'''import json
import os

import numpy as np
import pandas as pd
from pandas.util.testing import assert_frame_equal

from plio.io.io_bae import socetset_keywords_to_dict, read_gpf, save_gpf, read_ipf, save_ipf
from plio.examples import get_path

import pytest

@pytest.fixture
def insight_gpf():
    return get_path('InSightE08_XW.gpf')

@pytest.fixture
def example_str_id_gpf():
    return get_path('InSightE08_string_id.gpf')

@pytest.fixture()
def insight_expected_gpf():
    dtype_dict = {'point_id': 'str',
               'stat': 'int32',
               'known': 'int32',
               'lat_Y_North': 'float64',
               'long_X_East': 'float64',
               'ht': 'float64',
               'sig0': 'float64',
               'sig1': 'float64',
               'sig2': 'float64',
               'res0': 'float64',
               'res1': 'float64',
               'res2': 'float64'}
    return pd.read_csv(get_path('InSightE08_XW.csv'), dtype=dtype_dict)

@pytest.fixture
def insight_ipf():
    return get_path('P20_008845_1894_XN_09N203W.ipf')

@pytest.fixture
def example_str_id_ipf():
    return get_path('example_string_id_ipf.ipf')

@pytest.fixture()
def insight_expected_ipf():
    dtype_dict = {'pt_id': 'str',
                  'val': 'int32',
                  'fid_val': 'int32',
                  'no_obs': 'int32',
                  'l.': 'float64',
                  's.': 'float64',
                  'sig_l': 'float64',
                  'sig_s': 'float64',
                  'res_l': 'float64',
                  'res_s': 'float64',
                  'fid_x': 'float64',
                  'fid_y': 'float64'}
    return pd.read_csv(get_path('P20_008845_1894_XN_09N203W.csv'), dtype=dtype_dict)

@pytest.mark.parametrize('ipf, expected', [([insight_ipf()],insight_expected_ipf())])
def test_read_ipf(ipf, expected):
    df = read_ipf(ipf)
    assert_frame_equal(df, expected)

@pytest.mark.parametrize('gpf, expected', [(insight_gpf(),insight_expected_gpf())])
def test_read_gpf(gpf, expected):
    df = read_gpf(gpf)
    assert_frame_equal(df, expected)

@pytest.mark.parametrize('ipf, file', [(insight_ipf(), 'plio/io/tests/temp')])
def test_write_ipf(ipf, file):
    df = read_ipf(ipf)
    save_ipf(df, file)

    file = os.path.join(file, 'P20_008845_1894_XN_09N203W.ipf')

    with open(ipf) as f:
        fl = f.readlines()

    with open(file) as f:
        fs = f.readlines()

    # Check that the header is the same
    for i in range(3):
        assert fl[i] == fs[i]

    truth_arr = [line.split() for line in open(ipf, 'r')][3:]
    truth_arr = np.hstack(np.array(truth_arr))
    truth_arr = truth_arr.reshape(-1, 12)

    test_arr  = [line.split() for line in open(file, 'r')][3:]
    test_arr = np.hstack(np.array(test_arr))
    test_arr = test_arr.reshape(-1, 12)

    assert (truth_arr == test_arr).all()

@pytest.mark.parametrize('ipf, file', [(example_str_id_ipf(), 'plio/io/tests/temp')])
def test_write_str_id_ipf(ipf, file):
    df = read_ipf(ipf)
    save_ipf(df, file)
    file = os.path.join(file, 'example_string_id_ipf.ipf')

    with open(ipf) as f:
        fl = f.readlines()

    with open(file) as f:
        fs = f.readlines()
    
    # Quick check to make sure that length of IPF files matches
    #  otherwise, the test that follows will be invalid
    assert len(fl) == len(fs)

    # Test that every 5th line (the lines containing the point ID and integer flags) matches
    for i in range(3,len(fs),6):
        assert fs[i] == fl[i]

@pytest.mark.parametrize('gpf, file', [(insight_gpf(), 'out.gpf')])
def test_write_gpf(gpf, file):
    """
    We test by manually comparing files and not using filecmp so that we
    are not testing float point precision differences, e.g. 0.0 == 0.00000000.
    """
    df = read_gpf(gpf)
    save_gpf(df, file)

    with open(gpf) as f:
        fl = f.readlines()

    with open(file) as f:
        fs = f.readlines()

    # Check that the header is the same
    for i in range(3):
        assert fl[i] == fs[i]

    truth_arr = np.genfromtxt(gpf, skip_header=3)
    test_arr = np.genfromtxt(file, skip_header=3)

    np.testing.assert_array_almost_equal(truth_arr, test_arr)

    # np.testing.assert_array_almost_equal(truth_arr, test_arr)

@pytest.mark.parametrize('gpf, file', [(example_str_id_gpf(), 'out.gpf')])
def test_write_str_id_gpf(gpf, file):
    """
    This test makes sure that the point IDs of a GPF whose point IDs only contain numbers,
    are written correctly when saving to disk
    """
    df = read_gpf(gpf)
    save_gpf(df, file)

    with open(gpf) as f:
        fl = f.readlines()

    with open(file) as f:
        fs = f.readlines()
    
    # Quick check to make sure that length of GPF files matches
    #  otherwise, the test that follows will be invalid
    assert len(fl) == len(fs)

    # Test that every 5th line (the lines containing the point ID and integer flags) matches
    for i in range(3,len(fs),5):
        assert fs[i] == fl[i]

@pytest.mark.parametrize('gpf', [(example_str_id_gpf())])
def test_gpf_dtypes(gpf):
    """
    This test makes sure that a GPF whose point IDs only contain numbers
    are always treated as strings after they're read in.
    """
    # Read the GPF file under test into a pandas dataframe
    df = read_gpf(gpf)
    
    # Truth list of column data types
    truth_dtypes = ['O','int32','int32','float64','float64','float64','float64','float64','float64','float64','float64','float64']
    
    # Test list of column data types
    test_dtypes = list(df.dtypes)
    
    # Check that the type of each column matches the truth list
    assert truth_dtypes == test_dtypes

@pytest.mark.parametrize('ipf', [(example_str_id_ipf())])
def test_ipf_dtypes(ipf):
    """
    This test makes sure that a IPF whose point IDs only contain numbers
    are always treated as strings after they're read in.
    """
    # Read the IPF file under test into a pandas dataframe
    df = read_ipf(ipf)
    
    # Truth list of column data types
    truth_dtypes = ['O','int32','int32','int32','float64','float64','float64','float64','float64','float64','float64','float64', 'O']
    
    # Test list of column data types
    test_dtypes = list(df.dtypes)
    
    # Check that the type of each column matches the truth list
    assert truth_dtypes == test_dtypes

class TestISDFromSocetLis():

    def test_parse_with_empty_newlines(self):
        # Ensure all keys read when whitespace present
        empty_newlines = r"""T0_QUAT 1.0000000000000000000000000e-01

T1_QUAT 1.0000000000000000000000000e-01"""
        data = socetset_keywords_to_dict(empty_newlines)
        assert len(data.keys()) == 2

    def test_duplicate_key_check(self):
        duplicate_keys = r"""T 1
T 1"""
        with pytest.raises(ValueError):
            data = socetset_keywords_to_dict(duplicate_keys)

    def test_multiple_per_line(self):
        multiple_per_line = r"""T 1 1 1"""
        data = socetset_keywords_to_dict(multiple_per_line)
        assert len(data['T']) == 3

    def test_key_on_different_line(self):
        key_on_different_line = r"""A
0.0 1.00000000000000e+00 2.00000000000000e+00
3.0000000000000e+00 4.00000000000000e+00 5.00000000000000e+00
B 1.0e-01 2.000000e+00 3.00000000000000e+00"""
        data = socetset_keywords_to_dict(key_on_different_line)
        assert len(data['A']) == 6
        assert data['A'] == [0, 1, 2, 3, 4, 5]

        assert len(data['B']) == 3
        assert data['B'] == [0.1, 2, 3]

    def test_key_on_different_line_whitespace(self):
        key_on_different_line_whitespace = r"""A
    0.0 1.00000000000000e+00 2.00000000000000e+00
    3.0000000000000e+00 4.00000000000000e+00 5.00000000000000e+00
B 1.0e-01 2.000000e+00 3.00000000000000e+00"""
        data = socetset_keywords_to_dict(key_on_different_line_whitespace)
        assert len(data['A']) == 6
        assert data['A'] == [0, 1, 2, 3, 4, 5]

        assert len(data['B']) == 3
        assert data['B'] == [0.1, 2, 3]
'''