las_rs 0.2.1

High-performance parser and writer for LAS (Log ASCII Standard) well-log files — LAS 1.2 / 2.0 / 3.0. Pure-Rust core; the optional `python` feature adds the PyO3 bindings that back the `las-rs` PyPI wheel.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217

"""
Phase 3 tests — Data section parsing.

Covers comma-decimal marks, null handling in the index column, data-section
comment skipping, data shape validation, wrapped-file reading (v1.2 and v2.0),
dtype inference and coercion, and the normal/numpy engine switch.

All tests are marked xfail because the `las_rs` Rust extension has not yet
been implemented.
"""

import os

import numpy as np
import pytest

import las_rs

test_dir = os.path.dirname(__file__)


def fixture(fn):
    return os.path.join(test_dir, "fixtures", fn)


# ---------------------------------------------------------------------------
# Comma-decimal mark
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_comma_decimal_mark():
    """Values written with a comma decimal separator (e.g. '1670,5') are
    parsed as the float 1670.5 when the comma-decimal read policy is active."""
    las = las_rs.read(fixture("edge_cases/comma_decimal.las"), read_policy="comma-decimal-mark")
    dept = las.curves["DEPT"].data
    # The second depth sample is 1671.0 written in the file as "1671,000"
    assert dept[1] == pytest.approx(1671.0)


# ---------------------------------------------------------------------------
# Index column null handling
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_index_not_null_replaced():
    """The NULL value (-999.25) that appears in the index (DEPT) column must
    NOT be replaced with NaN — it must be kept as-is."""
    las = las_rs.read(fixture("edge_cases/index_null.las"))
    dept = las.curves["DEPT"].data
    # The third row (index 2) has -999.25 in the depth column; it should
    # remain numeric, not become NaN.
    assert not np.isnan(dept[2])
    assert dept[2] == pytest.approx(-999.25)


# ---------------------------------------------------------------------------
# Comment lines in data section
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_skip_data_comments():
    """Lines starting with '#' inside the ~ASCII data section are treated as
    comments and skipped; they must not contribute to the row count."""
    las = las_rs.read(fixture("edge_cases/comment_lines.las"))
    dept = las.curves["DEPT"].data
    # The fixture has 3 data rows interspersed with 4 comment lines;
    # only the 3 real rows should appear in the parsed result.
    assert len(dept) == 3


# ---------------------------------------------------------------------------
# Data shape matches curves
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_data_shape_matches_curves():
    """The number of columns in the 2-D data array equals the number of
    curves defined in the ~Curve section."""
    las = las_rs.read(fixture("v12/sample_v12.las"))
    n_curves = len(las.curves)
    data = las.data  # 2-D numpy array, shape (n_rows, n_curves)
    assert data.shape[1] == n_curves


# ---------------------------------------------------------------------------
# Wrapped v1.2
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_wrapped_v12_reads():
    """A WRAP=YES v1.2 file is read without error and its data array has the
    expected shape (rows × curves)."""
    las = las_rs.read(fixture("v12/sample_v12_wrapped.las"))
    # Fixture: 4 depth steps, 12 curves (DEPT + 11 logs)
    assert las.data.shape == (4, 12)


@pytest.mark.xfail(reason="not yet implemented")
def test_wrapped_v12_values():
    """Spot-check specific values from the wrapped v1.2 fixture."""
    las = las_rs.read(fixture("v12/sample_v12_wrapped.las"))
    dept = las.curves["DEPT"].data
    gr = las.curves["GR"].data
    # First depth step
    assert dept[0] == pytest.approx(800.0)
    assert gr[0] == pytest.approx(34.215)


# ---------------------------------------------------------------------------
# Wrapped v2.0
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_wrapped_v20_reads():
    """A WRAP=YES v2.0 file is read without error and its data array has the
    expected shape (rows × curves)."""
    las = las_rs.read(fixture("v20/sample_v20_wrapped.las"))
    # Fixture: 3 depth steps, 10 curves (DEPT + 9 logs)
    assert las.data.shape == (3, 10)


# ---------------------------------------------------------------------------
# dtype inference — float64 default
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_dtypes_auto_float():
    """When dtypes='auto' (the default), numeric columns are inferred as
    float64."""
    las = las_rs.read(fixture("v12/sample_v12.las"))
    for curve in las.curves:
        assert curve.data.dtype == np.float64


# ---------------------------------------------------------------------------
# dtype inference — string columns
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_dtypes_auto_string():
    """When dtypes='auto', a column that cannot be parsed as a number is kept
    as a string (object) dtype."""
    # Use a fixture whose data section contains a text column
    las = las_rs.read(
        fixture("edge_cases/comment_lines.las"),
        dtypes="auto",
    )
    # All-numeric fixture: every column should be float64 (sanity guard)
    for curve in las.curves:
        assert curve.data.dtype in (np.float64, object)


# ---------------------------------------------------------------------------
# dtype specified — dict
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_dtypes_specified_dict():
    """dtypes={'GR': int} converts the GR column to integer dtype."""
    las = las_rs.read(fixture("v12/sample_v12.las"), dtypes={"GR": int})
    assert las.curves["GR"].data.dtype == np.intp or np.issubdtype(
        las.curves["GR"].data.dtype, np.integer
    )


# ---------------------------------------------------------------------------
# dtype specified — list
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_dtypes_specified_list():
    """dtypes=[float, float, float, float] applied per-column in order."""
    las = las_rs.read(fixture("v12/sample_v12.las"), dtypes=[float, float, float, float])
    for curve in las.curves:
        assert np.issubdtype(curve.data.dtype, np.floating)


# ---------------------------------------------------------------------------
# Engine selection — normal
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_engine_normal():
    """engine='normal' parses the data section correctly and produces the
    same result as default parsing."""
    las = las_rs.read(fixture("v12/sample_v12.las"), engine="normal")
    dept = las.curves["DEPT"].data
    assert dept[0] == pytest.approx(500.0)
    assert len(dept) == 6


# ---------------------------------------------------------------------------
# Engine selection — numpy
# ---------------------------------------------------------------------------


@pytest.mark.xfail(reason="not yet implemented")
def test_engine_numpy():
    """engine='numpy' parses the data section correctly and produces the
    same depths as the normal engine."""
    las_normal = las_rs.read(fixture("v12/sample_v12.las"), engine="normal")
    las_numpy = las_rs.read(fixture("v12/sample_v12.las"), engine="numpy")
    np.testing.assert_array_almost_equal(
        las_normal.curves["DEPT"].data,
        las_numpy.curves["DEPT"].data,
    )