#162: Sort imports

demos/burgers-hessian.py

@@ -9,12 +9,12 @@
 #
 # As before, we copy over what is now effectively boiler plate to set up our problem. ::
 
-from firedrake import *
+import matplotlib.pyplot as plt
 from animate.adapt import adapt
 from animate.metric import RiemannianMetric
-from goalie import *
-import matplotlib.pyplot as plt
+from firedrake import *
 
+from goalie import *
 
 fields = ["u"]
 

demos/burgers.py

@@ -21,6 +21,7 @@
 # side. See the Firedrake demo for details on the discretisation used.
 
 from firedrake import *
+
 from goalie import *
 
 # In this problem, we have a single prognostic variable,

demos/burgers1.py

@@ -11,6 +11,7 @@
 # ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # For ease, the field list and functions for obtaining the

demos/burgers2.py

@@ -9,8 +9,8 @@
 # Again, begin by importing Goalie with adjoint mode activated. ::
 
 from firedrake import *
-from goalie_adjoint import *
 
+from goalie_adjoint import *
 
 set_log_level(DEBUG)
 

demos/burgers_ee.py

@@ -25,6 +25,7 @@
 # Goalie. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 set_log_level(DEBUG)

demos/burgers_oo.py

@@ -19,8 +19,8 @@
 # ::
 
 from firedrake import *
-from goalie_adjoint import *
 
+from goalie_adjoint import *
 
 set_log_level(DEBUG)
 

demos/burgers_time_integrated.py

@@ -9,6 +9,7 @@
 # Begin by importing from Goalie and the first Burgers demo. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # Redefine the ``get_initial_condition``, ``get_function_spaces``,

demos/gray_scott.py

@@ -10,6 +10,7 @@
 # diffusivities and react with one another nonlinearly. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # The problem is defined on a doubly periodic mesh of squares. ::

demos/gray_scott_split.py

@@ -9,6 +9,7 @@
 # equations differ in both the diffusion and reaction terms. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # This time, we have two fields instead of one, as well as two function spaces. ::

demos/mesh_seq.py

@@ -12,6 +12,7 @@
 # of both Firedrake and Goalie. ::
 
 from firedrake import *
+
 from goalie import *
 
 # Again, turn debugging mode on to get verbose output. ::

demos/ode.py

@@ -42,8 +42,8 @@
 # First, import from the namespaces of Firedrake and Goalie. ::
 
 from firedrake import *
-from goalie import *
 
+from goalie import *
 
 # Next, create a simple :class:`~.TimeInterval` object to hold information related to
 # the time discretisation. This is a simplified version of :class:`~.TimePartition`,

demos/point_discharge2d-goal_oriented.py

@@ -10,14 +10,14 @@
 # We copy over the setup as before. The only difference is that we import from
 # `goalie_adjoint` rather than `goalie`. ::
 
-from firedrake import *
+import matplotlib.colors as mcolors
+import matplotlib.pyplot as plt
 from animate.adapt import adapt
 from animate.metric import RiemannianMetric
-from goalie_adjoint import *
-import matplotlib.pyplot as plt
-import matplotlib.colors as mcolors
+from firedrake import *
 from matplotlib import ticker
 
+from goalie_adjoint import *
 
 fields = ["c"]
 

demos/point_discharge2d-hessian.py

@@ -13,11 +13,11 @@
 # adaptation functionality from Firedrake, which can be found in ``firedrake.meshadapt``.
 # ::
 
-from firedrake import *
 from animate.adapt import adapt
 from animate.metric import RiemannianMetric
-from goalie import *
+from firedrake import *
 
+from goalie import *
 
 # We again consider the "point discharge with diffusion" test case from the
 # `previous demo <./point_discharge2d.py.html>`__, approximating the tracer concentration

demos/point_discharge2d.py

@@ -26,6 +26,7 @@
 # As always, start by importing Firedrake and Goalie. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # We solve the advection-diffusion problem in :math:`\mathbb P1` space. ::

demos/solid_body_rotation.py

@@ -37,6 +37,7 @@
 # adjoint mode activated. ::
 
 from firedrake import *
+
 from goalie_adjoint import *
 
 # For simplicity, we use a :math:`\mathbb P1` space for each
@@ -113,9 +114,8 @@ def get_initial_condition(mesh_seq, field="c"):
 # only the :meth:`get_function_spaces` and :meth:`get_initial_condition`
 # methods implemented. ::
 
-from firedrake.pyplot import tricontourf
 import matplotlib.pyplot as plt
-
+from firedrake.pyplot import tricontourf
 
 mesh_seq = MeshSeq(
     time_partition,

demos/solid_body_rotation_split.py

@@ -18,7 +18,6 @@
 
 from solid_body_rotation import *
 
-
 fields = ["bell", "cone", "slot_cyl"]
 
 

goalie/adjoint.py

@@ -2,17 +2,18 @@
 Drivers for solving adjoint problems on sequences of meshes.
 """
 
+from functools import wraps
+
 import firedrake
-from firedrake.petsc import PETSc
+import numpy as np
 from firedrake.adjoint import pyadjoint
+from firedrake.petsc import PETSc
+
 from .function_data import AdjointSolutionData
+from .log import pyrint
 from .mesh_seq import MeshSeq
 from .options import GoalOrientedParameters
 from .utility import AttrDict, norm
-from .log import pyrint
-from functools import wraps
-import numpy as np
-
 
 __all__ = ["AdjointMeshSeq", "annotate_qoi"]
 

goalie/error_estimation.py

@@ -1,12 +1,12 @@
 """
 Tools to automate goal-oriented error estimation.
 """
+
 import firedrake
+import ufl
 from firedrake import Function, FunctionSpace
 from firedrake.functionspaceimpl import WithGeometry
 from firedrake.petsc import PETSc
-import ufl
-
 
 __all__ = ["get_dwr_indicator"]
 

goalie/function_data.py

@@ -2,10 +2,12 @@
 Nested dictionaries of solution data :class:`~.Function`\s.
 """
 
+import abc
+
 import firedrake.function as ffunc
 import firedrake.functionspace as ffs
+
 from .utility import AttrDict
-import abc
 
 __all__ = [
     "ForwardSolutionData",

goalie/go_mesh_seq.py

@@ -2,16 +2,17 @@
 Drivers for goal-oriented error estimation on sequences of meshes.
 """
 
-from .adjoint import AdjointMeshSeq
-from .error_estimation import get_dwr_indicator
-from .function_data import IndicatorData
-from .log import pyrint
-from firedrake import Function, FunctionSpace, MeshHierarchy, TransferManager
-from firedrake.petsc import PETSc
 from collections.abc import Iterable
+
 import numpy as np
 import ufl
+from firedrake import Function, FunctionSpace, MeshHierarchy, TransferManager
+from firedrake.petsc import PETSc
 
+from .adjoint import AdjointMeshSeq
+from .error_estimation import get_dwr_indicator
+from .function_data import IndicatorData
+from .log import pyrint
 
 __all__ = ["GoalOrientedMeshSeq"]
 

goalie/interpolation.py

@@ -2,12 +2,12 @@
 Driver functions for mesh-to-mesh data transfer.
 """
 
-from .utility import assemble_mass_matrix, cofunction2function, function2cofunction
 import firedrake
 from firedrake.functionspaceimpl import WithGeometry
 from firedrake.petsc import PETSc
 from petsc4py import PETSc as petsc4py
 
+from .utility import assemble_mass_matrix, cofunction2function, function2cofunction
 
 __all__ = ["transfer", "interpolate", "project"]
 

goalie/log.py

@@ -4,10 +4,11 @@
 Code mostly copied from `the Thetis project
 <https://thetisproject.org>`__.
 """
-import firedrake
+
 import logging
-from logging import DEBUG, WARNING, ERROR
+from logging import DEBUG, ERROR, WARNING
 
+import firedrake
 
 __all__ = [
     "logger",

goalie/math.py

@@ -2,7 +2,6 @@
 import ufl
 import ufl.core.expr
 
-
 __all__ = ["bessi0", "bessk0"]
 
 

goalie/mesh_seq.py

@@ -2,20 +2,21 @@
 Sequences of meshes corresponding to a :class:`~.TimePartition`.
 """
 
+from collections.abc import Iterable
+
 import firedrake
+import numpy as np
+from animate.quality import QualityMeasure
 from firedrake.adjoint import pyadjoint
 from firedrake.adjoint_utils.solving import get_solve_blocks
 from firedrake.petsc import PETSc
 from firedrake.pyplot import triplot
+
 from .function_data import ForwardSolutionData
 from .interpolation import transfer
-from .log import pyrint, debug, warning, info, logger, DEBUG
+from .log import DEBUG, debug, info, logger, pyrint, warning
 from .options import AdaptParameters
-from animate.quality import QualityMeasure
 from .utility import AttrDict, Mesh
-from collections.abc import Iterable
-import numpy as np
-
 
 __all__ = ["MeshSeq"]
 

goalie/metric.py

@@ -1,14 +1,16 @@
 """
 Driver functions for metric-based mesh adaptation.
 """
-from .log import debug
-from animate.metric import RiemannianMetric
-import firedrake
-from firedrake.petsc import PETSc
+
 from collections.abc import Iterable
+
+import firedrake
 import numpy as np
 import ufl
+from animate.metric import RiemannianMetric
+from firedrake.petsc import PETSc
 
+from .log import debug
 
 __all__ = ["enforce_variable_constraints", "space_time_normalise", "ramp_complexity"]
 

goalie/options.py

@@ -1,6 +1,6 @@
-from .utility import AttrDict
 from animate.adapt import RiemannianMetric
 
+from .utility import AttrDict
 
 __all__ = [
     "AdaptParameters",

goalie/point_seq.py

@@ -1,5 +1,6 @@
 import firedrake
 import firedrake.mesh as fmesh
+
 from .mesh_seq import MeshSeq
 
 __all__ = ["PointSeq"]

goalie/time_partition.py

@@ -1,10 +1,12 @@
 """
 Partitioning for the temporal domain.
 """
-from .log import debug
+
 from collections.abc import Iterable
+
 import numpy as np
 
+from .log import debug
 
 __all__ = ["TimePartition", "TimeInterval", "TimeInstant"]
 

goalie/utility.py

@@ -2,14 +2,15 @@
 Utility functions and classes for mesh adaptation.
 """
 
+import os
 from collections import OrderedDict
+
 import firedrake
 import firedrake.mesh as fmesh
-from firedrake.petsc import PETSc
-from firedrake.__future__ import interpolate
 import numpy as np
-import os
 import ufl
+from firedrake.__future__ import interpolate
+from firedrake.petsc import PETSc
 
 
 @PETSc.Log.EventDecorator()

goalie_adjoint/__init__.py

@@ -1,5 +1,7 @@
 from __future__ import absolute_import
+
+from pyadjoint import no_annotations  # noqa
+
 from goalie import *  # noqa
 from goalie.adjoint import *  # noqa
 from goalie.go_mesh_seq import *  # noqa
-from pyadjoint import no_annotations  # noqa