def test_XAxis_append_summary(position_xvalues, exp_summary):
xaxis = XAxis.XAxis(ident=b'A', long_name=b'B', units=b'C')
x_values = []
for frame_number, (vr_postion, lrsh_position,
x_value) in enumerate(position_xvalues):
xaxis.append(File.LogicalRecordPositionBase(vr_postion, lrsh_position),
frame_number + 1, x_value)
x_values.append(x_value)
result = xaxis.summary
# print(result)
assert result.count == len(x_values)
assert result.min == min(x_values)
assert result.max == max(x_values)
array = np.array(x_values)
spacing_summary = XAxis.compute_spacing(array)
assert result.spacing == spacing_summary
def test_XAxis_getitem(position_xvalues, expected):
x_axis = XAxis.XAxis(ident=b'A', long_name=b'B', units=b'C')
x_values = []
for frame_number, (vr_postion, lrsh_position,
x_value) in enumerate(position_xvalues):
x_axis.append(
File.LogicalRecordPositionBase(vr_postion, lrsh_position),
frame_number + 1, x_value)
x_values.append(x_value)
assert len(x_axis) == len(expected)
# print()
for i in range(len(x_axis)):
# print(x_axis[i])
assert x_axis[i] == expected[i]
def add_iflr(self, file_logical_data: File.FileLogicalData, iflr: IFLR.IndirectlyFormattedLogicalRecord) -> None:
"""Adds a IFLR entry to the index. The IFLR just contains the object name and frame number.
This extracts the X axis from the first value in the IFLR free data and appends this to the
iflr_position_map.
"""
self._check_fld_iflr(file_logical_data, iflr)
frame_array: LogPass.FrameArray = self.log_pass[iflr.object_name]
frame_array.read_x_axis(file_logical_data.logical_data, frame_number=0)
if iflr.object_name not in self.iflr_position_map:
self.iflr_position_map[iflr.object_name] = XAxis.XAxis(
frame_array.x_axis.ident,
frame_array.x_axis.long_name,
frame_array.x_axis.units,
)
self.iflr_position_map[iflr.object_name].append(
file_logical_data.position,
iflr.frame_number,
frame_array.x_axis.array.mean(),
)
def test_compute_spacing_eq(x_array, expected):
result = XAxis.compute_spacing(x_array)
assert result == expected
assert result != 1
def test_compute_spacing_counts_counts_negative(diff_array, exp_median, exp_counts):
_median, counts = XAxis.compute_spacing_counts(-diff_array)
assert exp_counts == counts
def test_compute_spacing_counts_median(diff_array, exp_median, exp_counts):
median, _counts = XAxis.compute_spacing_counts(diff_array)
assert exp_median == median
def test_XAxis_ctor():
xaxis = XAxis.XAxis(ident=b'A', long_name=b'B', units=b'C')
assert xaxis.ident == b'A'
assert xaxis.long_name == b'B'
assert xaxis.units == b'C'
def test_x_axis_spacing_summary_eq(array_a, array_b, expected):
x_axis_a = XAxis.compute_spacing(array_a)
x_axis_b = XAxis.compute_spacing(array_b)
assert (x_axis_a == x_axis_b) == expected
assert (x_axis_b == x_axis_a) == expected
assert not x_axis_a == 1
def test_xaxis_spacing_counts_total(norm, dupe, skip, back, expected):
counts = XAxis.XAxisSpacingCounts(norm, dupe, skip, back)
assert counts.total == expected
def test_compute_spacing_histogram_str(x_array, expected):
x_axis = XAxis.compute_spacing(x_array)
result = x_axis.histogram_str()
# print(result)
assert result == expected
from TotalDepth.RP66V1.core import XAxis, File
@pytest.mark.parametrize(
'norm, dupe, skip, back, expected',
(
(1, 2, 3, 4, 10),
)
)
def test_xaxis_spacing_counts_total(norm, dupe, skip, back, expected):
counts = XAxis.XAxisSpacingCounts(norm, dupe, skip, back)
assert counts.total == expected
SPACING_COUNTS = (
(np.array([1.0, 1.0, 1.0]), 1.0, XAxis.XAxisSpacingCounts(3, 0, 0, 0),),
# Norm
(np.array([1.0, 1.0, 1.1]), 1.0, XAxis.XAxisSpacingCounts(3, 0, 0, 0),),
# Dupe
(np.array([1.0, 1.0, 0.0]), 1.0, XAxis.XAxisSpacingCounts(2, 1, 0, 0),),
# Skip
(np.array([1.0, 1.0, 2.0]), 1.0, XAxis.XAxisSpacingCounts(2, 0, 1, 0),),
# Back
(np.array([1.0, 1.0, -1.0]), 1.0, XAxis.XAxisSpacingCounts(2, 0, 0, 1),),
)
@pytest.mark.parametrize('diff_array, exp_median, exp_counts', SPACING_COUNTS)
def test_compute_spacing_counts_median(diff_array, exp_median, exp_counts):
median, _counts = XAxis.compute_spacing_counts(diff_array)
assert exp_median == median
