import datetime
import faulthandler
import os
import unittest

import numpy

faulthandler.enable()  # to debug seg faults and timeouts

import netCDF4

import cf

VN = cf.CF()


def _make_contiguous_file(filename):
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"

    n.createDimension("station", 4)
    n.createDimension("obs", 24)
    n.createDimension("name_strlen", 8)
    n.createDimension("bounds", 2)

    lon = n.createVariable("lon", "f8", ("station",))
    lon.standard_name = "longitude"
    lon.long_name = "station longitude"
    lon.units = "degrees_east"
    lon.bounds = "lon_bounds"
    lon[...] = [-23, 0, 67, 178]

    lon_bounds = n.createVariable("lon_bounds", "f8", ("station", "bounds"))
    lon_bounds[...] = [[-24, -22], [-1, 1], [66, 68], [177, 179]]

    lat = n.createVariable("lat", "f8", ("station",))
    lat.standard_name = "latitude"
    lat.long_name = "station latitude"
    lat.units = "degrees_north"
    lat[...] = [-9, 2, 34, 78]

    alt = n.createVariable("alt", "f8", ("station",))
    alt.long_name = "vertical distance above the surface"
    alt.standard_name = "height"
    alt.units = "m"
    alt.positive = "up"
    alt.axis = "Z"
    alt[...] = [0.5, 12.6, 23.7, 345]

    station_name = n.createVariable(
        "station_name", "S1", ("station", "name_strlen")
    )
    station_name.long_name = "station name"
    station_name.cf_role = "timeseries_id"
    station_name[...] = numpy.array(
        [
            [x for x in "station1"],
            [x for x in "station2"],
            [x for x in "station3"],
            [x for x in "station4"],
        ]
    )

    station_info = n.createVariable("station_info", "i4", ("station",))
    station_info.long_name = "some kind of station info"
    station_info[...] = [-10, -9, -8, -7]

    row_size = n.createVariable("row_size", "i4", ("station",))
    row_size.long_name = "number of observations for this station"
    row_size.sample_dimension = "obs"
    row_size[...] = [3, 7, 5, 9]

    time = n.createVariable("time", "f8", ("obs",))
    time.standard_name = "time"
    time.long_name = "time of measurement"
    time.units = "days since 1970-01-01 00:00:00"
    time.bounds = "time_bounds"
    time[0:3] = [-3, -2, -1]
    time[3:10] = [1, 2, 3, 4, 5, 6, 7]
    time[10:15] = [0.5, 1.5, 2.5, 3.5, 4.5]
    time[15:24] = range(-2, 7)

    time_bounds = n.createVariable("time_bounds", "f8", ("obs", "bounds"))
    time_bounds[..., 0] = time[...] - 0.5
    time_bounds[..., 1] = time[...] + 0.5

    humidity = n.createVariable("humidity", "f8", ("obs",), fill_value=-999.9)
    humidity.standard_name = "specific_humidity"
    humidity.coordinates = "time lat lon alt station_name station_info"
    humidity[0:3] = numpy.arange(0, 3)
    humidity[3:10] = numpy.arange(1, 71, 10)
    humidity[10:15] = numpy.arange(2, 502, 100)
    humidity[15:24] = numpy.arange(3, 9003, 1000)

    temp = n.createVariable("temp", "f8", ("obs",), fill_value=-999.9)
    temp.standard_name = "air_temperature"
    temp.units = "Celsius"
    temp.coordinates = "time lat lon alt station_name station_info"
    temp[...] = humidity[...] + 273.15

    n.close()

    return filename


def _make_indexed_file(filename):
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"

    n.createDimension("station", 4)
    n.createDimension("obs", None)
    n.createDimension("name_strlen", 8)
    n.createDimension("bounds", 2)

    lon = n.createVariable("lon", "f8", ("station",))
    lon.standard_name = "longitude"
    lon.long_name = "station longitude"
    lon.units = "degrees_east"
    lon.bounds = "lon_bounds"
    lon[...] = [-23, 0, 67, 178]

    lon_bounds = n.createVariable("lon_bounds", "f8", ("station", "bounds"))
    lon_bounds[...] = [[-24, -22], [-1, 1], [66, 68], [177, 179]]

    lat = n.createVariable("lat", "f8", ("station",))
    lat.standard_name = "latitude"
    lat.long_name = "station latitude"
    lat.units = "degrees_north"
    lat[...] = [-9, 2, 34, 78]

    alt = n.createVariable("alt", "f8", ("station",))
    alt.long_name = "vertical distance above the surface"
    alt.standard_name = "height"
    alt.units = "m"
    alt.positive = "up"
    alt.axis = "Z"
    alt[...] = [0.5, 12.6, 23.7, 345]

    station_name = n.createVariable(
        "station_name", "S1", ("station", "name_strlen")
    )
    station_name.long_name = "station name"
    station_name.cf_role = "timeseries_id"
    station_name[...] = numpy.array(
        [
            [x for x in "station1"],
            [x for x in "station2"],
            [x for x in "station3"],
            [x for x in "station4"],
        ]
    )

    station_info = n.createVariable("station_info", "i4", ("station",))
    station_info.long_name = "some kind of station info"
    station_info[...] = [-10, -9, -8, -7]

    # row_size[...] = [3, 7, 5, 9]
    stationIndex = n.createVariable("stationIndex", "i4", ("obs",))
    stationIndex.long_name = "which station this obs is for"
    stationIndex.instance_dimension = "station"
    stationIndex[...] = [
        3,
        2,
        1,
        0,
        2,
        3,
        3,
        3,
        1,
        1,
        0,
        2,
        3,
        1,
        0,
        1,
        2,
        3,
        2,
        3,
        3,
        3,
        1,
        1,
    ]

    t = [
        [-3, -2, -1],
        [1, 2, 3, 4, 5, 6, 7],
        [0.5, 1.5, 2.5, 3.5, 4.5],
        range(-2, 7),
    ]

    time = n.createVariable("time", "f8", ("obs",))
    time.standard_name = "time"
    time.long_name = "time of measurement"
    time.units = "days since 1970-01-01 00:00:00"
    time.bounds = "time_bounds"
    ssi = [0, 0, 0, 0]
    for i, si in enumerate(stationIndex[...]):
        time[i] = t[si][ssi[si]]
        ssi[si] += 1

    time_bounds = n.createVariable("time_bounds", "f8", ("obs", "bounds"))
    time_bounds[..., 0] = time[...] - 0.5
    time_bounds[..., 1] = time[...] + 0.5

    humidity = n.createVariable("humidity", "f8", ("obs",), fill_value=-999.9)
    humidity.standard_name = "specific_humidity"
    humidity.coordinates = "time lat lon alt station_name station_info"

    h = [
        numpy.arange(0, 3),
        numpy.arange(1, 71, 10),
        numpy.arange(2, 502, 100),
        numpy.arange(3, 9003, 1000),
    ]

    ssi = [0, 0, 0, 0]
    for i, si in enumerate(stationIndex[...]):
        humidity[i] = h[si][ssi[si]]
        ssi[si] += 1

    temp = n.createVariable("temp", "f8", ("obs",), fill_value=-999.9)
    temp.standard_name = "air_temperature"
    temp.units = "Celsius"
    temp.coordinates = "time lat lon alt station_name station_info"
    temp[...] = humidity[...] + 273.15

    n.close()

    return filename


def _make_indexed_contiguous_file(filename):
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeriesProfile"

    # 3 stations
    n.createDimension("station", 3)
    # 58 profiles spreadover 4 stations, each at a different time
    profile = n.createDimension("profile", 58)
    n.createDimension("obs", None)
    n.createDimension("name_strlen", 8)
    n.createDimension("bounds", 2)

    lon = n.createVariable("lon", "f8", ("station",))
    lon.standard_name = "longitude"
    lon.long_name = "station longitude"
    lon.units = "degrees_east"
    lon.bounds = "lon_bounds"
    lon[...] = [-23, 0, 67]

    lon_bounds = n.createVariable("lon_bounds", "f8", ("station", "bounds"))
    lon_bounds[...] = [[-24, -22], [-1, 1], [66, 68]]

    lat = n.createVariable("lat", "f8", ("station",))
    lat.standard_name = "latitude"
    lat.long_name = "station latitude"
    lat.units = "degrees_north"
    lat[...] = [-9, 2, 34]

    alt = n.createVariable("alt", "f8", ("station",))
    alt.long_name = "vertical distance above the surface"
    alt.standard_name = "height"
    alt.units = "m"
    alt.positive = "up"
    alt.axis = "Z"
    alt[...] = [0.5, 12.6, 23.7]

    station_name = n.createVariable(
        "station_name", "S1", ("station", "name_strlen")
    )
    station_name.long_name = "station name"
    station_name.cf_role = "timeseries_id"
    station_name[...] = numpy.array(
        [
            [x for x in "station1"],
            [x for x in "station2"],
            [x for x in "station3"],
        ]
    )

    profile = n.createVariable("profile", "i4", ("profile"))
    profile.cf_role = "profile_id"
    profile[...] = numpy.arange(58) + 100

    station_info = n.createVariable("station_info", "i4", ("station",))
    station_info.long_name = "some kind of station info"
    station_info[...] = [-10, -9, -8]

    stationIndex = n.createVariable("stationIndex", "i4", ("profile",))
    stationIndex.long_name = "which station this profile is for"
    stationIndex.instance_dimension = "station"
    stationIndex[...] = [
        2,
        1,
        0,
        2,
        1,
        1,
        0,
        2,
        1,
        0,
        1,
        2,
        2,
        1,
        1,
        2,
        1,
        0,
        2,
        1,
        1,
        0,
        2,
        1,
        0,
        1,
        2,
        2,
        1,
        1,
        2,
        1,
        0,
        2,
        1,
        1,
        0,
        2,
        1,
        0,
        1,
        2,
        2,
        1,
        1,
        2,
        1,
        0,
        2,
        1,
        1,
        0,
        2,
        1,
        0,
        1,
        2,
        2,
    ]
    # station N has list(stationIndex[...]).count(N) profiles

    row_size = n.createVariable("row_size", "i4", ("profile",))
    row_size.long_name = "number of observations for this profile"
    row_size.sample_dimension = "obs"
    row_size[...] = [
        1,
        4,
        1,
        3,
        2,
        2,
        3,
        3,
        1,
        2,
        2,
        3,
        2,
        2,
        2,
        2,
        1,
        2,
        1,
        3,
        3,
        2,
        1,
        3,
        1,
        3,
        2,
        3,
        1,
        3,
        3,
        2,
        2,
        2,
        1,
        1,
        1,
        3,
        1,
        1,
        2,
        1,
        1,
        3,
        3,
        2,
        2,
        2,
        2,
        1,
        2,
        3,
        3,
        3,
        2,
        3,
        1,
        1,
    ]  # sum = 118

    time = n.createVariable("time", "f8", ("profile",))
    time.standard_name = "time"
    time.long_name = "time"
    time.units = "days since 1970-01-01 00:00:00"
    time.bounds = "time_bounds"
    t0 = [3, 0, -3]
    ssi = [0, 0, 0]
    for i, si in enumerate(stationIndex[...]):
        time[i] = t0[si] + ssi[si]
        ssi[si] += 1

    time_bounds = n.createVariable("time_bounds", "f8", ("profile", "bounds"))
    time_bounds[..., 0] = time[...] - 0.5
    time_bounds[..., 1] = time[...] + 0.5

    z = n.createVariable("z", "f8", ("obs",))
    z.standard_name = "altitude"
    z.long_name = "height above mean sea level"
    z.units = "km"
    z.axis = "Z"
    z.positive = "up"
    z.bounds = "z_bounds"

    #        z0 = [1, 0, 3]
    #        i = 0
    #        for s, r in zip(stationIndex[...], row_size[...]):
    #            z[i:i+r] = z0[s] + numpy.sort(
    #                numpy.random.uniform(0, numpy.random.uniform(1, 2), r))
    #            i += r

    data = [
        3.51977705293769,
        0.521185292100177,
        0.575154265863394,
        1.08495843717095,
        1.37710968624395,
        2.07123455611723,
        3.47064474274781,
        3.88569849023813,
        4.81069254279537,
        0.264339600625496,
        0.915704970094182,
        0.0701532210336895,
        0.395517651420933,
        1.00657582854276,
        1.17721374303641,
        1.82189345615046,
        3.52424307197668,
        3.93200473199559,
        3.95715099603671,
        1.57047493027102,
        1.09938982652955,
        1.17768722826975,
        0.251803399458277,
        1.59673486865804,
        4.02868944763605,
        4.03749228832264,
        4.79858281590985,
        3.00019933315412,
        3.65124061660449,
        0.458463542157766,
        0.978678197083262,
        0.0561560792556281,
        0.31182013232255,
        3.33350065357286,
        4.33143904011861,
        0.377894196412131,
        1.63020681064712,
        2.00097025264771,
        3.76948048424458,
        0.572927165845568,
        1.29408313557905,
        1.81296270533192,
        0.387142669131077,
        0.693459187515738,
        1.69261930636298,
        1.38258797228361,
        1.82590759889566,
        3.34993297710761,
        0.725250730922501,
        1.38221693486728,
        1.59828555215646,
        1.59281225554253,
        0.452340646918555,
        0.976663373825433,
        1.12640496317618,
        3.19366847375422,
        3.37209133117904,
        3.40665008236976,
        3.53525896684001,
        4.10444186715724,
        0.14920937817654,
        0.0907197953552753,
        0.42527916794473,
        0.618685137936187,
        3.01900591447357,
        3.37205542289986,
        3.86957342976163,
        0.17175098751914,
        0.990040375014957,
        1.57011428605984,
        2.12140567043994,
        3.24374743730506,
        4.24042441581785,
        0.929509749153725,
        0.0711997786817564,
        2.25090028461898,
        3.31520955860746,
        3.49482624434274,
        3.96812568493549,
        1.5681807261767,
        1.79993011515465,
        0.068325990211909,
        0.124469638352167,
        3.31990436971169,
        3.84766748039389,
        0.451973490541035,
        1.24303219956085,
        1.30478004656262,
        0.351892459787624,
        0.683685812990457,
        0.788883736575568,
        3.73033428872491,
        3.99479807507392,
        0.811582011950481,
        1.2241242448019,
        1.25563109687369,
        2.16603674712822,
        3.00010622131408,
        3.90637137662453,
        0.589586644805982,
        0.104656387266266,
        0.961185900148304,
        1.05120351477824,
        1.29460917520233,
        2.10139985693684,
        3.64252693587415,
        3.91197236350995,
        4.56466622863717,
        0.556476687600461,
        0.783717448678148,
        0.910917550635007,
        1.59750076220451,
        1.97101264162631,
        0.714693043642084,
        0.904381625638779,
        1.03767817888021,
        4.10124675852254,
        3.1059214185543,
    ]
    data = numpy.around(data, 2)
    z[...] = data

    z_bounds = n.createVariable("z_bounds", "f8", ("obs", "bounds"))
    z_bounds[..., 0] = z[...] - 0.01
    z_bounds[..., 1] = z[...] + 0.01

    humidity = n.createVariable("humidity", "f8", ("obs",), fill_value=-999.9)
    humidity.standard_name = "specific_humidity"
    humidity.coordinates = (
        "time lat lon alt z station_name station_info profile"
    )

    data *= 10
    data = numpy.around(data, 2)
    humidity[...] = data

    temp = n.createVariable("temp", "f8", ("obs",), fill_value=-999.9)
    temp.standard_name = "air_temperature"
    temp.units = "Celsius"
    temp.coordinates = "time lat lon alt z station_name station_info profile"

    data += 2731.5
    data = numpy.around(data, 2)
    temp[...] = data

    n.close()

    return filename


def _make_external_files():
    """TODO."""

    def _pp(
        filename,
        parent=False,
        external=False,
        combined=False,
        external_missing=False,
    ):
        """TODO."""
        nc = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

        nc.createDimension("grid_latitude", 10)
        nc.createDimension("grid_longitude", 9)

        nc.Conventions = "CF-" + VN
        if parent:
            nc.external_variables = "areacella"

        if parent or combined or external_missing:
            grid_latitude = nc.createVariable(
                dimensions=("grid_latitude",),
                datatype="f8",
                varname="grid_latitude",
            )
            grid_latitude.setncatts(
                {"units": "degrees", "standard_name": "grid_latitude"}
            )
            grid_latitude[...] = range(10)

            grid_longitude = nc.createVariable(
                dimensions=("grid_longitude",),
                datatype="f8",
                varname="grid_longitude",
            )
            grid_longitude.setncatts(
                {"units": "degrees", "standard_name": "grid_longitude"}
            )
            grid_longitude[...] = range(9)

            latitude = nc.createVariable(
                dimensions=("grid_latitude", "grid_longitude"),
                datatype="i4",
                varname="latitude",
            )
            latitude.setncatts(
                {"units": "degree_N", "standard_name": "latitude"}
            )

            latitude[...] = numpy.arange(90).reshape(10, 9)

            longitude = nc.createVariable(
                dimensions=("grid_longitude", "grid_latitude"),
                datatype="i4",
                varname="longitude",
            )
            longitude.setncatts(
                {"units": "degreeE", "standard_name": "longitude"}
            )
            longitude[...] = numpy.arange(90).reshape(9, 10)

            eastward_wind = nc.createVariable(
                dimensions=("grid_latitude", "grid_longitude"),
                datatype="f8",
                varname=u"eastward_wind",
            )
            eastward_wind.coordinates = u"latitude longitude"
            eastward_wind.standard_name = "eastward_wind"
            eastward_wind.cell_methods = (
                "grid_longitude: mean (interval: 1 day comment: ok) "
                "grid_latitude: maximum where sea"
            )
            eastward_wind.cell_measures = "area: areacella"
            eastward_wind.units = "m s-1"
            eastward_wind[...] = numpy.arange(90).reshape(10, 9) - 45.5

        if external or combined:
            areacella = nc.createVariable(
                dimensions=("grid_longitude", "grid_latitude"),
                datatype="f8",
                varname="areacella",
            )
            areacella.setncatts({"units": "m2", "standard_name": "cell_area"})
            areacella[...] = numpy.arange(90).reshape(9, 10) + 100000.5

        nc.close()

    parent_file = os.path.join(
        os.path.dirname(os.path.abspath(__file__)), "parent.nc"
    )
    external_file = os.path.join(
        os.path.dirname(os.path.abspath(__file__)), "external.nc"
    )
    combined_file = os.path.join(
        os.path.dirname(os.path.abspath(__file__)), "combined.nc"
    )
    external_missing_file = os.path.join(
        os.path.dirname(os.path.abspath(__file__)), "external_missing.nc"
    )

    _pp(parent_file, parent=True)
    _pp(external_file, external=True)
    _pp(combined_file, combined=True)
    _pp(external_missing_file, external_missing=True)

    return parent_file, external_file, combined_file, external_missing_file


def _make_gathered_file(filename):
    """TODO."""

    def _jj(shape, list_values):
        array = numpy.ma.masked_all(shape)
        for i, (index, x) in enumerate(numpy.ndenumerate(array)):
            if i in list_values:
                array[index] = i
        return array

    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN

    time = n.createDimension("time", 2)
    height = n.createDimension("height", 3)
    lat = n.createDimension("lat", 4)
    lon = n.createDimension("lon", 5)
    p = n.createDimension("p", 6)

    list1 = n.createDimension("list1", 4)
    list2 = n.createDimension("list2", 9)
    list3 = n.createDimension("list3", 14)

    # Dimension coordinate variables
    time = n.createVariable("time", "f8", ("time",))
    time.standard_name = "time"
    time.units = "days since 2000-1-1"
    time[...] = [31, 60]

    height = n.createVariable("height", "f8", ("height",))
    height.standard_name = "height"
    height.units = "metres"
    height.positive = "up"
    height[...] = [0.5, 1.5, 2.5]

    lat = n.createVariable("lat", "f8", ("lat",))
    lat.standard_name = "latitude"
    lat.units = "degrees_north"
    lat[...] = [-90, -85, -80, -75]

    p = n.createVariable("p", "i4", ("p",))
    p.long_name = "pseudolevel"
    p[...] = [1, 2, 3, 4, 5, 6]

    # Auxiliary coordinate variables

    aux0 = n.createVariable("aux0", "f8", ("list1",))
    aux0.standard_name = "longitude"
    aux0.units = "degrees_east"
    aux0[...] = numpy.arange(list1.size)

    aux1 = n.createVariable("aux1", "f8", ("list3",))
    aux1[...] = numpy.arange(list3.size)

    aux2 = n.createVariable("aux2", "f8", ("time", "list3", "p"))
    aux2[...] = numpy.arange(time.size * list3.size * p.size).reshape(
        time.size, list3.size, p.size
    )

    aux3 = n.createVariable("aux3", "f8", ("p", "list3", "time"))
    aux3[...] = numpy.arange(p.size * list3.size * time.size).reshape(
        p.size, list3.size, time.size
    )

    aux4 = n.createVariable("aux4", "f8", ("p", "time", "list3"))
    aux4[...] = numpy.arange(p.size * time.size * list3.size).reshape(
        p.size, time.size, list3.size
    )

    aux5 = n.createVariable("aux5", "f8", ("list3", "p", "time"))
    aux5[...] = numpy.arange(list3.size * p.size * time.size).reshape(
        list3.size, p.size, time.size
    )

    aux6 = n.createVariable("aux6", "f8", ("list3", "time"))
    aux6[...] = numpy.arange(list3.size * time.size).reshape(
        list3.size, time.size
    )

    aux7 = n.createVariable("aux7", "f8", ("lat",))
    aux7[...] = numpy.arange(lat.size)

    aux8 = n.createVariable(
        "aux8",
        "f8",
        (
            "lon",
            "lat",
        ),
    )
    aux8[...] = numpy.arange(lon.size * lat.size).reshape(lon.size, lat.size)

    aux9 = n.createVariable("aux9", "f8", ("time", "height"))
    aux9[...] = numpy.arange(time.size * height.size).reshape(
        time.size, height.size
    )

    # List variables
    list1 = n.createVariable("list1", "i", ("list1",))
    list1.compress = "lon"
    list1[...] = [0, 1, 3, 4]

    list2 = n.createVariable("list2", "i", ("list2",))
    list2.compress = "lat lon"
    list2[...] = [0, 1, 5, 6, 13, 14, 17, 18, 19]

    list3 = n.createVariable("list3", "i", ("list3",))
    list3.compress = "height lat lon"
    array = _jj(
        (3, 4, 5), [0, 1, 5, 6, 13, 14, 25, 26, 37, 38, 48, 49, 58, 59]
    )
    list3[...] = array.compressed()

    # Data variables
    temp1 = n.createVariable(
        "temp1", "f8", ("time", "height", "lat", "list1", "p")
    )
    temp1.long_name = "temp1"
    temp1.units = "K"
    temp1.coordinates = "aux0 aux7 aux8 aux9"
    temp1[...] = numpy.arange(2 * 3 * 4 * 4 * 6).reshape(2, 3, 4, 4, 6)

    temp2 = n.createVariable("temp2", "f8", ("time", "height", "list2", "p"))
    temp2.long_name = "temp2"
    temp2.units = "K"
    temp2.coordinates = "aux7 aux8 aux9"
    temp2[...] = numpy.arange(2 * 3 * 9 * 6).reshape(2, 3, 9, 6)

    temp3 = n.createVariable("temp3", "f8", ("time", "list3", "p"))
    temp3.long_name = "temp3"
    temp3.units = "K"
    temp3.coordinates = "aux0 aux1 aux2 aux3 aux4 aux5 aux6 aux7 aux8 aux9"
    temp3[...] = numpy.arange(2 * 14 * 6).reshape(2, 14, 6)

    n.close()

    return filename


# --------------------------------------------------------------------
# Geometry files
# --------------------------------------------------------------------
def _make_geometry_1_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = (
        "Make a netCDF file with 2 node coordinates variables, each of "
        "which has a corresponding auxiliary coordinate variable."
    )

    n.createDimension("time", 4)
    n.createDimension("instance", 2)
    n.createDimension("node", 5)

    t = n.createVariable("time", "i4", ("time",))
    t.units = "seconds since 2016-11-07 20:00 UTC"
    t[...] = [1, 2, 3, 4]

    lat = n.createVariable("lat", "f8", ("instance",))
    lat.standard_name = "latitude"
    lat.units = "degrees_north"
    lat.nodes = "y"
    lat[...] = [30, 50]

    lon = n.createVariable("lon", "f8", ("instance",))
    lon.standard_name = "longitude"
    lon.units = "degrees_east"
    lon.nodes = "x"
    lon[...] = [10, 60]

    datum = n.createVariable("datum", "i4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.longitude_of_prime_meridian = 0.0
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "line"
    geometry_container.node_count = "node_count"
    geometry_container.node_coordinates = "x y"

    node_count = n.createVariable("node_count", "i4", ("instance",))
    node_count[...] = [3, 2]

    x = n.createVariable("x", "f8", ("node",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [30, 10, 40, 50, 50]

    y = n.createVariable("y", "f8", ("node",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [10, 30, 40, 60, 50]

    pr = n.createVariable("pr", "f8", ("instance", "time"))
    pr.standard_name = "precipitation_amount"
    pr.units = "kg m-2"
    pr.coordinates = "time lat lon"
    pr.grid_mapping = "datum"
    pr.geometry = "geometry_container"
    pr[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "time lat lon"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[10, 20, 30, 40], [50, 60, 70, 80]]

    n.close()

    return filename


def _make_geometry_2_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = (
        "A netCDF file with 3 node coordinates variables, only two of "
        "which have a corresponding auxiliary coordinate variable."
    )

    n.createDimension("time", 4)
    n.createDimension("instance", 2)
    n.createDimension("node", 5)

    t = n.createVariable("time", "i4", ("time",))
    t.units = "seconds since 2016-11-07 20:00 UTC"
    t[...] = [1, 2, 3, 4]

    lat = n.createVariable("lat", "f8", ("instance",))
    lat.standard_name = "latitude"
    lat.units = "degrees_north"
    lat.nodes = "y"
    lat[...] = [30, 50]

    lon = n.createVariable("lon", "f8", ("instance",))
    lon.standard_name = "longitude"
    lon.units = "degrees_east"
    lon.nodes = "x"
    lon[...] = [10, 60]

    datum = n.createVariable("datum", "i4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.longitude_of_prime_meridian = 0.0
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "line"
    geometry_container.node_count = "node_count"
    geometry_container.node_coordinates = "x y z"

    node_count = n.createVariable("node_count", "i4", ("instance",))
    node_count[...] = [3, 2]

    x = n.createVariable("x", "f8", ("node",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [30, 10, 40, 50, 50]

    y = n.createVariable("y", "f8", ("node",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [10, 30, 40, 60, 50]

    z = n.createVariable("z", "f8", ("node",))
    z.units = "m"
    z.standard_name = "altitude"
    z.axis = "Z"
    z[...] = [100, 150, 200, 125, 80]

    someData = n.createVariable("someData", "f8", ("instance", "time"))
    someData.coordinates = "time lat lon"
    someData.grid_mapping = "datum"
    someData.geometry = "geometry_container"
    someData[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "time lat lon"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    n.close()

    return filename


def _make_geometry_3_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = (
        "A netCDF file with 3 node coordinates variables, each of which "
        "contains only one point, only two of which have a corresponding "
        "auxiliary coordinate variables. There is no node count variable."
    )

    n.createDimension("time", 4)
    n.createDimension("instance", 3)

    t = n.createVariable("time", "i4", ("time",))
    t.units = "seconds since 2016-11-07 20:00 UTC"
    t[...] = [1, 2, 3, 4]

    lat = n.createVariable("lat", "f8", ("instance",))
    lat.standard_name = "latitude"
    lat.units = "degrees_north"
    lat.nodes = "y"
    lat[...] = [30, 50, 70]

    lon = n.createVariable("lon", "f8", ("instance",))
    lon.standard_name = "longitude"
    lon.units = "degrees_east"
    lon.nodes = "x"
    lon[...] = [10, 60, 80]

    datum = n.createVariable("datum", "i4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.longitude_of_prime_meridian = 0.0
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "point"
    geometry_container.node_coordinates = "x y z"

    x = n.createVariable("x", "f8", ("instance",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [30, 10, 40]

    y = n.createVariable("y", "f8", ("instance",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [10, 30, 40]

    z = n.createVariable("z", "f8", ("instance",))
    z.units = "m"
    z.standard_name = "altitude"
    z.axis = "Z"
    z[...] = [100, 150, 200]

    someData_1 = n.createVariable("someData_1", "f8", ("instance", "time"))
    someData_1.coordinates = "lat lon"
    someData_1.grid_mapping = "datum"
    someData_1.geometry = "geometry_container"
    someData_1[...] = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "lat lon"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[10, 20, 30, 40], [50, 60, 70, 80], [90, 100, 110, 120]]

    n.close()

    return filename


def _make_geometry_4_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = (
        "A netCDF file with 2 node coordinates variables, none of which "
        "have a corresponding auxiliary coordinate variable."
    )

    n.createDimension("time", 4)
    n.createDimension("instance", 2)
    n.createDimension("node", 5)
    n.createDimension("strlen", 2)

    # Variables
    t = n.createVariable("time", "i4", ("time",))
    t.standard_name = "time"
    t.units = "days since 2000-01-01"
    t[...] = [1, 2, 3, 4]

    instance_id = n.createVariable("instance_id", "S1", ("instance", "strlen"))
    instance_id.cf_role = "timeseries_id"
    instance_id[...] = [["x", "1"], ["y", "2"]]

    datum = n.createVariable("datum", "i4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.longitude_of_prime_meridian = 0.0
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "line"
    geometry_container.node_count = "node_count"
    geometry_container.node_coordinates = "x y"

    node_count = n.createVariable("node_count", "i4", ("instance",))
    node_count[...] = [3, 2]

    x = n.createVariable("x", "f8", ("node",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [30, 10, 40, 50, 50]

    y = n.createVariable("y", "f8", ("node",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [10, 30, 40, 60, 50]

    someData_1 = n.createVariable("someData_1", "f8", ("instance", "time"))
    someData_1.coordinates = "instance_id"
    someData_1.grid_mapping = "datum"
    someData_1.geometry = "geometry_container"
    someData_1[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "instance_id"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[10, 20, 30, 40], [50, 60, 70, 80]]

    n.close()

    return filename


def _make_interior_ring_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    # Global attributes
    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = "TODO"

    # Dimensions
    n.createDimension("time", 4)
    n.createDimension("instance", 2)
    n.createDimension("node", 13)
    n.createDimension("part", 4)
    n.createDimension("strlen", 2)

    # Variables
    t = n.createVariable("time", "i4", ("time",))
    t.standard_name = "time"
    t.units = "days since 2000-01-01"
    t[...] = [1, 2, 3, 4]

    instance_id = n.createVariable("instance_id", "S1", ("instance", "strlen"))
    instance_id.cf_role = "timeseries_id"
    instance_id[...] = [["x", "1"], ["y", "2"]]

    x = n.createVariable("x", "f8", ("node",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [20, 10, 0, 5, 10, 15, 10, 20, 10, 0, 50, 40, 30]

    y = n.createVariable("y", "f8", ("node",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [0, 15, 0, 5, 10, 5, 5, 20, 35, 20, 0, 15, 0]

    z = n.createVariable("z", "f8", ("instance",))
    z.units = "m"
    z.standard_name = "altitude"
    z.positive = "up"
    z.axis = "Z"
    z[...] = [5000, 20]

    lat = n.createVariable("lat", "f8", ("instance",))
    lat.units = "degrees_north"
    lat.standard_name = "latitude"
    lat.nodes = "y"
    lat[...] = [25, 7]

    lon = n.createVariable("lon", "f8", ("instance",))
    lon.units = "degrees_east"
    lon.standard_name = "longitude"
    lon.nodes = "x"
    lon[...] = [10, 40]

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "polygon"
    geometry_container.node_count = "node_count"
    geometry_container.node_coordinates = "x y"
    geometry_container.grid_mapping = "datum"
    geometry_container.coordinates = "lat lon"
    geometry_container.part_node_count = "part_node_count"
    geometry_container.interior_ring = "interior_ring"

    node_count = n.createVariable("node_count", "i4", ("instance"))
    node_count[...] = [10, 3]

    part_node_count = n.createVariable("part_node_count", "i4", ("part"))
    part_node_count[...] = [3, 4, 3, 3]

    interior_ring = n.createVariable("interior_ring", "i4", ("part"))
    interior_ring[...] = [0, 1, 0, 0]

    datum = n.createVariable("datum", "f4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563
    datum.longitude_of_prime_meridian = 0.0

    pr = n.createVariable("pr", "f8", ("instance", "time"))
    pr.standard_name = "preciptitation_amount"
    pr.standard_units = "kg m-2"
    pr.coordinates = "time lat lon z instance_id"
    pr.grid_mapping = "datum"
    pr.geometry = "geometry_container"
    pr[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "time lat lon z instance_id"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    n.close()

    return filename


def _make_interior_ring_file_2(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")

    # Global attributes
    n.Conventions = "CF-" + VN
    n.featureType = "timeSeries"
    n.comment = "TODO"

    # Dimensions
    n.createDimension("time", 4)
    n.createDimension("instance", 2)
    n.createDimension("node", 13)
    n.createDimension("part", 4)
    n.createDimension("strlen", 2)

    # Variables
    t = n.createVariable("time", "i4", ("time",))
    t.standard_name = "time"
    t.units = "days since 2000-01-01"
    t[...] = [1, 2, 3, 4]

    instance_id = n.createVariable("instance_id", "S1", ("instance", "strlen"))
    instance_id.cf_role = "timeseries_id"
    instance_id[...] = [["x", "1"], ["y", "2"]]

    x = n.createVariable("x", "f8", ("node",))
    x.units = "degrees_east"
    x.standard_name = "longitude"
    x.axis = "X"
    x[...] = [20, 10, 0, 5, 10, 15, 10, 20, 10, 0, 50, 40, 30]

    y = n.createVariable("y", "f8", ("node",))
    y.units = "degrees_north"
    y.standard_name = "latitude"
    y.axis = "Y"
    y[...] = [0, 15, 0, 5, 10, 5, 5, 20, 35, 20, 0, 15, 0]

    z = n.createVariable("z", "f8", ("node",))
    z.units = "m"
    z.standard_name = "altitude"
    z.axis = "Z"
    z[...] = [1, 2, 4, 2, 3, 4, 5, 5, 1, 4, 3, 2, 1]

    lat = n.createVariable("lat", "f8", ("instance",))
    lat.units = "degrees_north"
    lat.standard_name = "latitude"
    lat.nodes = "y"
    lat[...] = [25, 7]

    lon = n.createVariable("lon", "f8", ("instance",))
    lon.units = "degrees_east"
    lon.standard_name = "longitude"
    lon.nodes = "x"
    lon[...] = [10, 40]

    geometry_container = n.createVariable("geometry_container", "i4", ())
    geometry_container.geometry_type = "polygon"
    geometry_container.node_count = "node_count"
    geometry_container.node_coordinates = "x y z"
    geometry_container.grid_mapping = "datum"
    geometry_container.coordinates = "lat lon"
    geometry_container.part_node_count = "part_node_count"
    geometry_container.interior_ring = "interior_ring"

    node_count = n.createVariable("node_count", "i4", ("instance"))
    node_count[...] = [10, 3]

    part_node_count = n.createVariable("part_node_count", "i4", ("part"))
    part_node_count[...] = [3, 4, 3, 3]

    interior_ring = n.createVariable("interior_ring", "i4", ("part"))
    interior_ring[...] = [0, 1, 0, 0]

    datum = n.createVariable("datum", "f4", ())
    datum.grid_mapping_name = "latitude_longitude"
    datum.semi_major_axis = 6378137.0
    datum.inverse_flattening = 298.257223563
    datum.longitude_of_prime_meridian = 0.0

    pr = n.createVariable("pr", "f8", ("instance", "time"))
    pr.standard_name = "preciptitation_amount"
    pr.standard_units = "kg m-2"
    pr.coordinates = "time lat lon z instance_id"
    pr.grid_mapping = "datum"
    pr.geometry = "geometry_container"
    pr[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    someData_2 = n.createVariable("someData_2", "f8", ("instance", "time"))
    someData_2.coordinates = "time lat lon z instance_id"
    someData_2.grid_mapping = "datum"
    someData_2.geometry = "geometry_container"
    someData_2[...] = [[1, 2, 3, 4], [5, 6, 7, 8]]

    n.close()

    return filename


def _make_string_char_file(filename):
    """See n.comment for details."""
    n = netCDF4.Dataset(filename, "w", format="NETCDF4")

    n.Conventions = "CF-" + VN
    n.comment = "A netCDF file with variables of string and char data types"

    n.createDimension("dim1", 1)
    n.createDimension("time", 4)
    n.createDimension("lat", 2)
    n.createDimension("lon", 3)
    n.createDimension("strlen8", 8)
    n.createDimension("strlen7", 7)
    n.createDimension("strlen5", 5)
    n.createDimension("strlen3", 3)

    months = numpy.array(["January", "February", "March", "April"], dtype="S8")

    months_m = numpy.ma.array(
        months, dtype="S7", mask=[0, 1, 0, 0], fill_value=b""
    )

    numbers = numpy.array(
        [["one", "two", "three"], ["four", "five", "six"]], dtype="S5"
    )

    s_months4 = n.createVariable("s_months4", str, ("time",))
    s_months4.long_name = "string: Four months"
    s_months4[:] = months

    s_months1 = n.createVariable("s_months1", str, ("dim1",))
    s_months1.long_name = "string: One month"
    s_months1[:] = numpy.array(["December"], dtype="S8")

    s_months0 = n.createVariable("s_months0", str, ())
    s_months0.long_name = "string: One month (scalar)"
    s_months0[:] = numpy.array(["May"], dtype="S3")

    s_numbers = n.createVariable("s_numbers", str, ("lat", "lon"))
    s_numbers.long_name = "string: Two dimensional"
    s_numbers[...] = numbers

    s_months4m = n.createVariable("s_months4m", str, ("time",))
    s_months4m.long_name = "string: Four months (masked)"
    array = months.copy()
    array[1] = ""
    s_months4m[...] = array

    c_months4 = n.createVariable("c_months4", "S1", ("time", "strlen8"))
    c_months4.long_name = "char: Four months"
    c_months4[:, :] = netCDF4.stringtochar(months)

    c_months1 = n.createVariable("c_months1", "S1", ("dim1", "strlen8"))
    c_months1.long_name = "char: One month"
    c_months1[:] = netCDF4.stringtochar(numpy.array(["December"], dtype="S8"))
    c_months0 = n.createVariable("c_months0", "S1", ("strlen3",))
    c_months0.long_name = "char: One month (scalar)"
    c_months0[:] = numpy.array(list("May"))

    c_numbers = n.createVariable("c_numbers", "S1", ("lat", "lon", "strlen5"))
    c_numbers.long_name = "char: Two dimensional"
    c_numbers[...] = netCDF4.stringtochar(numbers)

    c_months4m = n.createVariable("c_months4m", "S1", ("time", "strlen7"))
    c_months4m.long_name = "char: Four months (masked)"
    array = netCDF4.stringtochar(months_m)
    c_months4m[:, :] = array

    n.close()

    return filename


def _make_broken_bounds_cdl(filename):
    with open(filename, mode="w") as f:
        f.write(
            """netcdf broken_bounds {
dimensions:
      lat = 180 ;
      bnds = 2 ;
      lon = 288 ;
      time = UNLIMITED ; // (1825 currently)
variables:
      double lat(lat) ;
           lat:long_name = "latitude" ;
           lat:units = "degrees_north" ;
           lat:axis = "Y" ;
           lat:bounds = "lat_bnds" ;
           lat:standard_name = "latitude" ;
           lat:cell_methods = "time: point" ;
      double lat_bnds(lat, bnds) ;
           lat_bnds:long_name = "latitude bounds" ;
           lat_bnds:units = "degrees_north" ;
           lat_bnds:axis = "Y" ;
      double lon(lon) ;
           lon:long_name = "longitude" ;
           lon:units = "degrees_east" ;
           lon:axis = "X" ;
           lon:bounds = "lon_bnds" ;
           lon:standard_name = "longitude" ;
           lon:cell_methods = "time: point" ;
      double lon_bnds(lon, bnds) ;
           lon_bnds:long_name = "longitude bounds" ;
           lon_bnds:units = "m" ;
           lon_bnds:axis = "X" ;
      float pr(time, lat, lon) ;
           pr:long_name = "Precipitation" ;
           pr:units = "kg m-2 s-1" ;
           pr:missing_value = 1.e+20f ;
           pr:_FillValue = 1.e+20f ;
           pr:cell_methods = "area: time: mean" ;
           pr:cell_measures = "area: areacella" ;
           pr:standard_name = "precipitation_flux" ;
           pr:interp_method = "conserve_order1" ;
           pr:original_name = "pr" ;
      double time(time) ;
           time:long_name = "time" ;
           time:units = "days since 1850-01-01 00:00:00" ;
           time:axis = "T" ;
           time:calendar_type = "noleap" ;
           time:calendar = "noleap" ;
           time:bounds = "time_bnds" ;
           time:standard_name = "time" ;
           time:description = "Temporal mean" ;
      double time_bnds(time, bnds) ;
           time_bnds:long_name = "time axis boundaries" ;
           time_bnds:units = "days since 1850-01-01 00:00:00" ;

// global attributes:
           :external_variables = "areacella" ;
           :Conventions = "CF-"""
            + VN
            + """" ;
           :source = "model" ;
           :comment = "Bounds variable has incompatible units to its parent coordinate variable" ;
}
"""
        )


contiguous_file = _make_contiguous_file("DSG_timeSeries_contiguous.nc")
indexed_file = _make_indexed_file("DSG_timeSeries_indexed.nc")
indexed_contiguous_file = _make_indexed_contiguous_file(
    "DSG_timeSeriesProfile_indexed_contiguous.nc"
)

(
    parent_file,
    external_file,
    combined_file,
    external_missing_file,
) = _make_external_files()

geometry_1_file = _make_geometry_1_file("geometry_1.nc")
geometry_2_file = _make_geometry_2_file("geometry_2.nc")
geometry_3_file = _make_geometry_3_file("geometry_3.nc")
geometry_4_file = _make_geometry_4_file("geometry_4.nc")
interior_ring_file = _make_interior_ring_file("geometry_interior_ring.nc")
interior_ring_file_2 = _make_interior_ring_file_2(
    "geometry_interior_ring_2.nc"
)

gathered = _make_gathered_file("gathered.nc")

string_char_file = _make_string_char_file("string_char.nc")

broken_bounds_file = _make_broken_bounds_cdl("broken_bounds.cdl")

if __name__ == "__main__":
    print("Run date:", datetime.datetime.now())
    cf.environment()
    print()
    unittest.main(verbosity=2)
