkWarnings(uv.parse_ants,
[ant_str], {},
nwarnings=1,
message='Warning: Polarization')
ant_pairs_expected = [(1, 3), (2, 3)]
pols_expected = [-2, -4]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Single baseline with single polarization in last entry
ant_str = '1_3l,2_3x'
ant_pairs_nums, polarizations = uvtest.checkWarnings(uv.parse_ants,
[ant_str], {},
nwarnings=1,
message='Warning: Polarization')
ant_pairs_expected = [(1, 3), (2, 3)]
pols_expected = [-2, -3]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Multiple baselines as list
ant_str = '1_2,1_3,1_11'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 2), (1, 3), (1, 11)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Multiples baselines with polarizations as list
ant_str = '1r_2l,1l_3l,1r_11r'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 2), (1, 3), (1, 11)]
pols_expected = [-1, -2, -3]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Specific baselines with parenthesis
ant_str = '(1,3)_11'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 11), (3, 11)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Specific baselines with parenthesis
ant_str = '1_(3,11)'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 3), (1, 11)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Antenna numbers with polarizations
ant_str = '(1l,2r)_(3l,6r)'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 3), (1, 6), (2, 3), (2, 6)]
pols_expected = [-1, -2, -3, -4]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Antenna numbers with - for avoidance
ant_str = '1_(-3,11)'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 11)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Remove specific antenna number
ant_str = '1,-3'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(0, 1), (1, 2), (1, 6), (1, 7), (1, 8), (1, 11),
(1, 14), (1, 18), (1, 19), (1, 20), (1, 21),
(1, 22), (1, 23), (1, 24), (1, 26), (1, 27)]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Remove specific baseline (same expected antenna pairs as above example)
ant_str = '1,-1_3'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Antenna numbers with polarizations and - for avoidance
ant_str = '1l_(-3r,11l)'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 11)]
pols_expected = [-2]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Antenna numbers and pseudo-Stokes parameters
ant_str = '(1l,2r)_(3l,6r),pI,pq'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 3), (1, 6), (2, 3), (2, 6)]
pols_expected = [2, 1, -1, -2, -3, -4]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Multiple baselines with multiple polarizations, one pol to be removed
ant_str = '1l_2,1l_3,-1l_3r'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = [(1, 2), (1, 3)]
pols_expected = [-2]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Multiple baselines with multiple polarizations, one pol (not in data) to be removed
ant_str = '1l_2,1l_3,-1x_3y'
ant_pairs_nums, polarizations = uvtest.checkWarnings(uv.parse_ants,
[ant_str], {},
nwarnings=1,
message='Warning: Polarization')
ant_pairs_expected = [(1, 2), (1, 3)]
pols_expected = [-2, -4]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Test print toggle on single baseline with polarization
ant_str = '1l_2l'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str, print_toggle=True)
ant_pairs_expected = [(1, 2)]
pols_expected = [-2]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert Counter(polarizations) == Counter(pols_expected)
# Test ant_str='auto' on file with auto correlations
uv = UVData()
testfile = os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcA')
uv.read(testfile)
ant_str = 'auto'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_nums = [9, 10, 20, 22, 31, 43, 53, 64, 65, 72, 80, 81, 88, 89, 96, 97,
104, 105, 112]
ant_pairs_autos = [(ant_i, ant_i) for ant_i in ant_nums]
assert Counter(ant_pairs_nums) == Counter(ant_pairs_autos)
assert isinstance(polarizations, type(None))
# Test cross correlation extraction on data with auto + cross
ant_str = 'cross'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_cross = list(itertools.combinations(ant_nums, 2))
assert Counter(ant_pairs_nums) == Counter(ant_pairs_cross)
assert isinstance(polarizations, type(None))
# Remove only polarization of single baseline
ant_str = 'all,-9x_10x'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = ant_pairs_autos + ant_pairs_cross
ant_pairs_expected.remove((9, 10))
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
# Test appending all to beginning of strings that start with -
ant_str = '-9'
ant_pairs_nums, polarizations = uv.parse_ants(ant_str)
ant_pairs_expected = ant_pairs_autos + ant_pairs_cross
for ant_i in ant_nums:
ant_pairs_expected.remove((9, ant_i))
assert Counter(ant_pairs_nums) == Counter(ant_pairs_expected)
assert isinstance(polarizations, type(None))
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_select_with_ant_str():
# Test select function with ant_str argument
uv = UVData()
testfile = os.path.join(
DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
inplace = False
# Check error thrown if ant_str passed with antenna_nums,
# antenna_names, ant_pairs_nums, or polarizations
pytest.raises(ValueError, uv.select,
ant_str='',
antenna_nums=[],
inplace=inplace)
pytest.raises(ValueError, uv.select,
ant_str='',
antenna_nums=[],
inplace=inplace)
pytest.raises(ValueError, uv.select,
ant_str='',
antenna_nums=[],
inplace=inplace)
pytest.raises(ValueError, uv.select,
ant_str='',
antenna_nums=[],
inplace=inplace)
# All baselines
ant_str = 'all'
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(uv.get_antpairs())
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Auto correlations
ant_str = 'auto'
pytest.raises(ValueError, uv.select, ant_str=ant_str, inplace=inplace)
# No auto correlations in this data
# Cross correlations
ant_str = 'cross'
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(uv.get_antpairs())
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# All baselines in data are cross correlations
# pseudo-Stokes params
ant_str = 'pI,pq,pU,pv'
pytest.raises(ValueError, uv.select, ant_str=ant_str, inplace=inplace)
# Unparsible string
ant_str = 'none'
pytest.raises(ValueError, uv.select, ant_str=ant_str, inplace=inplace)
# Single antenna number
ant_str = '0'
ant_pairs = [(0, 1), (0, 2), (0, 3), (0, 6), (0, 7), (0, 8), (0, 11),
(0, 14), (0, 18), (0, 19), (0, 20), (0, 21), (0, 22),
(0, 23), (0, 24), (0, 26), (0, 27)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Single antenna number not present in data
ant_str = '10'
uv2 = uvtest.checkWarnings(uv.select, [], {'ant_str': ant_str, 'inplace': inplace},
nwarnings=1, message='Warning: Antenna')
# Multiple antenna numbers as list
ant_str = '22,26'
ant_pairs = [(0, 22), (0, 26), (1, 22), (1, 26), (2, 22), (2, 26),
(3, 22), (3, 26), (6, 22), (6, 26), (7, 22),
(7, 26), (8, 22), (8, 26), (11, 22), (11, 26),
(14, 22), (14, 26), (18, 22), (18, 26), (19, 22),
(19, 26), (20, 22), (20, 26), (21, 22), (21, 26),
(22, 23), (22, 24), (22, 26), (22, 27), (23, 26),
(24, 26), (26, 27)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Single baseline
ant_str = '1_3'
ant_pairs = [(1, 3)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Single baseline with polarization
ant_str = '1l_3r'
ant_pairs = [(1, 3)]
pols = ['lr']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Single baseline with single polarization in first entry
ant_str = '1l_3,2x_3'
# x,y pols not present in data
uv2 = uvtest.checkWarnings(uv.select, [],
{'ant_str': ant_str, 'inplace': inplace},
nwarnings=1, message='Warning: Polarization')
# with polarizations in data
ant_str = '1l_3,2_3'
ant_pairs = [(1, 3), (2, 3)]
pols = ['ll', 'lr']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Single baseline with single polarization in last entry
ant_str = '1_3l,2_3x'
# x,y pols not present in data
uv2 = uvtest.checkWarnings(uv.select, [],
{'ant_str': ant_str, 'inplace': inplace},
nwarnings=1, message='Warning: Polarization')
# with polarizations in data
ant_str = '1_3l,2_3'
ant_pairs = [(1, 3), (2, 3)]
pols = ['ll', 'rl']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Multiple baselines as list
ant_str = '1_2,1_3,1_10'
# Antenna number 10 not in data
uv2 = uvtest.checkWarnings(uv.select, [],
{'ant_str': ant_str, 'inplace': inplace},
nwarnings=1, message='Warning: Antenna')
ant_pairs = [(1, 2), (1, 3)]
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Multiples baselines with polarizations as list
ant_str = '1r_2l,1l_3l,1r_11r'
ant_pairs = [(1, 2), (1, 3), (1, 11)]
pols = ['rr', 'll', 'rl']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Specific baselines with parenthesis
ant_str = '(1,3)_11'
ant_pairs = [(1, 11), (3, 11)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Specific baselines with parenthesis
ant_str = '1_(3,11)'
ant_pairs = [(1, 3), (1, 11)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Antenna numbers with polarizations
ant_str = '(1l,2r)_(3l,6r)'
ant_pairs = [(1, 3), (1, 6), (2, 3), (2, 6)]
pols = ['rr', 'll', 'rl', 'lr']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Antenna numbers with - for avoidance
ant_str = '1_(-3,11)'
ant_pairs = [(1, 11)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
ant_str = '(-1,3)_11'
ant_pairs = [(3, 11)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Remove specific antenna number
ant_str = '1,-3'
ant_pairs = [(0, 1), (1, 2), (1, 6), (1, 7), (1, 8), (1, 11),
(1, 14), (1, 18), (1, 19), (1, 20), (1, 21),
(1, 22), (1, 23), (1, 24), (1, 26), (1, 27)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Remove specific baseline
ant_str = '1,-1_3'
ant_pairs = [(0, 1), (1, 2), (1, 6), (1, 7), (1, 8), (1, 11),
(1, 14), (1, 18), (1, 19), (1, 20), (1, 21),
(1, 22), (1, 23), (1, 24), (1, 26), (1, 27)]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Antenna numbers with polarizations and - for avoidance
ant_str = '1l_(-3r,11l)'
ant_pairs = [(1, 11)]
pols = ['ll']
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(pols)
# Test pseudo-Stokes params with select
ant_str = 'pi,pQ'
pols = ['pQ', 'pI']
uv.polarization_array = np.array([4, 3, 2, 1])
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(uv.get_antpairs())
assert Counter(uv2.get_pols()) == Counter(pols)
# Test ant_str = 'auto' on file with auto correlations
uv = UVData()
testfile = os.path.join(DATA_PATH, 'zen.2457698.40355.xx.HH.uvcA')
uv.read(testfile)
ant_str = 'auto'
ant_nums = [9, 10, 20, 22, 31, 43, 53, 64, 65, 72, 80, 81, 88, 89, 96, 97,
104, 105, 112]
ant_pairs_autos = [(ant_i, ant_i) for ant_i in ant_nums]
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs_autos)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Test cross correlation extraction on data with auto + cross
ant_str = 'cross'
ant_pairs_cross = list(itertools.combinations(ant_nums, 2))
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs_cross)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Remove only polarization of single baseline
ant_str = 'all,-9x_10x'
ant_pairs = ant_pairs_autos + ant_pairs_cross
ant_pairs.remove((9, 10))
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
# Test appending all to beginning of strings that start with -
ant_str = '-9'
ant_pairs = ant_pairs_autos + ant_pairs_cross
for ant_i in ant_nums:
ant_pairs.remove((9, ant_i))
uv2 = uv.select(ant_str=ant_str, inplace=inplace)
assert Counter(uv2.get_antpairs()) == Counter(ant_pairs)
assert Counter(uv2.get_pols()) == Counter(uv.get_pols())
def test_set_uvws_from_antenna_pos():
# Test set_uvws_from_antenna_positions function with phased data
uv_object = UVData()
testfile = os.path.join(
DATA_PATH, '1133866760.uvfits')
uv_object.read_uvfits(testfile)
orig_uvw_array = np.copy(uv_object.uvw_array)
with pytest.raises(ValueError) as cm:
uv_object.set_uvws_from_antenna_positions()
assert str(cm.value).startswith("UVW calculation requires unphased data.")
with pytest.raises(ValueError) as cm:
uvtest.checkWarnings(
uv_object.set_uvws_from_antenna_positions,
[True, "xyz"],
message="Data will be unphased"
)
assert str(cm.value).startswith("Invalid parameter orig_phase_frame.")
with pytest.raises(ValueError) as cm:
uvtest.checkWarnings(
uv_object.set_uvws_from_antenna_positions,
[True, "gcrs", "xyz"],
message="Data will be unphased"
)
assert str(cm.value).startswith("Invalid parameter output_phase_frame.")
uvtest.checkWarnings(
uv_object.set_uvws_from_antenna_positions,
[True, 'gcrs', 'gcrs'],
message='Data will be unphased'
)
max_diff = np.amax(np.absolute(np.subtract(orig_uvw_array,
uv_object.uvw_array)))
assert np.isclose(max_diff, 0., atol=2)
def test_deprecated_redundancy_funcs():
uv0 = UVData()
uv0.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
redant_gps, centers, lengths = uvtest.checkWarnings(
uv0.get_antenna_redundancies,
func_kwargs={'include_autos': False, 'conjugate_bls': True},
category=DeprecationWarning,
message=['UVData.get_antenna_redundancies has been replaced'])
redbl_gps, centers, lengths, _ = uvtest.checkWarnings(
uv0.get_baseline_redundancies, category=DeprecationWarning,
message='UVData.get_baseline_redundancies has been replaced')
red_gps_new, _, _, = uv0.get_redundancies(include_autos=False, use_antpos=True)
assert red_gps_new == redant_gps
def test_get_antenna_redundancies():
uv0 = UVData()
uv0.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
old_bl_array = np.copy(uv0.baseline_array)
red_gps, centers, lengths = uv0.get_redundancies(use_antpos=True, include_autos=False, conjugate_bls=True)
# new and old baseline Numbers are not the same (different conjugation)
assert not np.allclose(uv0.baseline_array, old_bl_array)
# assert all baselines are in the data (because it's conjugated to match)
for i, gp in enumerate(red_gps):
for bl in gp:
assert bl in uv0.baseline_array
# conjugate data differently
uv0.conjugate_bls(convention='ant1<ant2')
new_red_gps, new_centers, new_lengths, conjs = uv0.get_redundancies(use_antpos=True,
include_autos=False,
include_conjugates=True)
assert conjs is None
apos, anums = uv0.get_ENU_antpos()
new_red_gps, new_centers, new_lengths = uvutils.get_antenna_redundancies(
anums, apos, include_autos=False)
# all redundancy info is the same
assert red_gps == new_red_gps
assert np.allclose(centers, new_centers)
assert np.allclose(lengths, new_lengths)
def test_redundancy_contract_expand():
# Test that a UVData object can be reduced to one baseline from each redundant group
# and restored to its original form.
uv0 = UVData()
uv0.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
tol = 0.02 # Fails at lower precision because some baselines fall into multiple redundant groups
# Assign identical data to each redundant group:
red_gps, centers, lengths = uv0.get_redundancies(tol=tol, use_antpos=True, conjugate_bls=True)
for i, gp in enumerate(red_gps):
for bl in gp:
inds = np.where(bl == uv0.baseline_array)
uv0.data_array[inds] *= 0
uv0.data_array[inds] += complex(i)
uv2 = uv0.compress_by_redundancy(tol=tol, inplace=False)
# Compare in-place to separated compression.
uv3 = copy.deepcopy(uv0)
uv3.compress_by_redundancy(tol=tol)
assert uv2 == uv3
# check inflating gets back to the original
uvtest.checkWarnings(
uv2.inflate_by_redundancy,
[tol],
message=['Missing some redundant groups. Filling in available data.']
)
uv2.history = uv0.history
# Inflation changes the baseline ordering into the order of the redundant groups.
# reorder bls for comparison
uv0.reorder_blts(conj_convention='u>0')
uv2.reorder_blts(conj_convention='u>0')
uv2._uvw_array.tols = [0, tol]
assert uv2 == uv0
uv3 = uv2.compress_by_redundancy(tol=tol, inplace=False)
uvtest.checkWarnings(
uv3.inflate_by_redundancy,
[tol],
message=['Missing some redundant groups. Filling in available data.']
)
# Confirm that we get the same result looping inflate -> compress -> inflate.
uv3.reorder_blts(conj_convention='u>0')
uv2.reorder_blts(conj_convention='u>0')
uv2.history = uv3.history
assert uv2 == uv3
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_redundancy_contract_expand_nblts_not_nbls_times_ntimes():
uv0 = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv0.read_uvfits(testfile)
# check that Nblts != Nbls * Ntimes
assert uv0.Nblts != uv0.Nbls * uv0.Ntimes
tol = 1.0
# Assign identical data to each redundant group:
red_gps, centers, lengths = uv0.get_redundancies(tol=tol, use_antpos=True, conjugate_bls=True)
for i, gp in enumerate(red_gps):
for bl in gp:
inds = np.where(bl == uv0.baseline_array)
uv0.data_array[inds, ...] *= 0
uv0.data_array[inds, ...] += complex(i)
uv2 = uv0.compress_by_redundancy(tol=tol, inplace=False)
# check inflating gets back to the original
uvtest.checkWarnings(uv2.inflate_by_redundancy, {tol: tol},
message=['Missing some redundant groups. Filling in available data.'])
uv2.history = uv0.history
# Inflation changes the baseline ordering into the order of the redundant groups.
# reorder bls for comparison
uv0.reorder_blts()
uv2.reorder_blts()
uv2._uvw_array.tols = [0, tol]
blt_inds = []
missing_inds = []
for bl, t in zip(uv0.baseline_array, uv0.time_array):
if (bl, t) in zip(uv2.baseline_array, uv2.time_array):
this_ind = np.where((uv2.baseline_array == bl) & (uv2.time_array == t))[0]
blt_inds.append(this_ind[0])
else:
# this is missing because of the compress_by_redundancy step
missing_inds.append(np.where((uv0.baseline_array == bl) & (uv0.time_array == t))[0])
uv3 = uv2.select(blt_inds=blt_inds, inplace=False)
orig_inds_keep = list(np.arange(uv0.Nblts))
for ind in missing_inds:
orig_inds_keep.remove(ind)
uv1 = uv0.select(blt_inds=orig_inds_keep, inplace=False)
assert uv3 == uv1
def test_compress_redundancy_metadata_only():
uv0 = UVData()
uv0.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
tol = 0.05
# Assign identical data to each redundant group:
red_gps, centers, lengths = uv0.get_redundancies(tol=tol, use_antpos=True, conjugate_bls=True)
for i, gp in enumerate(red_gps):
for bl in gp:
inds = np.where(bl == uv0.baseline_array)
uv0.data_array[inds] *= 0
uv0.data_array[inds] += complex(i)
uv2 = copy.deepcopy(uv0)
uv2.data_array = None
uv2.flag_array = None
uv2.nsample_array = None
uv2.compress_by_redundancy(tol=tol, inplace=True)
# check for deprecation warning with metadata_only keyword
uv1 = copy.deepcopy(uv0)
uv1.data_array = None
uv1.flag_array = None
uv1.nsample_array = None
uvtest.checkWarnings(uv1.compress_by_redundancy,
func_kwargs={'tol': tol, 'inplace': True,
'metadata_only': True},
category=DeprecationWarning,
message='The metadata_only option has been replaced')
assert uv1 == uv2
uv0.compress_by_redundancy(tol=tol)
uv0.data_array = None
uv0.flag_array = None
uv0.nsample_array = None
assert uv0 == uv2
def test_redundancy_missing_groups():
# Check that if I try to inflate a compressed UVData that is missing redundant groups, it will
# raise the right warnings and fill only what data are available.
uv0 = UVData()
uv0.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
tol = 0.02
Nselect = 19
uv0.compress_by_redundancy(tol=tol)
fname = 'temp_hera19_missingreds.uvfits'
bls = np.unique(uv0.baseline_array)[:Nselect] # First twenty baseline groups
uv0.select(bls=[uv0.baseline_to_antnums(bl) for bl in bls])
uv0.write_uvfits(fname)
uv1 = UVData()
uv1.read_uvfits(fname)
os.remove(fname)
assert uv0 == uv1 # Check that writing compressed files causes no issues.
uvtest.checkWarnings(
uv1.inflate_by_redundancy,
[tol],
message=['Missing some redundant groups. Filling in available data.']
)
uv2 = uv1.compress_by_redundancy(tol=tol, inplace=False)
assert np.unique(uv2.baseline_array).size == Nselect
def test_quick_redundant_vs_redundant_test_array():
"""Verify the quick redundancy calc returns the same groups as a known array."""
uv = UVData()
uv.read_uvfits(os.path.join(DATA_PATH, 'fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits'))
uv.select(times=uv.time_array[0])
uv.unphase_to_drift()
uv.conjugate_bls(convention='u>0', use_enu=True)
tol = 0.05
# a quick and dirty redundancy calculation
unique_bls, baseline_inds = np.unique(uv.baseline_array, return_index=True)
uvw_vectors = np.take(uv.uvw_array, baseline_inds, axis=0)
uvw_diffs = np.expand_dims(uvw_vectors, axis=0) - np.expand_dims(uvw_vectors, axis=1)
uvw_diffs = np.linalg.norm(uvw_diffs, axis=2)
reds = np.where(uvw_diffs < tol, unique_bls, 0)
reds = np.ma.masked_where(reds == 0, reds)
groups = []
for bl in reds:
grp = []
grp.extend(bl.compressed())
for other_bls in reds:
if set(reds.compressed()).issubset(other_bls.compressed()):
grp.extend(other_bls.compressed())
grp = np.unique(grp).tolist()
groups.append(grp)
pad = len(max(groups, key=len))
groups = np.array([i + [-1] * (pad - len(i)) for i in groups])
groups = np.unique(groups, axis=0)
groups = [[bl for bl in grp if bl != -1] for grp in groups]
groups.sort(key=len)
redundant_groups, centers, lengths, conj_inds = uv.get_redundancies(tol=tol, include_conjugates=True)
redundant_groups.sort(key=len)
assert groups == redundant_groups
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_redundancy_finder_when_nblts_not_nbls_times_ntimes():
"""Test the redundancy finder functions when Nblts != Nbls * Ntimes."""
tol = 1 # meter
uv = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
uv.conjugate_bls(convention='u>0', use_enu=True)
# check that Nblts != Nbls * Ntimes
assert uv.Nblts != uv.Nbls * uv.Ntimes
# a quick and dirty redundancy calculation
unique_bls, baseline_inds = np.unique(uv.baseline_array, return_index=True)
uvw_vectors = np.take(uv.uvw_array, baseline_inds, axis=0)
uvw_diffs = np.expand_dims(uvw_vectors, axis=0) - np.expand_dims(uvw_vectors, axis=1)
uvw_diffs = np.linalg.norm(uvw_diffs, axis=2)
reds = np.where(uvw_diffs < tol, unique_bls, 0)
reds = np.ma.masked_where(reds == 0, reds)
groups = []
for bl in reds:
grp = []
grp.extend(bl.compressed())
for other_bls in reds:
if set(reds.compressed()).issubset(other_bls.compressed()):
grp.extend(other_bls.compressed())
grp = np.unique(grp).tolist()
groups.append(grp)
pad = len(max(groups, key=len))
groups = np.array([i + [-1] * (pad - len(i)) for i in groups])
groups = np.unique(groups, axis=0)
groups = [[bl for bl in grp if bl != -1] for grp in groups]
groups.sort(key=len)
redundant_groups, centers, lengths, conj_inds = uv.get_redundancies(tol=tol, include_conjugates=True)
redundant_groups.sort(key=len)
assert groups == redundant_groups
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_overlapping_data_add():
# read in test data
uv = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv.read_uvfits(testfile)
# slice into four objects
blts1 = np.arange(500)
blts2 = np.arange(500, 1360)
uv1 = uv.select(polarizations=[-1, -2], blt_inds=blts1, inplace=False)
uv2 = uv.select(polarizations=[-3, -4], blt_inds=blts1, inplace=False)
uv3 = uv.select(polarizations=[-1, -2], blt_inds=blts2, inplace=False)
uv4 = uv.select(polarizations=[-3, -4], blt_inds=blts2, inplace=False)
# combine and check for equality
uvfull = uv1 + uv2
uvfull += uv3
uvfull += uv4
extra_history = ("Downselected to specific baseline-times, polarizations using pyuvdata. "
"Combined data along polarization axis using pyuvdata. Combined data along "
"baseline-time axis using pyuvdata. Overwrote invalid data using pyuvdata.")
assert uvutils._check_histories(uvfull.history, uv.history + extra_history)
uvfull.history = uv.history # make histories match
assert uv == uvfull
# check combination not-in-place
uvfull = uv1 + uv2
uvfull += uv3
uvfull = uvfull + uv4
uvfull.history = uv.history # make histories match
assert uv == uvfull
# test raising error for adding objects incorrectly (i.e., having the object
# with data to be overwritten come second)
uvfull = uv1 + uv2
uvfull += uv3
pytest.raises(ValueError, uv4.__iadd__, uvfull)
pytest.raises(ValueError, uv4.__add__, uv4, uvfull)
# write individual objects out, and make sure that we can read in the list
uv1_out = os.path.join(DATA_PATH, "uv1.uvfits")
uv1.write_uvfits(uv1_out)
uv2_out = os.path.join(DATA_PATH, "uv2.uvfits")
uv2.write_uvfits(uv2_out)
uv3_out = os.path.join(DATA_PATH, "uv3.uvfits")
uv3.write_uvfits(uv3_out)
uv4_out = os.path.join(DATA_PATH, "uv4.uvfits")
uv4.write_uvfits(uv4_out)
uvfull = UVData()
uvfull.read(np.array([uv1_out, uv2_out, uv3_out, uv4_out]))
assert uvutils._check_histories(uvfull.history, uv.history + extra_history)
uvfull.history = uv.history # make histories match
assert uvfull == uv
# clean up after ourselves
os.remove(uv1_out)
os.remove(uv2_out)
os.remove(uv3_out)
os.remove(uv4_out)
return
@pytest.mark.filterwarnings("ignore:Altitude is not present in Miriad file")
def test_lsts_from_time_with_only_unique():
"""Test `set_lsts_from_time_array` with only unique values is identical to full array."""
miriad_file = os.path.join(DATA_PATH, 'zen.2456865.60537.xy.uvcRREAA')
uv = UVData()
uv.read_miriad(miriad_file)
lat, lon, alt = uv.telescope_location_lat_lon_alt_degrees
# calculate the lsts for all elements in time array
full_lsts = uvutils.get_lst_for_time(uv.time_array, lat, lon, alt)
# use `set_lst_from_time_array` to set the uv.lst_array using only unique values
uv.set_lsts_from_time_array()
assert np.array_equal(full_lsts, uv.lst_array)
@pytest.mark.filterwarnings("ignore:Telescope EVLA is not")
def test_copy():
"""Test the copy method"""
uv_object = UVData()
testfile = os.path.join(DATA_PATH, 'day2_TDEM0003_10s_norx_1src_1spw.uvfits')
uv_object.read_uvfits(testfile)
uv_object_copy = uv_object.copy()
assert uv_object_copy == uv_object
uv_object_copy = uv_object.copy(metadata_only=True)
assert uv_object_copy.metadata_only
for name in uv_object._data_params:
setattr(uv_object, name, None)
assert uv_object_copy == uv_object
uv_object_copy = uv_object.copy()
assert uv_object_copy == uv_object
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time(resample_in_time_file):
"""Test the upsample_in_time method"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.allclose(uv_object.integration_time, max_integration_time)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be the same
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0], out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_with_flags(resample_in_time_file):
"""Test the upsample_in_time method with flags"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) / 2.0
# add flags and upsample again
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[0], 0, 0, 0] = True
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
# data and nsamples should be changed as normal, but flagged
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0], out_wf[0, 0, 0])
out_flags = uv_object.get_flags(0, 1)
assert np.all(out_flags[:2, 0, 0])
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_noninteger_resampling(resample_in_time_file):
"""Test the upsample_in_time method with a non-integer resampling factor"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) * 0.75
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.allclose(uv_object.integration_time, max_integration_time * 0.5 / 0.75)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be different by a factor of 2
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0], out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
def test_upsample_in_time_errors(resample_in_time_file):
"""Test errors and warnings raised by upsample_in_time"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# test using a too-small integration time
max_integration_time = 1e-3 * np.amin(uv_object.integration_time)
with pytest.raises(ValueError) as cm:
uv_object.upsample_in_time(max_integration_time)
assert str(cm.value).startswith("Decreasing the integration time by more than")
# catch a warning for doing no work
uv_object2 = uv_object.copy()
max_integration_time = 2 * np.amax(uv_object.integration_time)
uvtest.checkWarnings(uv_object.upsample_in_time, [max_integration_time],
message="All values in integration_time array are already shorter")
assert uv_object == uv_object2
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_summing_correlator_mode(resample_in_time_file):
"""Test the upsample_in_time method with summing correlator mode"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline",
summing_correlator_mode=True)
assert np.allclose(uv_object.integration_time, max_integration_time)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be the half the input
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0] / 2, out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_summing_correlator_mode_with_flags(resample_in_time_file):
"""Test the upsample_in_time method with summing correlator mode and flags"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# add flags and upsample again
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[0], 0, 0, 0] = True
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline",
summing_correlator_mode=True)
# data and nsamples should be changed as normal, but flagged
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0] / 2, out_wf[0, 0, 0])
out_flags = uv_object.get_flags(0, 1)
assert np.all(out_flags[:2, 0, 0])
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_summing_correlator_mode_nonint_resampling(resample_in_time_file):
"""Test the upsample_in_time method with summing correlator mode
and non-integer resampling
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# try again with a non-integer resampling factor
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) * 0.75
uv_object.upsample_in_time(max_integration_time, blt_order="baseline",
summing_correlator_mode=True)
assert np.allclose(uv_object.integration_time, max_integration_time * 0.5 / 0.75)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be half the input
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[0, 0, 0] / 2, out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_partial_upsample_in_time(resample_in_time_file):
"""Test the upsample_in_time method with non-uniform upsampling"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# change a whole baseline's integration time
bl_inds = uv_object.antpair2ind(0, 1)
uv_object.integration_time[bl_inds] = uv_object.integration_time[0] / 2.0
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_wf_01 = uv_object.get_data(0, 1)
init_wf_02 = uv_object.get_data(0, 2)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns_01 = uv_object.get_nsamples(0, 1)
init_ns_02 = uv_object.get_nsamples(0, 2)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time)
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.allclose(uv_object.integration_time, max_integration_time)
# output data should be the same
out_wf_01 = uv_object.get_data(0, 1)
out_wf_02 = uv_object.get_data(0, 2)
assert np.all(init_wf_01 == out_wf_01)
assert np.isclose(init_wf_02[0, 0, 0], out_wf_02[0, 0, 0])
assert init_wf_02.size * 2 == out_wf_02.size
# this should be true because there are no flags
out_ns_01 = uv_object.get_nsamples(0, 1)
out_ns_02 = uv_object.get_nsamples(0, 2)
assert np.allclose(out_ns_01, init_ns_01)
assert np.isclose(init_ns_02[0, 0, 0], out_ns_02[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_drift(resample_in_time_file):
"""Test the upsample_in_time method on drift mode data"""
uv_object = resample_in_time_file
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(
max_integration_time, blt_order="baseline", allow_drift=True
)
assert np.allclose(uv_object.integration_time, max_integration_time)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be the same
out_wf = uv_object.get_data(0, 1)
# we need a "large" tolerance given the "large" data
new_tol = 1e-2 * np.amax(np.abs(uv_object.data_array))
assert np.isclose(init_wf[0, 0, 0], out_wf[0, 0, 0], atol=new_tol)
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_in_time_drift_no_phasing(resample_in_time_file):
"""Test the upsample_in_time method on drift mode data without phasing"""
uv_object = resample_in_time_file
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
max_integration_time = np.amin(uv_object.integration_time) / 2.0
# upsample with allow_drift=False
uv_object.upsample_in_time(
max_integration_time, blt_order="baseline", allow_drift=False
)
assert np.allclose(uv_object.integration_time, max_integration_time)
# we should double the size of the data arrays
assert uv_object.data_array.size == 2 * init_data_size
# output data should be similar, but somewhat different because of the phasing
out_wf = uv_object.get_data(0, 1)
# we need a "large" tolerance given the "large" data
new_tol = 1e-2 * np.amax(np.abs(uv_object.data_array))
assert np.isclose(init_wf[0, 0, 0], out_wf[0, 0, 0], atol=new_tol)
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(init_ns[0, 0, 0], out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time(resample_in_time_file):
"""Test the downsample_in_time method"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time")
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_partial_flags(resample_in_time_file):
"""Test the downsample_in_time method with partial flagging"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
# add flags and try again. With one of the 2 inputs flagged, the data should
# just be the unflagged value and nsample should be half the unflagged one
# and the output should not be flagged.
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[0], 0, 0, 0] = True
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time")
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[1, 0, 0], out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that there are still no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_totally_flagged(resample_in_time_file):
"""Test the downsample_in_time method with totally flagged integrations"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
# add more flags and try again. When all the input points are flagged,
# data and nsample should have the same results as no flags but the output
# should be flagged
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[:2], 0, 0, 0] = True
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time")
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that the new sample is flagged
out_flag = uv_object.get_flags(0, 1)
assert out_flag[0, 0, 0]
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_uneven_samples(resample_in_time_file):
"""Test the downsample_in_time method with uneven downsampling"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
# test again with a downsample factor that doesn't go evenly into the number of samples
min_integration_time = original_int_time * 3.0
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time", keep_ragged=False)
# Only some baselines have an even number of times, so the output integration time
# is not uniformly the same. For the test case, we'll have *either* the original
# integration time or twice that.
assert np.all(
np.logical_or(
np.isclose(uv_object.integration_time, original_int_time),
np.isclose(uv_object.integration_time, min_integration_time)
)
)
# as usual, the new data should be the average of the input data (3 points now)
out_wf = uv_object.get_data(0, 1)
assert np.isclose(np.mean(init_wf[0:3, 0, 0]), out_wf[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_uneven_samples_discard_ragged(resample_in_time_file):
"""Test the downsample_in_time method with uneven downsampling and
discarding the ragged samples.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
# test again with a downsample factor that doesn't go evenly into the number of samples
min_integration_time = original_int_time * 3.0
# test again with keep_ragged=False
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time", keep_ragged=False)
# make sure integration time is correct
# in this case, all integration times should be the target one
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
# as usual, the new data should be the average of the input data
out_wf = uv_object.get_data(0, 1)
assert np.isclose(np.mean(init_wf[0:3, 0, 0]), out_wf[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_summing_correlator_mode(resample_in_time_file):
"""Test the downsample_in_time method with summing correlator mode"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time", summing_correlator_mode=True)
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be the sum
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]), out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_summing_correlator_mode_partial_flags(
resample_in_time_file
):
"""Test the downsample_in_time method with summing correlator mode and
partial flags
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
# add flags and try again. With one of the 2 inputs flagged, the data should
# just be the unflagged value and nsample should be half the unflagged one
# and the output should not be flagged.
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[0], 0, 0, 0] = True
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time", summing_correlator_mode=True)
out_wf = uv_object.get_data(0, 1)
assert np.isclose(init_wf[1, 0, 0], out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that there are still no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_summing_correlator_mode_totally_flagged(
resample_in_time_file
):
"""Test the downsample_in_time method with summing correlator mode and
totally flagged integrations.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
# add more flags and try again. When all the input points are flagged,
# data and nsample should have the same results as no flags but the output
# should be flagged
inds01 = uv_object.antpair2ind(0, 1)
uv_object.flag_array[inds01[:2], 0, 0, 0] = True
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
minor_order="time", summing_correlator_mode=True)
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]), out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that the new sample is flagged
out_flag = uv_object.get_flags(0, 1)
assert out_flag[0, 0, 0]
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_summing_correlator_mode_uneven_samples(
resample_in_time_file
):
"""Test the downsample_in_time method with summing correlator mode and
uneven samples.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# test again with a downsample factor that doesn't go evenly into the number of samples
min_integration_time = original_int_time * 3.0
uv_object.downsample_in_time(
min_integration_time,
blt_order="baseline",
minor_order="time",
keep_ragged=False,
summing_correlator_mode=True,
)
# Only some baselines have an even number of times, so the output integration time
# is not uniformly the same. For the test case, we'll have *either* the original
# integration time or twice that.
assert np.all(
np.logical_or(
np.isclose(uv_object.integration_time, original_int_time),
np.isclose(uv_object.integration_time, min_integration_time)
)
)
# as usual, the new data should be the average of the input data (3 points now)
out_wf = uv_object.get_data(0, 1)
assert np.isclose(np.sum(init_wf[0:3, 0, 0]), out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(np.mean(init_ns[0:3, 0, 0]), out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_summing_correlator_mode_uneven_samples_drop_ragged(
resample_in_time_file
):
"""Test the downsample_in_time method with summing correlator mode and
uneven samples, dropping ragged ones.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# test again with keep_ragged=False
min_integration_time = original_int_time * 3.0
uv_object.downsample_in_time(
min_integration_time,
blt_order="baseline",
minor_order="time",
keep_ragged=False,
summing_correlator_mode=True,
)
# make sure integration time is correct
# in this case, all integration times should be the target one
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
# as usual, the new data should be the average of the input data
out_wf = uv_object.get_data(0, 1)
assert np.isclose(np.sum(init_wf[0:3, 0, 0]), out_wf[0, 0, 0])
# make sure nsamples is correct
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose(np.mean(init_ns[0:3, 0, 0]), out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_partial_downsample_in_time(resample_in_time_file):
"""Test the downsample_in_time method without uniform downsampling"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# change a whole baseline's integration time
bl_inds = uv_object.antpair2ind(0, 1)
uv_object.integration_time[bl_inds] = uv_object.integration_time[0] * 2.0
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline")
# save some values for later
init_wf_01 = uv_object.get_data(0, 1)
init_wf_02 = uv_object.get_data(0, 2)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns_01 = uv_object.get_nsamples(0, 1)
init_ns_02 = uv_object.get_nsamples(0, 2)
# change the target integration time
min_integration_time = np.amax(uv_object.integration_time)
uv_object.downsample_in_time(min_integration_time, blt_order="baseline")
# Should have all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
# output data should be the same
out_wf_01 = uv_object.get_data(0, 1)
out_wf_02 = uv_object.get_data(0, 2)
assert np.all(init_wf_01 == out_wf_01)
assert np.isclose((init_wf_02[0, 0, 0] + init_wf_02[1, 0, 0]) / 2.,
out_wf_02[0, 0, 0])
# this should be true because there are no flags
out_ns_01 = uv_object.get_nsamples(0, 1)
out_ns_02 = uv_object.get_nsamples(0, 2)
assert np.allclose(out_ns_01, init_ns_01)
assert np.isclose((init_ns_02[0, 0, 0] + init_ns_02[1, 0, 0]) / 2.0,
out_ns_02[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_drift(resample_in_time_file):
"""Test the downsample_in_time method on drift mode data"""
uv_object = resample_in_time_file
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
uv_object.downsample_in_time(min_integration_time, blt_order="baseline",
allow_drift=True)
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_downsample_in_time_drift_no_phasing(resample_in_time_file):
"""Test the downsample_in_time method on drift mode data without phasing"""
uv_object = resample_in_time_file
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
original_int_time = np.amax(uv_object.integration_time)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the target integration time
min_integration_time = original_int_time * 2.0
# try again with allow_drift=False
uv_object.downsample_in_time(
min_integration_time, blt_order="baseline", allow_drift=False,
)
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be similar to the average, but somewhat different
# because of the phasing
out_wf = uv_object.get_data(0, 1)
new_tol = 5e-2 * np.amax(np.abs(uv_object.data_array))
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2.,
out_wf[0, 0, 0], atol=new_tol)
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
return
def test_downsample_in_time_errors(resample_in_time_file):
"""Test various errors and warnings are raised"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# raise an error for a too-large integration time
max_integration_time = 1e3 * np.amax(uv_object.integration_time)
with pytest.raises(ValueError) as cm:
uv_object.downsample_in_time(max_integration_time)
assert str(cm.value).startswith("Increasing the integration time by more than")
# catch a warning for doing no work
uv_object2 = uv_object.copy()
max_integration_time = 0.5 * np.amin(uv_object.integration_time)
uvtest.checkWarnings(uv_object.downsample_in_time, [max_integration_time],
message="All values in the integration_time array are "
"already longer")
assert uv_object == uv_object2
del uv_object2
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# make a gap in the times to check a warning about that
inds01 = uv_object.antpair2ind(0, 1)
initial_int_time = uv_object.integration_time[inds01[0]]
# time array is in jd, integration time is in sec
uv_object.time_array[inds01[-1]] += initial_int_time / (24 * 3600)
uv_object.Ntimes += 1
min_integration_time = 2 * np.amin(uv_object.integration_time)
uvtest.checkWarnings(uv_object.downsample_in_time, [min_integration_time],
message=["There is a gap in the times of baseline (0, 1)"])
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
def test_downsample_in_time_int_time_mismatch_warning(resample_in_time_file):
"""Test warning in downsample_in_time about mismatch between integration
times and the time between integrations.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_data_size = uv_object.data_array.size
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# change the integration times to catch a warning about integration times
# not matching the time delta between integrations
uv_object.integration_time *= 0.5
min_integration_time = 2 * np.amin(uv_object.integration_time)
uvtest.checkWarnings(uv_object.downsample_in_time, [min_integration_time],
message=["The time difference between integrations is "
"not the same"],
nwarnings=10)
# Should have half the size of the data array and all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
assert uv_object.data_array.size * 2 == init_data_size
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
def test_downsample_in_time_varying_integration_time(resample_in_time_file):
"""Test downsample_in_time handling of file with integration time changing
within a baseline
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# test handling (& warnings) with varying integration time in a baseline
# First, change both integration time & time array to match
inds01 = uv_object.antpair2ind(0, 1)
initial_int_time = uv_object.integration_time[inds01[0]]
# time array is in jd, integration time is in sec
uv_object.time_array[inds01[-2]] += (initial_int_time / 2) / (24 * 3600)
uv_object.time_array[inds01[-1]] += (3 * initial_int_time / 2) / (24 * 3600)
uv_object.integration_time[inds01[-2:]] += initial_int_time
uv_object.Ntimes = np.unique(uv_object.time_array).size
min_integration_time = 2 * np.amin(uv_object.integration_time)
uvtest.checkWarnings(uv_object.downsample_in_time, [min_integration_time],
nwarnings=0)
# Should have all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
def test_downsample_in_time_varying_integration_time_warning(resample_in_time_file):
"""Test downsample_in_time handling of file with integration time changing
within a baseline, but without adjusting the time_array so there is a mismatch.
"""
uv_object = resample_in_time_file
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
# save some values for later
init_wf = uv_object.get_data(0, 1)
# check that there are no flags
assert np.nonzero(uv_object.flag_array)[0].size == 0
init_ns = uv_object.get_nsamples(0, 1)
# Next, change just integration time, so time array doesn't match
inds01 = uv_object.antpair2ind(0, 1)
initial_int_time = uv_object.integration_time[inds01[0]]
uv_object.integration_time[inds01[-2:]] += initial_int_time
min_integration_time = 2 * np.amin(uv_object.integration_time)
uvtest.checkWarnings(uv_object.downsample_in_time, [min_integration_time],
message="The time difference between integrations is "
"different than")
# Should have all the new integration time
# (for this file with 20 integrations and a factor of 2 downsampling)
assert np.all(np.isclose(uv_object.integration_time, min_integration_time))
# output data should be the average
out_wf = uv_object.get_data(0, 1)
assert np.isclose((init_wf[0, 0, 0] + init_wf[1, 0, 0]) / 2., out_wf[0, 0, 0])
# this should be true because there are no flags
out_ns = uv_object.get_nsamples(0, 1)
assert np.isclose((init_ns[0, 0, 0] + init_ns[1, 0, 0]) / 2., out_ns[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
@pytest.mark.filterwarnings("ignore:Data will be unphased and rephased")
def test_upsample_downsample_in_time(resample_in_time_file):
"""Test round trip works"""
uv_object = resample_in_time_file
# set uvws from antenna positions so they'll agree later.
# the fact that this is required is a bit concerning, it means that
# our calculated uvws from the antenna positions do not match what's in the file
uv_object.set_uvws_from_antenna_positions()
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
uv_object2 = uv_object.copy()
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.amax(uv_object.integration_time) <= max_integration_time
new_Nblts = uv_object.Nblts
# check that calling upsample again with the same max_integration_time
# gives warning and does nothing
uvtest.checkWarnings(uv_object.upsample_in_time, func_args=[max_integration_time],
func_kwargs={'blt_order': "baseline"},
message='All values in the integration_time array are '
'already longer')
assert uv_object.Nblts == new_Nblts
# check that calling upsample again with the almost the same max_integration_time
# gives warning and does nothing
small_number = 0.9 * uv_object._integration_time.tols[1]
uvtest.checkWarnings(uv_object.upsample_in_time,
func_args=[max_integration_time - small_number],
func_kwargs={'blt_order': "baseline"},
message='All values in the integration_time array are '
'already longer')
assert uv_object.Nblts == new_Nblts
uv_object.downsample_in_time(np.amin(uv_object2.integration_time), blt_order="baseline")
# increase tolerance on LST if iers.conf.auto_max_age is set to None, as we
# do in testing if the iers url is down. See conftest.py for more info.
if iers.conf.auto_max_age is None:
uv_object._lst_array.tols = (0, 1e-4)
# make sure that history is correct
assert "Upsampled data to 0.939524 second integration time using pyuvdata." in uv_object.history
assert "Downsampled data to 1.879048 second integration time using pyuvdata." in uv_object.history
# overwrite history and check for equality
uv_object.history = uv_object2.history
assert uv_object == uv_object2
# check that calling downsample again with the same min_integration_time
# gives warning and does nothing
uvtest.checkWarnings(uv_object.downsample_in_time,
func_args=[np.amin(uv_object2.integration_time)],
func_kwargs={'blt_order': "baseline"},
message='All values in the integration_time array are '
'already shorter')
assert uv_object.Nblts == uv_object2.Nblts
# check that calling upsample again with the almost the same min_integration_time
# gives warning and does nothing
uvtest.checkWarnings(uv_object.downsample_in_time,
func_args=[np.amin(uv_object2.integration_time) + small_number],
func_kwargs={'blt_order': "baseline"},
message='All values in the integration_time array are '
'already shorter')
assert uv_object.Nblts == uv_object2.Nblts
return
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
@pytest.mark.filterwarnings("ignore:Data will be unphased and rephased")
@pytest.mark.filterwarnings("ignore:There is a gap in the times of baseline")
def test_upsample_downsample_in_time_odd_resample(resample_in_time_file):
"""Test round trip works with odd resampling"""
uv_object = resample_in_time_file
# set uvws from antenna positions so they'll agree later.
# the fact that this is required is a bit concerning, it means that
# our calculated uvws from the antenna positions do not match what's in the file
uv_object.set_uvws_from_antenna_positions()
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
uv_object2 = uv_object.copy()
# try again with a resampling factor of 3 (test odd numbers)
max_integration_time = np.amin(uv_object.integration_time) / 3.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.amax(uv_object.integration_time) <= max_integration_time
uv_object.downsample_in_time(np.amin(uv_object2.integration_time), blt_order="baseline")
# increase tolerance on LST if iers.conf.auto_max_age is set to None, as we
# do in testing if the iers url is down. See conftest.py for more info.
if iers.conf.auto_max_age is None:
uv_object._lst_array.tols = (0, 1e-4)
# make sure that history is correct
assert "Upsampled data to 0.626349 second integration time using pyuvdata." in uv_object.history
assert "Downsampled data to 1.879048 second integration time using pyuvdata." in uv_object.history
# overwrite history and check for equality
uv_object.history = uv_object2.history
assert uv_object == uv_object2
@pytest.mark.filterwarnings("ignore:The xyz array in ENU_from_ECEF")
@pytest.mark.filterwarnings("ignore:The enu array in ECEF_from_ENU")
def test_upsample_downsample_in_time_metadata_only(resample_in_time_file):
"""Test round trip works with metadata-only objects"""
uv_object = resample_in_time_file
# drop the data arrays
uv_object.data_array = None
uv_object.flag_array = None
uv_object.nsample_array = None
# set uvws from antenna positions so they'll agree later.
# the fact that this is required is a bit concerning, it means that
# our calculated uvws from the antenna positions do not match what's in the file
uv_object.set_uvws_from_antenna_positions()
uv_object.phase_to_time(Time(uv_object.time_array[0], format="jd"))
# reorder to make sure we get the right value later
uv_object.reorder_blts(order="baseline", minor_order="time")
uv_object2 = uv_object.copy()
max_integration_time = np.amin(uv_object.integration_time) / 2.0
uv_object.upsample_in_time(max_integration_time, blt_order="baseline")
assert np.amax(uv_object.integration_time) <= max_integration_time
uv_object.downsample_in_time(np.amin(uv_object2.integration_time), blt_order="baseline")
# increase tolerance on LST if iers.conf.auto_max_age is set to None, as we
# do in testing if the iers url is down. See conftest.py for more info.
if iers.conf.auto_max_age is None:
uv_object._lst_array.tols = (0, 1e-4)
# make sure that history is correct
assert "Upsampled data to 0.939524 second integration time using pyuvdata." in uv_object.history
assert "Downsampled data to 1.879048 second integration time using pyuvdata." in uv_object.history
# overwrite history and check for equality
uv_object.history = uv_object2.history
assert uv_object == uv_object2
@pytest.mark.filterwarnings("ignore:Telescope mock-HERA is not in known_telescopes")
@pytest.mark.filterwarnings("ignore:There is a gap in the times of baseline")
def test_resample_in_time(bda_test_file):
"""Test the resample_in_time method"""
# Note this file has slight variations in the delta t between integrations
# that causes our gap test to issue a warning, but the variations are small
# We aren't worried about them, so we filter those warnings
uv_object = bda_test_file
# save some initial info
# 2s integration time
init_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
init_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
init_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
init_data_136_137 = uv_object.get_data((136, 137))
uv_object.resample_in_time(8)
# Should have all the target integration time
assert np.all(np.isclose(uv_object.integration_time, 8))
# 2s integration time
out_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
out_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
out_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
out_data_136_137 = uv_object.get_data((136, 137))
# check array sizes make sense
assert out_data_1_136.size * 4 == init_data_1_136.size
assert out_data_1_137.size * 2 == init_data_1_137.size
assert out_data_1_138.size == init_data_1_138.size
assert out_data_136_137.size / 2 == init_data_136_137.size
# check some values
assert np.isclose(np.mean(init_data_1_136[0:4, 0, 0]), out_data_1_136[0, 0, 0])
assert np.isclose(np.mean(init_data_1_137[0:2, 0, 0]), out_data_1_137[0, 0, 0])
assert np.isclose(init_data_1_138[0, 0, 0], out_data_1_138[0, 0, 0])
assert np.isclose(init_data_136_137[0, 0, 0], out_data_136_137[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:Telescope mock-HERA is not in known_telescopes")
@pytest.mark.filterwarnings("ignore:There is a gap in the times of baseline")
def test_resample_in_time_downsample_only(bda_test_file):
"""Test resample_in_time with downsampling only"""
# Note this file has slight variations in the delta t between integrations
# that causes our gap test to issue a warning, but the variations are small
# We aren't worried about them, so we filter those warnings
uv_object = bda_test_file
# save some initial info
# 2s integration time
init_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
init_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
init_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
init_data_136_137 = uv_object.get_data((136, 137))
# resample again, with only_downsample set
uv_object.resample_in_time(8, only_downsample=True)
# Should have all less than or equal to the target integration time
assert np.all(
np.logical_or(
np.isclose(uv_object.integration_time, 8),
np.isclose(uv_object.integration_time, 16)
)
)
# 2s integration time
out_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
out_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
out_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
out_data_136_137 = uv_object.get_data((136, 137))
# check array sizes make sense
assert out_data_1_136.size * 4 == init_data_1_136.size
assert out_data_1_137.size * 2 == init_data_1_137.size
assert out_data_1_138.size == init_data_1_138.size
assert out_data_136_137.size == init_data_136_137.size
# check some values
assert np.isclose(np.mean(init_data_1_136[0:4, 0, 0]), out_data_1_136[0, 0, 0])
assert np.isclose(np.mean(init_data_1_137[0:2, 0, 0]), out_data_1_137[0, 0, 0])
assert np.isclose(init_data_1_138[0, 0, 0], out_data_1_138[0, 0, 0])
assert np.isclose(init_data_136_137[0, 0, 0], out_data_136_137[0, 0, 0])
return
@pytest.mark.filterwarnings("ignore:Telescope mock-HERA is not in known_telescopes")
@pytest.mark.filterwarnings("ignore:There is a gap in the times of baseline")
def test_resample_in_time_only_upsample(bda_test_file):
"""Test resample_in_time with only upsampling"""
# Note this file has slight variations in the delta t between integrations
# that causes our gap test to issue a warning, but the variations are small
# We aren't worried about them, so we filter those warnings
uv_object = bda_test_file
# save some initial info
# 2s integration time
init_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
init_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
init_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
init_data_136_137 = uv_object.get_data((136, 137))
# again, with only_upsample set
uv_object.resample_in_time(8, only_upsample=True)
# Should have all greater than or equal to the target integration time
assert np.all(
np.logical_or(
np.logical_or(
np.isclose(uv_object.integration_time, 2.),
np.isclose(uv_object.integration_time, 4.)),
np.isclose(uv_object.integration_time, 8.)
)
)
# 2s integration time
out_data_1_136 = uv_object.get_data((1, 136))
# 4s integration time
out_data_1_137 = uv_object.get_data((1, 137))
# 8s integration time
out_data_1_138 = uv_object.get_data((1, 138))
# 16s integration time
out_data_136_137 = uv_object.get_data((136, 137))
# check array sizes make sense
assert out_data_1_136.size == init_data_1_136.size
assert out_data_1_137.size == init_data_1_137.size
assert out_data_1_138.size == init_data_1_138.size
assert out_data_136_137.size / 2 == init_data_136_137.size
# check some values
assert np.isclose(init_data_1_136[0, 0, 0], out_data_1_136[0, 0, 0])
assert np.isclose(init_data_1_137[0, 0, 0], out_data_1_137[0, 0, 0])
assert np.isclose(init_data_1_138[0, 0, 0], out_data_1_138[0, 0, 0])
assert np.isclose(init_data_136_137[0, 0, 0], out_data_136_137[0, 0, 0])
return
def test_remove_eq_coeffs_divide(uvdata_data):
"""Test using the remove_eq_coeffs method with divide convention."""
# give eq_coeffs to the object
eq_coeffs = np.empty(
(uvdata_data.uv_object.Nants_telescope, uvdata_data.uv_object.Nfreqs),
dtype=np.float
)
for i, ant in enumerate(uvdata_data.uv_object.antenna_numbers):
eq_coeffs[i, :] = ant + 1
uvdata_data.uv_object.eq_coeffs = eq_coeffs
uvdata_data.uv_object.eq_coeffs_convention = "divide"
uvdata_data.uv_object.remove_eq_coeffs()
# make sure the right coefficients were removed
for key in uvdata_data.uv_object.get_antpairs():
eq1 = key[0] + 1
eq2 = key[1] + 1
blt_inds = uvdata_data.uv_object.antpair2ind(key)
norm_data = uvdata_data.uv_object.data_array[blt_inds, 0, :, :]
unnorm_data = uvdata_data.uv_object2.data_array[blt_inds, 0, :, :]
assert np.allclose(norm_data, unnorm_data / (eq1 * eq2))
return
def test_remove_eq_coeffs_multiply(uvdata_data):
"""Test using the remove_eq_coeffs method with multiply convention."""
# give eq_coeffs to the object
eq_coeffs = np.empty(
(uvdata_data.uv_object.Nants_telescope, uvdata_data.uv_object.Nfreqs),
dtype=np.float
)
for i, ant in enumerate(uvdata_data.uv_object.antenna_numbers):
eq_coeffs[i, :] = ant + 1
uvdata_data.uv_object.eq_coeffs = eq_coeffs
uvdata_data.uv_object.eq_coeffs_convention = "multiply"
uvdata_data.uv_object.remove_eq_coeffs()
# make sure the right coefficients were removed
for key in uvdata_data.uv_object.get_antpairs():
eq1 = key[0] + 1
eq2 = key[1] + 1
blt_inds = uvdata_data.uv_object.antpair2ind(key)
norm_data = uvdata_data.uv_object.data_array[blt_inds, 0, :, :]
unnorm_data = uvdata_data.uv_object2.data_array[blt_inds, 0, :, :]
assert np.allclose(norm_data, unnorm_data * (eq1 * eq2))
return
def test_remove_eq_coeffs_errors(uvdata_data):
"""Test errors raised by remove_eq_coeffs method."""
# raise error when eq_coeffs are not defined
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object.remove_eq_coeffs()
assert str(cm.value).startswith("The eq_coeffs attribute must be defined")
# raise error when eq_coeffs are defined but not eq_coeffs_convention
uvdata_data.uv_object.eq_coeffs = np.ones(
(uvdata_data.uv_object.Nants_telescope, uvdata_data.uv_object.Nfreqs)
)
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object.remove_eq_coeffs()
assert str(cm.value).startswith("The eq_coeffs_convention attribute must be defined")
# raise error when convention is not a valid choice
uvdata_data.uv_object.eq_coeffs_convention = "foo"
with pytest.raises(ValueError) as cm:
uvdata_data.uv_object.remove_eq_coeffs()
assert str(cm.value).startswith("Got unknown convention foo. Must be one of")
return
