mirror of
https://github.com/wassname/segpy.git
synced 2026-06-27 18:25:38 +08:00
Robert Smallshire
98 lines
4.1 KiB
Python
98 lines
4.1 KiB
Python
"""Tools for interoperability between Segpy and Numpy arrays."""
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import numpy as np
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from segpy.util import ensure_superset
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from segpy_numpy.dtypes import make_dtype
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class DimensionalityError:
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pass
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def extract_inline_3d(reader, inline_number, xline_numbers=None, sample_numbers=None, null=None):
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"""Extract an inline as a two-dimensional array.
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Args:
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reader:
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inline_number: The number of the inline to be extracted.
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xline_numbers: Either a sequence of crossline numbers from which traces are
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to be extracted or a slice object indicating that some slice of all
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crossline numbers is to be used. If None, traces will be extracted at
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all crosslines.
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sample_numbers: An optional sorted sequence of samples numbers at which to
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extract samples. If not provided, samples will be extracted at all
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depths.
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null: A null value
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Returns:
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A two-dimensional array. If null is None a masked array will be returned, otherwise
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a simple array will be returned.. The first (slowest changing) index will correspond
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to the traces (index zero will correspond to the first crossline number). The
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second (fastest changing) index will correspond to the samples (index zero will
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correspond to the first sample number.
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"""
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if inline_number not in reader.inline_numbers():
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raise ValueError("Inline number {} not present in {}".format(inline_number, reader))
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xline_numbers = ensure_superset(reader.xline_numbers(), xline_numbers)
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sample_numbers = ensure_superset(range(0, reader.max_num_trace_samples()), sample_numbers)
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shape = (len(xline_numbers), len(sample_numbers))
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dtype = make_dtype(reader.data_sample_format)
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array = make_array(shape, dtype, null)
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if isinstance(sample_numbers, range):
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_populate_inline_array_over_sample_range(reader, inline_number, xline_numbers, sample_numbers, array)
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else:
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_populate_inline_array_numbered_samples(reader, inline_number, xline_numbers, sample_numbers, array)
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return array
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def _populate_inline_array_numbered_samples(reader, inline_number, xline_numbers, sample_numbers, array):
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for xline_index, xline_number in enumerate(xline_numbers):
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inline_xline_number = (inline_number, xline_number)
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if reader.has_trace_index(inline_xline_number):
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trace_index = reader.trace_index(inline_xline_number)
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num_trace_samples = reader.num_trace_samples(trace_index)
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trace_sample_start = sample_numbers[0]
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trace_sample_stop = min(sample_numbers[-1] + 1, num_trace_samples)
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trace_samples = reader.trace_samples(trace_index, trace_sample_start, trace_sample_stop)
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for sample_index, sample_number in enumerate(sample_numbers):
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array[xline_index, sample_index] = trace_samples[sample_number - trace_sample_start]
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def _populate_inline_array_over_sample_range(reader, inline_number, xline_numbers, sample_numbers, array):
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for xline_index, xline_number in enumerate(xline_numbers):
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inline_xline_number = (inline_number, xline_number)
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if reader.has_trace_index(inline_xline_number):
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trace_index = reader.trace_index(inline_xline_number)
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num_trace_samples = reader.num_trace_samples(trace_index)
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trace_sample_stop = min(sample_numbers.stop, num_trace_samples)
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trace_samples = reader.trace_samples(trace_index, sample_numbers.start, trace_sample_stop)
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source_slice = slice(sample_numbers.start, trace_sample_stop, sample_numbers.step)
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array[xline_index, :] = trace_samples[source_slice]
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def make_array(shape, dtype, null=None):
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"""Make an array"""
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if null is None:
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return np.ma.masked_all(shape, dtype)
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array = np.empty(shape, dtype)
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array.fill(null)
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return array
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def start_and_stop(sequence):
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"""Obtain start and stop values from a sequence."""
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sample_start = sequence[0]
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try:
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sample_stop = sequence.stop
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except AttributeError:
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sample_stop = sequence[-1] + 1
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return sample_start, sample_stop
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