Add a unit test to catch the errors with dimensions of size 1 being read in incorrectly by cdf_to_xarray

[bryan-harter]

See this PR here: #289

We accidentally were squeezing things, we want to make sure we don't do that.

Here was code I was testing with:

import os
import numpy as np
import xarray as xr

from cdflib.xarray import cdf_to_xarray, xarray_to_cdf

if os.path.exists("hello.cdf"):
    os.remove("hello.cdf")

sample_global_attributes = {
    "Project": "Hail Mary",
    "Source_name": "Thin Air",
    "Discipline": "None",
    "Data_type": "counts",
    "Descriptor": "Midichlorians in unicorn blood",
    "Data_version": "3.14",
    "Logical_file_id": "SEVENTEEN",
    "PI_name": "Darth Vader",
    "PI_affiliation": "Dark Side",
    "TEXT": "AHHHHH",
    "Instrument_type": "Banjo",
    "Mission_group": "Impossible",
    "Logical_source": ":)",
    "Logical_source_description": ":(",
}
sample_variable_attributes = {
    "CATDESC": "data",
    "DISPLAY_TYPE": "spectrogram",
    "FIELDNAM": "test",
    "FORMAT": "test",
    "UNITS": "test",
    "VALIDMIN": 0,
    "VALIDMAX": 10,
    "FILLVAL": np.int64(-9223372036854775808),
}
sample_data_variable_attributes = sample_variable_attributes | {"VAR_TYPE": "data", "LABLAXIS": "test"}
sample_support_variable_attributes = sample_variable_attributes | {"VAR_TYPE": "support_data"}

var_data = [[1, 2, 3]]
var_dims = ["epoch", "direction"]
data = xr.Variable(var_dims, var_data, sample_data_variable_attributes | {"DEPEND_0": "epoch", "DEPEND_1": "direction"})
support_data = [1, 2, 3]
support_dims = ["direction"]
support = xr.Variable(
    support_dims, support_data, sample_support_variable_attributes | {"DEPEND_1": "direction"}
)
epoch_data = [1]
epoch_dims = ["epoch"]
epoch = xr.Variable(epoch_dims, epoch_data, sample_support_variable_attributes)
dir_data = [1, 2, 3]
dir_dims = ["direction"]
direction = xr.Variable(dir_dims, dir_data, sample_support_variable_attributes)

ds = xr.Dataset(
    data_vars={"data": data, "epoch": epoch, "direction": direction, "support": support}, attrs=sample_global_attributes
)

xarray_to_cdf(ds, "hello.cdf", auto_fix_depends=False, terminate_on_warning=True)

x = cdf_to_xarray("hello.cdf")

print(x)

if os.path.exists("hello.cdf"):
    os.remove("hello.cdf")