# -*- mode: python; coding: utf-8 -*-
# Copyright (c) 2018 Radio Astronomy Software Group
# Licensed under the 2-clause BSD License

"""Tests for common utility functions.

"""
import os
import pytest
import numpy as np
from astropy import units
from astropy.time import Time
from astropy.coordinates import SkyCoord, Angle
import copy

from pyuvdata import (
    UVData,
    UVFlag,
    UVCal,
)
import pyuvdata.utils as uvutils
import pyuvdata.tests as uvtest
from pyuvdata.data import DATA_PATH


ref_latlonalt = (-26.7 * np.pi / 180.0, 116.7 * np.pi / 180.0, 377.8)
ref_xyz = (-2562123.42683, 5094215.40141, -2848728.58869)


def test_XYZ_from_LatLonAlt():
    """Test conversion from lat/lon/alt to ECEF xyz with reference values."""
    out_xyz = uvutils.XYZ_from_LatLonAlt(
        ref_latlonalt[0], ref_latlonalt[1], ref_latlonalt[2]
    )
    # Got reference by forcing http://www.oc.nps.edu/oc2902w/coord/llhxyz.htm
    # to give additional precision.
    assert np.allclose(ref_xyz, out_xyz, rtol=0, atol=1e-3)

    # test error checking
    pytest.raises(
        ValueError,
        uvutils.XYZ_from_LatLonAlt,
        ref_latlonalt[0],
        ref_latlonalt[1],
        np.array([ref_latlonalt[2], ref_latlonalt[2]]),
    )
    pytest.raises(
        ValueError,
        uvutils.XYZ_from_LatLonAlt,
        ref_latlonalt[0],
        np.array([ref_latlonalt[1], ref_latlonalt[1]]),
        ref_latlonalt[2],
    )


def test_LatLonAlt_from_XYZ():
    """Test conversion from ECEF xyz to lat/lon/alt with reference values."""
    out_latlonalt = uvutils.LatLonAlt_from_XYZ(ref_xyz)
    # Got reference by forcing http://www.oc.nps.edu/oc2902w/coord/llhxyz.htm
    # to give additional precision.
    assert np.allclose(ref_latlonalt, out_latlonalt, rtol=0, atol=1e-3)
    pytest.raises(ValueError, uvutils.LatLonAlt_from_XYZ, ref_latlonalt)

    # test passing multiple values
    xyz_mult = np.stack((np.array(ref_xyz), np.array(ref_xyz)))
    lat_vec, lon_vec, alt_vec = uvutils.LatLonAlt_from_XYZ(xyz_mult)
    assert np.allclose(
        ref_latlonalt, (lat_vec[1], lon_vec[1], alt_vec[1]), rtol=0, atol=1e-3
    )
    # check error if array transposed
    with pytest.raises(ValueError) as cm:
        uvutils.LatLonAlt_from_XYZ(xyz_mult.T)
    assert str(cm.value).startswith(
        "The expected shape of ECEF xyz array is (Npts, 3)."
    )

    # check error if only 2 coordinates
    with pytest.raises(ValueError) as cm:
        uvutils.LatLonAlt_from_XYZ(xyz_mult[:, 0:2])
    assert str(cm.value).startswith(
        "The expected shape of ECEF xyz array is (Npts, 3)."
    )

    # test error checking
    pytest.raises(ValueError, uvutils.LatLonAlt_from_XYZ, ref_xyz[0:1])


def test_ENU_tofrom_ECEF():
    center_lat = -30.7215261207 * np.pi / 180.0
    center_lon = 21.4283038269 * np.pi / 180.0
    center_alt = 1051.7
    # fmt: off
    lats = (np.array([-30.72218216, -30.72138101, -30.7212785, -30.7210011,
                     -30.72159853, -30.72206199, -30.72174614, -30.72188775,
                     -30.72183915, -30.72100138])
            * np.pi / 180.0)
    lons = (np.array([21.42728211, 21.42811727, 21.42814544, 21.42795736,
                     21.42686739, 21.42918772, 21.42785662, 21.4286408,
                     21.42750933, 21.42896567])
            * np.pi / 180.0)
    alts = np.array([1052.25, 1051.35, 1051.2, 1051., 1051.45, 1052.04, 1051.68,
                     1051.87, 1051.77, 1051.06])
    # used pymap3d, which implements matlab code, as a reference.
    x = [5109327.46674067, 5109339.76407785, 5109344.06370947,
         5109365.11297147, 5109372.115673, 5109266.94314734,
         5109329.89620962, 5109295.13656657, 5109337.21810468,
         5109329.85680612]

    y = [2005130.57953031, 2005221.35184577, 2005225.93775268,
         2005214.8436201, 2005105.42364036, 2005302.93158317,
         2005190.65566222, 2005257.71335575, 2005157.78980089,
         2005304.7729239]

    z = [-3239991.24516348, -3239914.4185286, -3239904.57048431,
         -3239878.02656316, -3239935.20415493, -3239979.68381865,
         -3239949.39266985, -3239962.98805772, -3239958.30386264,
         -3239878.08403833]

    east = [-97.87631659, -17.87126443, -15.17316938, -33.19049252, -137.60520964,
            84.67346748, -42.84049408, 32.28083937, -76.1094745, 63.40285935]
    north = [-72.7437482, 16.09066646, 27.45724573, 58.21544651, -8.02964511,
             -59.41961437, -24.39698388, -40.09891961, -34.70965816, 58.18410876]
    up = [0.54883333, -0.35004539, -0.50007736, -0.70035299, -0.25148791, 0.33916067,
          -0.02019057, 0.16979185, 0.06945155, -0.64058124]
    # fmt: on

    xyz = uvutils.XYZ_from_LatLonAlt(lats, lons, alts)
    assert np.allclose(np.stack((x, y, z), axis=1), xyz, atol=1e-3)

    enu = uvutils.ENU_from_ECEF(xyz, center_lat, center_lon, center_alt)
    assert np.allclose(np.stack((east, north, up), axis=1), enu, atol=1e-3)
    # check error if array transposed
    with pytest.raises(ValueError) as cm:
        uvutils.ENU_from_ECEF(xyz.T, center_lat, center_lon, center_alt)
    assert str(cm.value).startswith(
        "The expected shape of ECEF xyz array is (Npts, 3)."
    )

    # check error if only 2 coordinates
    with pytest.raises(ValueError) as cm:
        uvutils.ENU_from_ECEF(xyz[:, 0:2], center_lat, center_lon, center_alt)
    assert str(cm.value).startswith(
        "The expected shape of ECEF xyz array is (Npts, 3)."
    )

    # check that a round trip gives the original value.
    xyz_from_enu = uvutils.ECEF_from_ENU(enu, center_lat, center_lon, center_alt)
    assert np.allclose(xyz, xyz_from_enu, atol=1e-3)
    # check error if array transposed
    with pytest.raises(ValueError) as cm:
        uvutils.ECEF_from_ENU(enu.T, center_lat, center_lon, center_alt)
    assert str(cm.value).startswith("The expected shape of the ENU array is (Npts, 3).")

    # check error if only 2 coordinates
    with pytest.raises(ValueError) as cm:
        uvutils.ECEF_from_ENU(enu[:, 0:2], center_lat, center_lon, center_alt)
    assert str(cm.value).startswith("The expected shape of the ENU array is (Npts, 3).")

    # check passing a single value
    enu_single = uvutils.ENU_from_ECEF(xyz[0, :], center_lat, center_lon, center_alt)
    assert np.allclose(np.array((east[0], north[0], up[0])), enu[0, :], atol=1e-3)

    xyz_from_enu = uvutils.ECEF_from_ENU(enu_single, center_lat, center_lon, center_alt)
    assert np.allclose(xyz[0, :], xyz_from_enu, atol=1e-3)

    # error checking
    pytest.raises(
        ValueError,
        uvutils.ENU_from_ECEF,
        xyz[:, 0:1],
        center_lat,
        center_lon,
        center_alt,
    )
    pytest.raises(
        ValueError,
        uvutils.ECEF_from_ENU,
        enu[:, 0:1],
        center_lat,
        center_lon,
        center_alt,
    )
    pytest.raises(
        ValueError, uvutils.ENU_from_ECEF, xyz / 2.0, center_lat, center_lon, center_alt
    )


def test_mwa_ecef_conversion():
    """
    Test based on comparing the antenna locations in a Cotter uvfits file to
    the antenna locations in MWA_tools.
    """

    test_data_file = os.path.join(DATA_PATH, "mwa128_ant_layouts.npz")
    f = np.load(test_data_file)

    # From the STABXYZ table in a cotter-generated uvfits file, obsid = 1066666832
    xyz = f["stabxyz"]
    # From the East/North/Height columns in a cotter-generated metafits file,
    # obsid = 1066666832
    enh = f["ENH"]
    # From a text file antenna_locations.txt in MWA_Tools/scripts
    txt_topo = f["txt_topo"]

    # From the unphased uvw coordinates of obsid 1066666832, positions relative
    # to antenna 0
    # these aren't used in the current test, but are interesting and might help
    # with phasing diagnosis in the future
    uvw_topo = f["uvw_topo"]
    # Sky coordinates are flipped for uvw derived values
    uvw_topo = -uvw_topo
    uvw_topo += txt_topo[0]

    # transpose these arrays to get them into the right shape
    txt_topo = txt_topo.T
    uvw_topo = uvw_topo.T

    # ARRAYX, ARRAYY, ARRAYZ in ECEF frame from Cotter file
    arrcent = f["arrcent"]
    lat, lon, alt = uvutils.LatLonAlt_from_XYZ(arrcent)

    # The STABXYZ coordinates are defined with X through the local meridian,
    # so rotate back to the prime meridian
    new_xyz = uvutils.ECEF_from_rotECEF(xyz.T, lon)
    # add in array center to get real ECEF
    ecef_xyz = new_xyz + arrcent

    enu = uvutils.ENU_from_ECEF(ecef_xyz, lat, lon, alt)

    assert np.allclose(enu, enh)

    # test other direction of ECEF rotation
    rot_xyz = uvutils.rotECEF_from_ECEF(new_xyz, lon)
    assert np.allclose(rot_xyz.T, xyz)


def test_phasing_funcs():
    # these tests are based on a notebook where I tested against the mwa_tools
    # phasing code
    ra_hrs = 12.1
    dec_degs = -42.3
    mjd = 55780.1

    array_center_xyz = np.array([-2559454.08, 5095372.14, -2849057.18])
    lat_lon_alt = uvutils.LatLonAlt_from_XYZ(array_center_xyz)

    obs_time = Time(mjd, format="mjd", location=(lat_lon_alt[1], lat_lon_alt[0]))

    icrs_coord = SkyCoord(
        ra=Angle(ra_hrs, unit="hr"), dec=Angle(dec_degs, unit="deg"), obstime=obs_time
    )
    gcrs_coord = icrs_coord.transform_to("gcrs")

    # in east/north/up frame (relative to array center) in meters: (Nants, 3)
    ants_enu = np.array([-101.94, 0156.41, 0001.24])

    ant_xyz_abs = uvutils.ECEF_from_ENU(
        ants_enu, lat_lon_alt[0], lat_lon_alt[1], lat_lon_alt[2]
    )

    array_center_coord = SkyCoord(
        x=array_center_xyz[0] * units.m,
        y=array_center_xyz[1] * units.m,
        z=array_center_xyz[2] * units.m,
        frame="itrs",
        obstime=obs_time,
    )

    itrs_coord = SkyCoord(
        x=ant_xyz_abs[0] * units.m,
        y=ant_xyz_abs[1] * units.m,
        z=ant_xyz_abs[2] * units.m,
        frame="itrs",
        obstime=obs_time,
    )

    gcrs_array_center = array_center_coord.transform_to("gcrs")
    gcrs_from_itrs_coord = itrs_coord.transform_to("gcrs")

    gcrs_rel = (
        (gcrs_from_itrs_coord.cartesian - gcrs_array_center.cartesian).get_xyz().T
    )

    gcrs_uvw = uvutils.phase_uvw(gcrs_coord.ra.rad, gcrs_coord.dec.rad, gcrs_rel.value)

    mwa_tools_calcuvw_u = -97.122828
    mwa_tools_calcuvw_v = 50.388281
    mwa_tools_calcuvw_w = -151.27976

    assert np.allclose(gcrs_uvw[0, 0], mwa_tools_calcuvw_u, atol=1e-3)
    assert np.allclose(gcrs_uvw[0, 1], mwa_tools_calcuvw_v, atol=1e-3)
    assert np.allclose(gcrs_uvw[0, 2], mwa_tools_calcuvw_w, atol=1e-3)

    # also test unphasing
    temp2 = uvutils.unphase_uvw(
        gcrs_coord.ra.rad, gcrs_coord.dec.rad, np.squeeze(gcrs_uvw)
    )
    assert np.allclose(gcrs_rel.value, temp2)


def test_pol_funcs():
    """ Test utility functions to convert between polarization strings and numbers """

    pol_nums = [-8, -7, -6, -5, -4, -3, -2, -1, 1, 2, 3, 4]
    pol_str = ["yx", "xy", "yy", "xx", "lr", "rl", "ll", "rr", "pI", "pQ", "pU", "pV"]
    assert pol_nums == uvutils.polstr2num(pol_str)
    assert pol_str == uvutils.polnum2str(pol_nums)
    # Check individuals
    assert -6 == uvutils.polstr2num("YY")
    assert "pV" == uvutils.polnum2str(4)
    # Check errors
    pytest.raises(KeyError, uvutils.polstr2num, "foo")
    pytest.raises(ValueError, uvutils.polstr2num, 1)
    pytest.raises(ValueError, uvutils.polnum2str, 7.3)
    # Check parse
    assert uvutils.parse_polstr("xX") == "xx"
    assert uvutils.parse_polstr("XX") == "xx"
    assert uvutils.parse_polstr("i") == "pI"


def test_pol_funcs_x_orientation():
    """Test functions to convert between pol strings and numbers with x_orientation."""

    pol_nums = [-8, -7, -6, -5, -4, -3, -2, -1, 1, 2, 3, 4]

    x_orient1 = "e"
    pol_str = ["ne", "en", "nn", "ee", "lr", "rl", "ll", "rr", "pI", "pQ", "pU", "pV"]
    assert pol_nums == uvutils.polstr2num(pol_str, x_orientation=x_orient1)
    assert pol_str == uvutils.polnum2str(pol_nums, x_orientation=x_orient1)
    # Check individuals
    assert -6 == uvutils.polstr2num("NN", x_orientation=x_orient1)
    assert "pV" == uvutils.polnum2str(4)
    # Check errors
    pytest.raises(KeyError, uvutils.polstr2num, "foo", x_orientation=x_orient1)
    pytest.raises(ValueError, uvutils.polstr2num, 1, x_orientation=x_orient1)
    pytest.raises(ValueError, uvutils.polnum2str, 7.3, x_orientation=x_orient1)
    # Check parse
    assert uvutils.parse_polstr("eE", x_orientation=x_orient1) == "ee"
    assert uvutils.parse_polstr("xx", x_orientation=x_orient1) == "ee"
    assert uvutils.parse_polstr("NN", x_orientation=x_orient1) == "nn"
    assert uvutils.parse_polstr("yy", x_orientation=x_orient1) == "nn"
    assert uvutils.parse_polstr("i", x_orientation=x_orient1) == "pI"

    x_orient2 = "n"
    pol_str = ["en", "ne", "ee", "nn", "lr", "rl", "ll", "rr", "pI", "pQ", "pU", "pV"]
    assert pol_nums == uvutils.polstr2num(pol_str, x_orientation=x_orient2)
    assert pol_str == uvutils.polnum2str(pol_nums, x_orientation=x_orient2)
    # Check individuals
    assert -6 == uvutils.polstr2num("EE", x_orientation=x_orient2)
    assert "pV" == uvutils.polnum2str(4)
    # Check errors
    pytest.raises(KeyError, uvutils.polstr2num, "foo", x_orientation=x_orient2)
    pytest.raises(ValueError, uvutils.polstr2num, 1, x_orientation=x_orient2)
    pytest.raises(ValueError, uvutils.polnum2str, 7.3, x_orientation=x_orient2)
    # Check parse
    assert uvutils.parse_polstr("nN", x_orientation=x_orient2) == "nn"
    assert uvutils.parse_polstr("xx", x_orientation=x_orient2) == "nn"
    assert uvutils.parse_polstr("EE", x_orientation=x_orient2) == "ee"
    assert uvutils.parse_polstr("yy", x_orientation=x_orient2) == "ee"
    assert uvutils.parse_polstr("i", x_orientation=x_orient2) == "pI"

    # check warnings for non-recognized x_orientation
    assert (
        uvtest.checkWarnings(
            uvutils.polstr2num,
            ["xx"],
            {"x_orientation": "foo"},
            message="x_orientation not recognized",
        )
        == -5
    )
    assert (
        uvtest.checkWarnings(
            uvutils.polnum2str,
            [-6],
            {"x_orientation": "foo"},
            message="x_orientation not recognized",
        )
        == "yy"
    )


def test_jones_num_funcs():
    """Test functions to convert between jones polarization strings and numbers."""

    jnums = [-8, -7, -6, -5, -4, -3, -2, -1]
    jstr = ["Jyx", "Jxy", "Jyy", "Jxx", "Jlr", "Jrl", "Jll", "Jrr"]
    assert jnums == uvutils.jstr2num(jstr)
    assert jstr, uvutils.jnum2str(jnums)
    # Check shorthands
    jstr = ["yx", "xy", "yy", "y", "xx", "x", "lr", "rl", "ll", "l", "rr", "r"]
    jnums = [-8, -7, -6, -6, -5, -5, -4, -3, -2, -2, -1, -1]
    assert jnums == uvutils.jstr2num(jstr)
    # Check individuals
    assert -6 == uvutils.jstr2num("jyy")
    assert "Jxy" == uvutils.jnum2str(-7)
    # Check errors
    pytest.raises(KeyError, uvutils.jstr2num, "foo")
    pytest.raises(ValueError, uvutils.jstr2num, 1)
    pytest.raises(ValueError, uvutils.jnum2str, 7.3)

    # check parse method
    assert uvutils.parse_jpolstr("x") == "Jxx"
    assert uvutils.parse_jpolstr("xy") == "Jxy"
    assert uvutils.parse_jpolstr("XY") == "Jxy"


def test_jones_num_funcs_x_orientation():
    """Test functions to convert jones pol strings and numbers with x_orientation."""

    jnums = [-8, -7, -6, -5, -4, -3, -2, -1]
    x_orient1 = "east"
    jstr = ["Jne", "Jen", "Jnn", "Jee", "Jlr", "Jrl", "Jll", "Jrr"]
    assert jnums == uvutils.jstr2num(jstr, x_orientation=x_orient1)
    assert jstr == uvutils.jnum2str(jnums, x_orientation=x_orient1)
    # Check shorthands
    jstr = ["ne", "en", "nn", "n", "ee", "e", "lr", "rl", "ll", "l", "rr", "r"]
    jnums = [-8, -7, -6, -6, -5, -5, -4, -3, -2, -2, -1, -1]
    assert jnums == uvutils.jstr2num(jstr, x_orientation=x_orient1)
    # Check individuals
    assert -6 == uvutils.jstr2num("jnn", x_orientation=x_orient1)
    assert "Jen" == uvutils.jnum2str(-7, x_orientation=x_orient1)
    # Check errors
    pytest.raises(KeyError, uvutils.jstr2num, "foo", x_orientation=x_orient1)
    pytest.raises(ValueError, uvutils.jstr2num, 1, x_orientation=x_orient1)
    pytest.raises(ValueError, uvutils.jnum2str, 7.3, x_orientation=x_orient1)

    # check parse method
    assert uvutils.parse_jpolstr("e", x_orientation=x_orient1) == "Jee"
    assert uvutils.parse_jpolstr("x", x_orientation=x_orient1) == "Jee"
    assert uvutils.parse_jpolstr("y", x_orientation=x_orient1) == "Jnn"
    assert uvutils.parse_jpolstr("en", x_orientation=x_orient1) == "Jen"
    assert uvutils.parse_jpolstr("NE", x_orientation=x_orient1) == "Jne"

    jnums = [-8, -7, -6, -5, -4, -3, -2, -1]
    x_orient2 = "north"
    jstr = ["Jen", "Jne", "Jee", "Jnn", "Jlr", "Jrl", "Jll", "Jrr"]
    assert jnums == uvutils.jstr2num(jstr, x_orientation=x_orient2)
    assert jstr == uvutils.jnum2str(jnums, x_orientation=x_orient2)
    # Check shorthands
    jstr = ["en", "ne", "ee", "e", "nn", "n", "lr", "rl", "ll", "l", "rr", "r"]
    jnums = [-8, -7, -6, -6, -5, -5, -4, -3, -2, -2, -1, -1]
    assert jnums == uvutils.jstr2num(jstr, x_orientation=x_orient2)
    # Check individuals
    assert -6 == uvutils.jstr2num("jee", x_orientation=x_orient2)
    assert "Jne" == uvutils.jnum2str(-7, x_orientation=x_orient2)
    # Check errors
    pytest.raises(KeyError, uvutils.jstr2num, "foo", x_orientation=x_orient2)
    pytest.raises(ValueError, uvutils.jstr2num, 1, x_orientation=x_orient2)
    pytest.raises(ValueError, uvutils.jnum2str, 7.3, x_orientation=x_orient2)

    # check parse method
    assert uvutils.parse_jpolstr("e", x_orientation=x_orient2) == "Jee"
    assert uvutils.parse_jpolstr("x", x_orientation=x_orient2) == "Jnn"
    assert uvutils.parse_jpolstr("y", x_orientation=x_orient2) == "Jee"
    assert uvutils.parse_jpolstr("en", x_orientation=x_orient2) == "Jen"
    assert uvutils.parse_jpolstr("NE", x_orientation=x_orient2) == "Jne"

    # check warnings for non-recognized x_orientation
    assert (
        uvtest.checkWarnings(
            uvutils.jstr2num,
            ["x"],
            {"x_orientation": "foo"},
            message="x_orientation not recognized",
        )
        == -5
    )
    assert (
        uvtest.checkWarnings(
            uvutils.jnum2str,
            [-6],
            {"x_orientation": "foo"},
            message="x_orientation not recognized",
        )
        == "Jyy"
    )


def test_conj_pol():
    """ Test function to conjugate pols """

    pol_nums = [-8, -7, -6, -5, -4, -3, -2, -1, 1, 2, 3, 4]
    cpol_nums = [-7, -8, -6, -5, -3, -4, -2, -1, 1, 2, 3, 4]
    assert pol_nums == uvutils.conj_pol(cpol_nums)
    assert uvutils.conj_pol(pol_nums) == cpol_nums
    # fmt: off
    pol_str = ['yx', 'xy', 'yy', 'xx', 'ee', 'nn', 'en', 'ne', 'lr', 'rl', 'll',
               'rr', 'pI', 'pQ', 'pU', 'pV']
    cpol_str = ['xy', 'yx', 'yy', 'xx', 'ee', 'nn', 'ne', 'en', 'rl', 'lr', 'll',
                'rr', 'pI', 'pQ', 'pU', 'pV']
    # fmt: on
    assert pol_str == uvutils.conj_pol(cpol_str)
    assert uvutils.conj_pol(pol_str) == cpol_str
    assert [pol_str, pol_nums] == uvutils.conj_pol([cpol_str, cpol_nums])

    # Test error with jones
    cjstr = ["Jxy", "Jyx", "Jyy", "Jxx", "Jrl", "Jlr", "Jll", "Jrr"]
    assert pytest.raises(KeyError, uvutils.conj_pol, cjstr)

    # Test invalid pol
    with pytest.raises(ValueError) as cm:
        uvutils.conj_pol(2.3)
    assert str(cm.value).startswith(
        "Polarization not recognized, cannot be conjugated."
    )


def test_redundancy_finder():
    """
    Check that get_baseline_redundancies and get_antenna_redundancies return consistent
    redundant groups for a test file with the HERA19 layout.
    """
    uvd = UVData()
    uvd.read_uvfits(
        os.path.join(DATA_PATH, "fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits")
    )

    uvd.select(times=uvd.time_array[0])
    uvd.unphase_to_drift(use_ant_pos=True)
    # uvw_array is now equivalent to baseline positions
    uvd.conjugate_bls(convention="ant1<ant2", use_enu=True)

    tol = 0.05  # meters

    bl_positions = uvd.uvw_array
    bl_pos_backup = copy.deepcopy(uvd.uvw_array)

    pytest.raises(
        ValueError,
        uvutils.get_baseline_redundancies,
        uvd.baseline_array,
        bl_positions[0:2, 0:1],
    )

    baseline_groups, vec_bin_centers, lens = uvutils.get_baseline_redundancies(
        uvd.baseline_array, bl_positions, tol=tol
    )

    for gi, gp in enumerate(baseline_groups):
        for bl in gp:
            bl_ind = np.where(uvd.baseline_array == bl)
            bl_vec = bl_positions[bl_ind]
            assert np.allclose(
                np.sqrt(np.dot(bl_vec, vec_bin_centers[gi])), lens[gi], atol=tol
            )

    # Shift the baselines around in a circle. Check that the same baselines are
    # recovered to the corresponding tolerance increase.
    # This moves one baseline at a time by a fixed displacement and checks that
    # the redundant groups are the same.

    hightol = 0.25  # meters. Less than the smallest baseline in the file.
    Nbls = uvd.Nbls
    Nshifts = 5
    shift_angs = np.linspace(0, 2 * np.pi, Nshifts)
    base_shifts = np.stack(
        (
            (hightol - tol) * np.cos(shift_angs),
            (hightol - tol) * np.sin(shift_angs),
            np.zeros(Nshifts),
        )
    ).T
    for sh in base_shifts:
        for bi in range(Nbls):
            # Shift one baseline at a time.
            bl_positions_new = uvd.uvw_array
            bl_positions_new[bi] += sh

            (
                baseline_groups_new,
                vec_bin_centers,
                lens,
            ) = uvutils.get_baseline_redundancies(
                uvd.baseline_array, bl_positions_new, tol=hightol
            )

            for gi, gp in enumerate(baseline_groups_new):
                for bl in gp:
                    bl_ind = np.where(uvd.baseline_array == bl)
                    bl_vec = bl_positions[bl_ind]
                    assert np.allclose(
                        np.sqrt(np.abs(np.dot(bl_vec, vec_bin_centers[gi]))),
                        lens[gi],
                        atol=hightol,
                    )

            # Compare baseline groups:
            a = [tuple(el) for el in baseline_groups]
            b = [tuple(el) for el in baseline_groups_new]
            assert set(a) == set(b)

    tol = 0.05

    antpos, antnums = uvd.get_ENU_antpos()

    baseline_groups_ants, vec_bin_centers, lens = uvutils.get_antenna_redundancies(
        antnums, antpos, tol=tol, include_autos=False
    )
    # Under these conditions, should see 19 redundant groups in the file.
    assert len(baseline_groups_ants) == 19

    # Check with conjugated baseline redundancies returned
    # Ensure at least one baseline has u==0 and v!=0 (for coverage of this case)
    bl_positions[16, 0] = 0
    (
        baseline_groups,
        vec_bin_centers,
        lens,
        conjugates,
    ) = uvutils.get_baseline_redundancies(
        uvd.baseline_array, bl_positions, tol=tol, with_conjugates=True
    )

    # restore baseline (16,0) and repeat to get correct groups
    bl_positions = bl_pos_backup
    (
        baseline_groups,
        vec_bin_centers,
        lens,
        conjugates,
    ) = uvutils.get_baseline_redundancies(
        uvd.baseline_array, bl_positions, tol=tol, with_conjugates=True
    )

    # Apply flips to compare with get_antenna_redundancies().
    bl_gps_unconj = copy.deepcopy(baseline_groups)
    for gi, gp in enumerate(bl_gps_unconj):
        for bi, bl in enumerate(gp):
            if bl in conjugates:
                bl_gps_unconj[gi][bi] = uvutils.baseline_index_flip(bl, len(antnums))
    bl_gps_unconj = [sorted(bgp) for bgp in bl_gps_unconj]
    assert np.all(sorted(baseline_groups_ants) == sorted(bl_gps_unconj))
    for gi, gp in enumerate(baseline_groups):
        for bl in gp:
            bl_ind = np.where(uvd.baseline_array == bl)
            bl_vec = bl_positions[bl_ind]
            if bl in conjugates:
                bl_vec *= -1
            assert np.isclose(
                np.sqrt(np.dot(bl_vec, vec_bin_centers[gi])), lens[gi], atol=tol
            )


def test_high_tolerance_redundancy_error():
    """
    Confirm that an error is raised if the redundancy tolerance is set too high,
    such that baselines end up in multiple
    """
    uvd = UVData()
    uvd.read_uvfits(
        os.path.join(DATA_PATH, "fewant_randsrc_airybeam_Nsrc100_10MHz.uvfits")
    )

    uvd.select(times=uvd.time_array[0])
    uvd.unphase_to_drift(use_ant_pos=True)
    # uvw_array is now equivalent to baseline positions
    uvd.conjugate_bls(convention="ant1<ant2", use_enu=True)
    bl_positions = uvd.uvw_array

    tol = 20.05  # meters

    with pytest.raises(ValueError) as cm:
        (
            baseline_groups,
            vec_bin_centers,
            lens,
            conjugates,
        ) = uvutils.get_baseline_redundancies(
            uvd.baseline_array, bl_positions, tol=tol, with_conjugates=True
        )
    assert "Some baselines are falling into" in str(cm.value)


def test_redundancy_conjugates():
    """
    Check that redundancy finding with conjugation works.

    Check that the correct baselines are flipped.
    """
    Nants = 10
    tol = 0.5
    ant1_arr = np.tile(np.arange(Nants), Nants)
    ant2_arr = np.repeat(np.arange(Nants), Nants)
    Nbls = ant1_arr.size
    bl_inds = uvutils.antnums_to_baseline(ant1_arr, ant2_arr, Nants)

    maxbl = 100.0
    bl_vecs = np.random.uniform(-maxbl, maxbl, (Nbls, 3))
    bl_vecs[0, 0] = 0
    bl_vecs[1, 0:2] = 0

    expected_conjugates = []
    for i, (u, v, w) in enumerate(bl_vecs):
        uneg = u < -tol
        uzer = np.isclose(u, 0.0, atol=tol)
        vneg = v < -tol
        vzer = np.isclose(v, 0.0, atol=tol)
        wneg = w < -tol
        if uneg or (uzer and vneg) or (uzer and vzer and wneg):
            expected_conjugates.append(bl_inds[i])
    bl_gps, vecs, lens, conjugates = uvutils.get_baseline_redundancies(
        bl_inds, bl_vecs, tol=tol, with_conjugates=True
    )

    assert sorted(conjugates) == sorted(expected_conjugates)


def test_redundancy_finder_fully_redundant_array():
    """Test the redundancy finder for a fully redundant array."""
    uvd = UVData()
    uvd.read_uvfits(os.path.join(DATA_PATH, "test_redundant_array.uvfits"))
    uvd.select(times=uvd.time_array[0])

    tol = 1  # meters
    bl_positions = uvd.uvw_array

    (
        baseline_groups,
        vec_bin_centers,
        lens,
        conjugates,
    ) = uvutils.get_baseline_redundancies(
        uvd.baseline_array, bl_positions, tol=tol, with_conjugates=True
    )

    # Only 1 set of redundant baselines
    assert len(baseline_groups) == 1
    #  Should return the input baselines
    assert baseline_groups[0].sort() == np.unique(uvd.baseline_array).sort()


def test_str_to_bytes():
    test_str = "HERA"

    test_bytes = uvtest.checkWarnings(
        uvutils._str_to_bytes,
        func_args=[test_str],
        nwarnings=1,
        category=DeprecationWarning,
        message="_str_to_bytes is deprecated and will be removed",
    )
    assert type(test_bytes) == bytes
    assert test_bytes == b"\x48\x45\x52\x41"
    return


def test_bytes_to_str():
    test_bytes = b"\x48\x45\x52\x41"
    test_str = uvtest.checkWarnings(
        uvutils._bytes_to_str,
        func_args=[test_bytes],
        nwarnings=1,
        category=DeprecationWarning,
        message="_bytes_to_str is deprecated and will be removed",
    )
    assert type(test_str) == str
    assert test_str == "HERA"
    return


def test_reorder_conj_pols_non_list():
    pytest.raises(ValueError, uvutils.reorder_conj_pols, 4)


def test_reorder_conj_pols_strings():
    pols = ["xx", "xy", "yx"]
    corder = uvutils.reorder_conj_pols(pols)
    assert np.array_equal(corder, [0, 2, 1])


def test_reorder_conj_pols_ints():
    pols = [-5, -7, -8]  # 'xx', 'xy', 'yx'
    corder = uvutils.reorder_conj_pols(pols)
    assert np.array_equal(corder, [0, 2, 1])


def test_reorder_conj_pols_missing_conj():
    pols = ["xx", "xy"]  # Missing 'yx'
    pytest.raises(ValueError, uvutils.reorder_conj_pols, pols)


def test_collapse_mean_no_return_no_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    out = uvutils.collapse(data, "mean", axis=0)
    out1 = uvutils.mean_collapse(data, axis=0)
    # Actual values are tested in test_mean_no_weights
    assert np.array_equal(out, out1)


def test_collapse_mean_returned_no_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    out, wo = uvutils.collapse(data, "mean", axis=0, return_weights=True)
    out1, wo1 = uvutils.mean_collapse(data, axis=0, return_weights=True)
    # Actual values are tested in test_mean_no_weights
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)


def test_collapse_mean_returned_with_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo = uvutils.collapse(data, "mean", weights=w, axis=0, return_weights=True)
    out1, wo1 = uvutils.mean_collapse(data, weights=w, axis=0, return_weights=True)
    # Actual values are tested in test_mean_weights
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)


def test_collapse_mean_returned_with_weights_and_weights_square():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo, wso = uvutils.collapse(
        data, "mean", weights=w, axis=0, return_weights=True, return_weights_square=True
    )
    out1, wo1, wso1 = uvutils.mean_collapse(
        data, weights=w, axis=0, return_weights=True, return_weights_square=True
    )
    # Actual values are tested in test_mean_weights
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)
    assert np.array_equal(wso, wso1)


def test_collapse_mean_returned_with_weights_square_no_return_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wso = uvutils.collapse(
        data,
        "mean",
        weights=w,
        axis=0,
        return_weights=False,
        return_weights_square=True,
    )
    out1, wso1 = uvutils.mean_collapse(
        data, weights=w, axis=0, return_weights=False, return_weights_square=True
    )
    # Actual values are tested in test_mean_weights
    assert np.array_equal(out, out1)
    assert np.array_equal(wso, wso1)


def test_collapse_absmean_no_return_no_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = (-1) ** i * np.ones_like(data[:, i])
    out = uvutils.collapse(data, "absmean", axis=0)
    out1 = uvutils.absmean_collapse(data, axis=0)
    # Actual values are tested in test_absmean_no_weights
    assert np.array_equal(out, out1)


def test_collapse_quadmean_no_return_no_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    out = uvutils.collapse(data, "quadmean", axis=0)
    out1 = uvutils.quadmean_collapse(data, axis=0)
    # Actual values are tested elsewhere?
    assert np.array_equal(out, out1)


def test_collapse_quadmean_returned_with_weights_and_weights_square():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo, wso = uvutils.collapse(
        data,
        "quadmean",
        weights=w,
        axis=0,
        return_weights=True,
        return_weights_square=True,
    )
    out1, wo1, wso1 = uvutils.quadmean_collapse(
        data, weights=w, axis=0, return_weights=True, return_weights_square=True
    )
    # Actual values are tested elsewhere?
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)
    assert np.array_equal(wso, wso1)


def test_collapse_quadmean_returned_with_weights_square_no_return_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wso = uvutils.collapse(
        data,
        "quadmean",
        weights=w,
        axis=0,
        return_weights=False,
        return_weights_square=True,
    )
    out1, wso1 = uvutils.quadmean_collapse(
        data, weights=w, axis=0, return_weights=False, return_weights_square=True
    )
    # Actual values are tested elsewhere?
    assert np.array_equal(out, out1)
    assert np.array_equal(wso, wso1)


def test_collapse_quadmean_returned_without_weights_square_with_return_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo = uvutils.collapse(
        data,
        "quadmean",
        weights=w,
        axis=0,
        return_weights=True,
        return_weights_square=False,
    )
    out1, wo1 = uvutils.quadmean_collapse(
        data, weights=w, axis=0, return_weights=True, return_weights_square=False
    )
    # Actual values are tested elsewhere?
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)


def test_collapse_quadmean_returned_with_weights_square_without_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo = uvutils.collapse(
        data,
        "quadmean",
        weights=w,
        axis=0,
        return_weights=False,
        return_weights_square=True,
    )
    out1, wo1 = uvutils.quadmean_collapse(
        data, weights=w, axis=0, return_weights=False, return_weights_square=True
    )
    # Actual values are tested elsewhere?
    assert np.array_equal(out, out1)
    assert np.array_equal(wo, wo1)


def test_collapse_or_no_return_no_weights():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, 8] = True
    o = uvutils.collapse(data, "or", axis=0)
    o1 = uvutils.or_collapse(data, axis=0)
    assert np.array_equal(o, o1)


def test_collapse_and_no_return_no_weights():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, :] = True
    o = uvutils.collapse(data, "and", axis=0)
    o1 = uvutils.and_collapse(data, axis=0)
    assert np.array_equal(o, o1)


def test_collapse_error():
    pytest.raises(ValueError, uvutils.collapse, np.ones((2, 3)), "fooboo")


def test_mean_no_weights():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    out, wo = uvutils.mean_collapse(data, axis=0, return_weights=True)
    assert np.array_equal(out, np.arange(data.shape[1]))
    assert np.array_equal(wo, data.shape[0] * np.ones(data.shape[1]))
    out, wo = uvutils.mean_collapse(data, axis=1, return_weights=True)
    assert np.all(out == np.mean(np.arange(data.shape[1])))
    assert len(out) == data.shape[0]
    assert np.array_equal(wo, data.shape[1] * np.ones(data.shape[0]))
    out, wo = uvutils.mean_collapse(data, return_weights=True)
    assert out == np.mean(np.arange(data.shape[1]))
    assert wo == data.size
    out = uvutils.mean_collapse(data)
    assert out == np.mean(np.arange(data.shape[1]))


def test_mean_weights_and_weights_square():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i]) + 1
    w = 1.0 / data
    out, wo, wso = uvutils.mean_collapse(
        data, weights=w, axis=0, return_weights=True, return_weights_square=True
    )
    assert np.allclose(out * wo, data.shape[0])
    assert np.allclose(wo, float(data.shape[0]) / (np.arange(data.shape[1]) + 1))
    assert np.allclose(wso, float(data.shape[0]) / (np.arange(data.shape[1]) + 1) ** 2)
    out, wo, wso = uvutils.mean_collapse(
        data, weights=w, axis=1, return_weights=True, return_weights_square=True
    )
    assert np.allclose(out * wo, data.shape[1])
    assert np.allclose(wo, np.sum(1.0 / (np.arange(data.shape[1]) + 1)))
    assert np.allclose(wso, np.sum(1.0 / (np.arange(data.shape[1]) + 1) ** 2))

    # Zero weights
    w = np.ones_like(w)
    w[0, :] = 0
    w[:, 0] = 0
    out, wo = uvutils.mean_collapse(data, weights=w, axis=0, return_weights=True)
    ans = np.arange(data.shape[1]).astype(np.float) + 1
    ans[0] = np.inf
    assert np.array_equal(out, ans)
    ans = (data.shape[0] - 1) * np.ones(data.shape[1])
    ans[0] = 0
    assert np.all(wo == ans)
    out, wo = uvutils.mean_collapse(data, weights=w, axis=1, return_weights=True)
    ans = np.mean(np.arange(data.shape[1])[1:] + 1) * np.ones(data.shape[0])
    ans[0] = np.inf
    assert np.all(out == ans)
    ans = (data.shape[1] - 1) * np.ones(data.shape[0])
    ans[0] = 0
    assert np.all(wo == ans)


def test_mean_infs():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    data[:, 0] = np.inf
    data[0, :] = np.inf
    out, wo = uvutils.mean_collapse(data, axis=0, return_weights=True)
    ans = np.arange(data.shape[1]).astype(np.float)
    ans[0] = np.inf
    assert np.array_equal(out, ans)
    ans = (data.shape[0] - 1) * np.ones(data.shape[1])
    ans[0] = 0
    assert np.all(wo == ans)
    out, wo = uvutils.mean_collapse(data, axis=1, return_weights=True)
    ans = np.mean(np.arange(data.shape[1])[1:]) * np.ones(data.shape[0])
    ans[0] = np.inf
    assert np.all(out == ans)
    ans = (data.shape[1] - 1) * np.ones(data.shape[0])
    ans[0] = 0
    assert np.all(wo == ans)


def test_absmean():
    # Fake data
    data1 = np.zeros((50, 25))
    for i in range(data1.shape[1]):
        data1[:, i] = (-1) ** i * np.ones_like(data1[:, i])
    data2 = np.ones_like(data1)
    out1 = uvutils.absmean_collapse(data1)
    out2 = uvutils.absmean_collapse(data2)
    assert out1 == out2


def test_quadmean():
    # Fake data
    data = np.zeros((50, 25))
    for i in range(data.shape[1]):
        data[:, i] = i * np.ones_like(data[:, i])
    o1, w1 = uvutils.quadmean_collapse(data, return_weights=True)
    o2, w2 = uvutils.mean_collapse(np.abs(data) ** 2, return_weights=True)
    o3 = uvutils.quadmean_collapse(data)  # without return_weights
    o2 = np.sqrt(o2)
    assert o1 == o2
    assert w1 == w2
    assert o1 == o3


def test_or_collapse():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, 8] = True
    o = uvutils.or_collapse(data, axis=0)
    ans = np.zeros(25, np.bool)
    ans[8] = True
    assert np.array_equal(o, ans)
    o = uvutils.or_collapse(data, axis=1)
    ans = np.zeros(50, np.bool)
    ans[0] = True
    assert np.array_equal(o, ans)
    o = uvutils.or_collapse(data)
    assert o


def test_or_collapse_weights():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, 8] = True
    w = np.ones_like(data, np.float)
    o, wo = uvutils.or_collapse(data, axis=0, weights=w, return_weights=True)
    ans = np.zeros(25, np.bool)
    ans[8] = True
    assert np.array_equal(o, ans)
    assert np.array_equal(wo, np.ones_like(o, dtype=np.float))
    w[0, 8] = 0.3
    o = uvtest.checkWarnings(
        uvutils.or_collapse,
        [data],
        {"axis": 0, "weights": w},
        nwarnings=1,
        message="Currently weights are",
    )
    assert np.array_equal(o, ans)


def test_or_collapse_errors():
    data = np.zeros(5)
    pytest.raises(ValueError, uvutils.or_collapse, data)


def test_and_collapse():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, :] = True
    o = uvutils.and_collapse(data, axis=0)
    ans = np.zeros(25, np.bool)
    assert np.array_equal(o, ans)
    o = uvutils.and_collapse(data, axis=1)
    ans = np.zeros(50, np.bool)
    ans[0] = True
    assert np.array_equal(o, ans)
    o = uvutils.and_collapse(data)
    assert not o


def test_and_collapse_weights():
    # Fake data
    data = np.zeros((50, 25), np.bool)
    data[0, :] = True
    w = np.ones_like(data, np.float)
    o, wo = uvutils.and_collapse(data, axis=0, weights=w, return_weights=True)
    ans = np.zeros(25, np.bool)
    assert np.array_equal(o, ans)
    assert np.array_equal(wo, np.ones_like(o, dtype=np.float))
    w[0, 8] = 0.3
    o = uvtest.checkWarnings(
        uvutils.and_collapse,
        [data],
        {"axis": 0, "weights": w},
        nwarnings=1,
        message="Currently weights are",
    )
    assert np.array_equal(o, ans)


def test_and_collapse_errors():
    data = np.zeros(5)
    pytest.raises(ValueError, uvutils.and_collapse, data)


def test_uvcalibrate_apply_gains():
    # read data
    uvd = UVData()
    uvd.read(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcAA"))
    # give it an x_orientation
    uvd.x_orientation = "east"
    uvc = UVCal()
    uvc.read_calfits(os.path.join(DATA_PATH, "zen.2457698.40355.xx.gain.calfits"))
    # assign gain scale manually
    uvc.gain_scale = "Jy"
    # downselect to match each other
    uvd.select(frequencies=uvd.freq_array[0, :10])
    uvc.select(times=uvc.time_array[:3])
    key = (43, 72, "xx")
    ant1 = (43, "Jxx")
    ant2 = (72, "Jxx")

    # division calibrate
    uvc.gain_convention = "divide"
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc, prop_flags=True, flag_missing=False, inplace=False
    )
    np.testing.assert_array_almost_equal(
        uvdcal.get_data(key),
        uvd.get_data(key) / (uvc.get_gains(ant1) * uvc.get_gains(ant2).conj()).T,
    )
    assert uvdcal.vis_units == "Jy"

    # test undo
    uvdcal = uvutils.uvcalibrate(
        uvdcal, uvc, prop_flags=True, flag_missing=False, inplace=False, undo=True
    )
    np.testing.assert_array_almost_equal(uvd.get_data(key), uvdcal.get_data(key))
    assert uvdcal.vis_units == "UNCALIB"

    # multiplication calibrate
    uvc.gain_convention = "multiply"
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc, prop_flags=False, flag_missing=False, inplace=False
    )
    np.testing.assert_array_almost_equal(
        uvdcal.get_data(key),
        uvd.get_data(key) * (uvc.get_gains(ant1) * uvc.get_gains(ant2).conj()).T,
    )
    assert uvdcal.vis_units == "Jy"

    # test delay conversion runs through
    uvc.read_calfits(os.path.join(DATA_PATH, "zen.2457698.40355.xx.delay.calfits"))
    uvc.select(times=uvc.time_array[:3], frequencies=uvc.freq_array[0, :10])
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc, prop_flags=False, flag_missing=False, inplace=False
    )

    # test d-term exception
    pytest.raises(ValueError, uvutils.uvcalibrate, uvd, uvc, Dterm_cal=True)
    # d-term not implemented error
    uvcDterm = copy.deepcopy(uvc)
    uvcDterm.jones_array = np.array([-7])
    uvcDterm = uvc + uvcDterm
    pytest.raises(
        NotImplementedError, uvutils.uvcalibrate, uvd, uvcDterm, Dterm_cal=True
    )


def test_uvcalibrate_flag_propagation():
    # read data
    uvd = UVData()
    uvd.read(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcAA"))
    uvc = UVCal()
    uvc.read_calfits(os.path.join(DATA_PATH, "zen.2457698.40355.xx.gain.calfits"))
    # downselect to match each other
    uvd.select(frequencies=uvd.freq_array[0, :10])
    uvc.select(times=uvc.time_array[:3])

    # test flag propagation
    uvc.flag_array[0] = True
    uvc.gain_array[1] = 0.0
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc, prop_flags=True, flag_missing=False, inplace=False
    )
    assert uvdcal.get_flags(9, 20, "xx").min()  # assert completely flagged
    assert uvdcal.get_flags(10, 20, "xx").min()  # assert completely flagged
    np.testing.assert_array_almost_equal(
        uvd.get_data(9, 20, "xx"), uvdcal.get_data(9, 20, "xx")
    )
    np.testing.assert_array_almost_equal(
        uvd.get_data(10, 20, "xx"), uvdcal.get_data(10, 20, "xx")
    )

    uvc_sub = uvc.select(antenna_nums=[9, 10], inplace=False)
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc_sub, prop_flags=True, flag_missing=False, inplace=False
    )
    assert not uvdcal.get_flags(20, 72, "xx").max()  # assert no flags exist
    uvdcal = uvutils.uvcalibrate(
        uvd, uvc_sub, prop_flags=True, flag_missing=True, inplace=False
    )
    assert uvdcal.get_flags(20, 72, "xx").min()  # assert completely flagged


def test_apply_uvflag():
    # load data and insert some flags
    uvd = UVData()
    uvd.read(os.path.join(DATA_PATH, "zen.2457698.40355.xx.HH.uvcAA"))
    uvd.flag_array[uvd.antpair2ind(9, 20)] = True

    # load a UVFlag into flag type
    uvf = UVFlag(uvd)
    uvf.to_flag()

    # insert flags for 2 out of 3 times
    uvf.flag_array[uvf.antpair2ind(9, 10)[:2]] = True

    # apply flags and check for basic flag propagation
    uvdf = uvutils.apply_uvflag(uvd, uvf, inplace=False)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 10)][:2])

    # test inplace
    uvdf = copy.deepcopy(uvd)
    uvutils.apply_uvflag(uvdf, uvf, inplace=True)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 10)][:2])

    # test flag missing
    uvf2 = uvf.select(bls=uvf.get_antpairs()[:-1], inplace=False)
    uvdf = uvutils.apply_uvflag(uvd, uvf2, inplace=False, flag_missing=True)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(uvf.get_antpairs()[-1])])
    uvdf = uvutils.apply_uvflag(uvd, uvf2, inplace=False, flag_missing=False)
    assert not np.any(uvdf.flag_array[uvdf.antpair2ind(uvf.get_antpairs()[-1])])

    # test force polarization
    uvdf = copy.deepcopy(uvd)
    uvdf2 = copy.deepcopy(uvd)
    uvdf2.polarization_array[0] = -6
    uvdf += uvdf2
    uvdf = uvutils.apply_uvflag(uvdf, uvf, inplace=False, force_pol=True)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 10)][:2])
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvdf, uvf, inplace=False, force_pol=False)
    assert "Input uvf and uvd polarizations do not match" in str(cm.value)

    # test unflag first
    uvdf = uvutils.apply_uvflag(uvd, uvf, inplace=False, unflag_first=True)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 10)][:2])
    assert not np.any(uvdf.flag_array[uvdf.antpair2ind(9, 20)])

    # convert uvf to waterfall and test
    uvfw = copy.deepcopy(uvf)
    uvfw.to_waterfall(method="or")
    uvdf = uvutils.apply_uvflag(uvd, uvfw, inplace=False)
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 10)][:2])
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(9, 20)][:2])
    assert np.all(uvdf.flag_array[uvdf.antpair2ind(20, 22)][:2])

    # test mode exception
    uvfm = copy.deepcopy(uvf)
    uvfm.mode = "metric"
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd, uvfm)
    assert "UVFlag must be flag mode" in str(cm.value)

    # test polarization exception
    uvd2 = copy.deepcopy(uvd)
    uvd2.polarization_array[0] = -6
    uvf2 = UVFlag(uvd)
    uvf2.to_flag()
    uvd2.polarization_array[0] = -8
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd2, uvf2, force_pol=False)
    assert "Input uvf and uvd polarizations do not match" in str(cm.value)

    # test time and frequency mismatch exceptions
    uvf2 = uvf.select(frequencies=uvf.freq_array[:, :2], inplace=False)
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd, uvf2)
    assert "UVFlag and UVData have mismatched frequency arrays" in str(cm.value)

    uvf2 = copy.deepcopy(uvf)
    uvf2.freq_array += 1.0
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd, uvf2)
    assert "UVFlag and UVData have mismatched frequency arrays" in str(cm.value)

    uvf2 = uvf.select(times=np.unique(uvf.time_array)[:2], inplace=False)
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd, uvf2)
    assert "UVFlag and UVData have mismatched time arrays" in str(cm.value)

    uvf2 = copy.deepcopy(uvf)
    uvf2.time_array += 1.0
    with pytest.raises(ValueError) as cm:
        uvutils.apply_uvflag(uvd, uvf2)
    assert "UVFlag and UVData have mismatched time arrays" in str(cm.value)

    # assert implicit broadcasting works
    uvf2 = uvf.select(frequencies=uvf.freq_array[:, :1], inplace=False)
    uvd2 = uvutils.apply_uvflag(uvd, uvf2, inplace=False)
    assert np.all(uvd2.get_flags(9, 10)[:2])
    uvf2 = uvf.select(times=np.unique(uvf.time_array)[:1], inplace=False)
    uvd2 = uvutils.apply_uvflag(uvd, uvf2, inplace=False)
    assert np.all(uvd2.get_flags(9, 10))


def test_upos_tol_reds():
    # Checks that the u-positive convention in get_antenna_redundancies
    # is enforced to the specificed tolerance.

    # Make a layout with two NS baselines, one with u ~ -2*eps, and another with u == 0
    # This would previously cause one to be flipped, when they should be redundant.

    eps = 1e-5
    tol = 3 * eps

    ant_pos = np.array(
        [[-eps, 1.0, 0.0], [1.0, 1.0, 0.0], [eps, 0.0, 0.0], [1.0, 0.0, 0.0]]
    )

    ant_nums = np.arange(4)

    red_grps, _, _ = uvutils.get_antenna_redundancies(ant_nums, ant_pos, tol=tol)

    assert len(red_grps) == 4