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Merge pull request #337 from mrava87/master
Revamped __init__ files
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‎.pre-commit-config.yaml‎

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hooks:
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- id: isort
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name: isort (python)
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args: ["--profile", "black", "--filter-files", "--line-length=88"]
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args:
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[
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"--profile",
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"black",
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"--skip",
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"__init__.py",
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"--filter-files",
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"--line-length=88",
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]

‎pylops/__init__.py‎

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# isort: skip_file
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from .LinearOperator import LinearOperator
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from .basicoperators import Regression
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from .basicoperators import LinearRegression
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from .basicoperators import MatrixMult
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from .basicoperators import Identity
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from .basicoperators import Zero
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from .basicoperators import Diagonal
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from .basicoperators import Flip
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from .basicoperators import Symmetrize
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from .basicoperators import Spread
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from .basicoperators import Transpose
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from .basicoperators import Roll
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from .basicoperators import Pad
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from .basicoperators import Sum
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from .basicoperators import FunctionOperator
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from .basicoperators import MemoizeOperator
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"""
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PyLops
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======
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from .basicoperators import VStack
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from .basicoperators import HStack
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from .basicoperators import Block
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from .basicoperators import BlockDiag
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from .basicoperators import Kronecker
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from .basicoperators import Real
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from .basicoperators import Imag
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from .basicoperators import Conj
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Linear operators and inverse problems are at the core of many of the most used
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algorithms in signal processing, image processing, and remote sensing.
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When dealing with small-scale problems, the Python numerical scientific
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libraries `numpy <http://www.numpy.org>`_
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and `scipy <http://www.scipy.org/scipylib/index.html>`_ allow to perform most
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of the underlying matrix operations (e.g., computation of matrix-vector
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products and manipulation of matrices) in a simple and expressive way.
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from .basicoperators import CausalIntegration
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from .basicoperators import FirstDerivative
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from .basicoperators import SecondDerivative
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from .basicoperators import Laplacian
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from .basicoperators import Gradient
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from .basicoperators import FirstDirectionalDerivative
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from .basicoperators import SecondDirectionalDerivative
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from .basicoperators import Restriction
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from .basicoperators import Smoothing1D
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from .basicoperators import Smoothing2D
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Many useful operators, however, do not lend themselves to an explicit matrix
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representation when used to solve large-scale problems. PyLops operators,
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on the other hand, still represent a matrix and can be treated in a similar
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way, but do not rely on the explicit creation of a dense (or sparse) matrix
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itself. Conversely, the forward and adjoint operators are represented by small
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pieces of codes that mimic the effect of the matrix on a vector or
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another matrix.
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from .avo.poststack import PoststackLinearModelling
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from .avo.prestack import PrestackWaveletModelling, PrestackLinearModelling
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Luckily, many iterative methods (e.g. cg, lsqr) do not need to know the
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individual entries of a matrix to solve a linear system. Such solvers only
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require the computation of forward and adjoint matrix-vector products as
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done for any of the PyLops operators.
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from .optimization.solver import cg, cgls
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from .optimization.leastsquares import NormalEquationsInversion, RegularizedInversion
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from .optimization.leastsquares import PreconditionedInversion
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from .optimization.sparsity import IRLS, OMP, ISTA, FISTA, SPGL1, SplitBregman
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PyLops provides
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1. A general construct for creating Linear Operators
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2. An extensive set of commonly used linear operators
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3. A set of least-squares and sparse solvers for linear operators.
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from .utils.seismicevents import makeaxis, linear2d, parabolic2d
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from .utils.tapers import hanningtaper, cosinetaper, taper2d, taper3d
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from .utils.wavelets import ricker, gaussian
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from .utils.utils import Report
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from .utils.deps import *
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Available subpackages
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---------------------
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basicoperators
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Basic Linear Operators
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signalprocessing
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Linear Operators for Signal Processing operations
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avo
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Linear Operators for Seismic Reservoir Characterization
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waveeqprocessing
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Linear Operators for Wave Equation oriented processing
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optimization
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Solvers
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utils
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Utility routines
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"""
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from . import avo
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from . import basicoperators
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from . import optimization
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from . import signalprocessing
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from . import utils
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from . import waveeqprocessing
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from .LinearOperator import LinearOperator
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from .basicoperators import *
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from . import (
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avo,
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basicoperators,
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optimization,
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signalprocessing,
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utils,
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waveeqprocessing,
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)
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from .avo.poststack import *
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from .avo.prestack import *
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from .optimization.solver import *
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from .optimization.leastsquares import *
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from .optimization.sparsity import *
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from .utils.seismicevents import *
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from .utils.tapers import *
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from .utils.utils import Report
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from .utils.wavelets import *
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try:
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from .version import version as __version__

‎pylops/avo/__init__.py‎

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# isort: skip_file
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"""
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AVO Operators
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=============
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The subpackage avo provides linear operators and applications aimed at
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solving various inverse problems in the area of Seismic Reservoir
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Characterization.
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A list of available operators present in pylops.avo:
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AVOLinearModelling AVO modelling.
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PoststackLinearModelling Post-stack seismic modelling.
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PrestackLinearModelling Pre-stack seismic modelling.
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PrestackWaveletModelling Pre-stack modelling operator for wavelet.
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and a list of applications:
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PoststackInversion Post-stack seismic inversion.
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PrestackInversion Pre-stack seismic inversion.
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"""
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from .poststack import *
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from .prestack import *
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__all__ = [
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"AVOLinearModelling",
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"PoststackLinearModelling",
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"PrestackWaveletModelling",
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"PrestackLinearModelling",
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"PoststackInversion",
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"PrestackInversion",
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]

‎pylops/basicoperators/__init__.py‎

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# isort: skip_file
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from .FunctionOperator import FunctionOperator
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from .MemoizeOperator import MemoizeOperator
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from .Regression import Regression
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from .LinearRegression import LinearRegression
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from .MatrixMult import MatrixMult
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from .Diagonal import Diagonal
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from .Zero import Zero
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from .Identity import Identity
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from .Restriction import Restriction
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from .Flip import Flip
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from .Symmetrize import Symmetrize
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from .Spread import Spread
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from .Transpose import Transpose
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from .Roll import Roll
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from .Pad import Pad
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from .Sum import Sum
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from .Real import Real
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from .Imag import Imag
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from .Conj import Conj
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from .VStack import VStack
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from .HStack import HStack
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from .Block import Block
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from .BlockDiag import BlockDiag
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from .Kronecker import Kronecker
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from .Smoothing1D import Smoothing1D
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from .Smoothing2D import Smoothing2D
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from .CausalIntegration import CausalIntegration
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from .FirstDerivative import FirstDerivative
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from .SecondDerivative import SecondDerivative
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from .Laplacian import Laplacian
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from .Gradient import Gradient
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from .DirectionalDerivative import FirstDirectionalDerivative
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from .DirectionalDerivative import SecondDirectionalDerivative
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"""
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Basic Linear Operators
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======================
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The subpackage basicoperators extends some of the basic linear algebra
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operations provided by numpy providing forward and adjoint functionalities.
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A list of operators present in pylops.basicoperators :
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MatrixMult Matrix multiplication.
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Identity Identity operator.
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Zero Zero operator.
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Diagonal Diagonal operator.
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Transpose Transpose operator.
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Flip Flip along an axis.
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Roll Roll along an axis.
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Pad Pad operator.
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Sum Sum operator.
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Symmetrize Symmetrize along an axis.
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Restriction Restriction (or sampling) operator.
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Regression Polynomial regression.
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LinearRegression Linear regression.
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CausalIntegration Causal integration.
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Spread Spread operator.
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VStack Vertical stacking.
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HStack Horizontal stacking.
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Block Block operator.
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BlockDiag Block-diagonal operator.
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Kronecker Kronecker operator.
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Real Real operator.
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Imag Imag operator.
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Conj Conj operator.
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Smoothing1D 1D Smoothing.
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Smoothing2D 2D Smoothing.
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FirstDerivative First derivative.
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SecondDerivative Second derivative.
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Laplacian Laplacian.
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Gradient Gradient.
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FirstDirectionalDerivative First Directional derivative.
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SecondDirectionalDerivative Second Directional derivative.
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"""
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from .FunctionOperator import *
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from .MemoizeOperator import *
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from .Regression import *
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from .LinearRegression import *
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from .MatrixMult import *
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from .Diagonal import *
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from .Zero import *
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from .Identity import *
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from .Restriction import *
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from .Flip import *
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from .Symmetrize import *
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from .Spread import *
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from .Transpose import *
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from .Roll import *
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from .Pad import *
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from .Sum import *
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from .VStack import *
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from .HStack import *
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from .Block import *
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from .BlockDiag import *
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from .Kronecker import *
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from .Real import *
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from .Imag import *
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from .Conj import *
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from .Smoothing1D import *
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from .Smoothing2D import *
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from .CausalIntegration import *
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from .FirstDerivative import *
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from .SecondDerivative import *
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from .Laplacian import *
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from .Gradient import *
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from .DirectionalDerivative import *
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__all__ = [
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"FunctionOperator",
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"MemoizeOperator",
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"Regression",
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"LinearRegression",
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"MatrixMult",
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"Diagonal",
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"Zero",
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"Identity",
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"Restriction",
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"Flip",
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"Symmetrize",
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"Spread",
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"Transpose",
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"Roll",
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"Pad",
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"Sum",
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"VStack",
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"HStack",
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"Block",
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"BlockDiag",
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"Kronecker",
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"Real",
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"Imag",
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"Conj",
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"Smoothing1D",
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"Smoothing2D",
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"CausalIntegration",
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"FirstDerivative",
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"SecondDerivative",
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"Laplacian",
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"Gradient",
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"FirstDirectionalDerivative",
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"SecondDirectionalDerivative",
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]

‎pylops/optimization/__init__.py‎

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# isort: skip_file
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"""
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Optimization
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============
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The subpackage optimization provides an extensive set of solvers to be
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used with PyLops linear operators.
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A list of least-squares solvers in pylops.optimization.solver:
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cg Conjugate gradient.
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cgls Conjugate gradient least-squares.
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lsqr LSQR.
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and wrappers for regularized or preconditioned inversion in pylops.optimization.leastsquares:
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NormalEquationsInversion Inversion of normal equations.
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RegularizedInversion Regularized inversion.
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PreconditionedInversion Preconditioned inversion.
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and sparsity-promoting solvers in pylops.optimization.sparsity:
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IRLS Iteratively reweighted least squares.
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OMP Orthogonal Matching Pursuit (OMP).
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ISTA Iterative Soft Thresholding Algorithm.
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FISTA Fast Iterative Soft Thresholding Algorithm.
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SPGL1 Spectral Projected-Gradient for L1 norm.
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SplitBregman Split Bregman for mixed L2-L1 norms.
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"""

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