Silence more warnings

Author: cgcgcg

base/PyNucleus_base/plot_utils.py

@@ -212,6 +212,7 @@ def myFmt(a, fmt):
 
 
 def formatScientificLatex(a, useEnotation=True):
+    import numpy as np
     if abs(a) > 0:
         exp = int(np.floor(np.log10(a)))
         mantissa = a/10**exp

base/PyNucleus_base/solver_factory.py

@@ -56,7 +56,9 @@ def build(self, name, **kwargs):
                 kwargs.pop('A', None)
                 hierarchy = kwargs.pop('hierarchy')
                 smoother = kwargs.pop('smoother', 'jacobi')
-                if not isinstance(hierarchy, list) and isinstance(hierarchy.builtHierarchies[-1].algebraicLevels[-1].A, ComplexLinearOperator) and self.multiLevelSolverFactory.isRegistered('complex_'+name):
+                if (not isinstance(hierarchy, list) and
+                        isinstance(hierarchy.builtHierarchies[-1].algebraicLevels[-1].A, ComplexLinearOperator) and
+                        self.multiLevelSolverFactory.isRegistered('complex_'+name)):
                     name = 'complex_'+name
                 solver = self.multiLevelSolverFactory.build(name, hierarchy, smoother, **kwargs)
             else:

base/PyNucleus_base/utilsFem.py

@@ -262,20 +262,20 @@ def saveDictToHDF5(params, f, ignore=set()):
                 if isinstance(val[0], list) and isinstance(val[0][0], (int, float, INDEX, REAL)):
                     g = f.create_group(key)
                     g.attrs['type'] = 'compressedList'
-                    l = 0
+                    listItems = 0
                     for i in range(len(val)):
-                        l += len(val[i])
+                        listItems += len(val[i])
                     indptr = uninitialized((len(val)+1), dtype=INDEX)
                     if isinstance(val[0][0], (int, INDEX)):
-                        data = uninitialized((l), dtype=INDEX)
+                        data = uninitialized((listItems), dtype=INDEX)
                     else:
-                        data = uninitialized((l), dtype=REAL)
-                    l = 0
+                        data = uninitialized((listItems), dtype=REAL)
+                    listItems = 0
                     for i in range(len(val)):
-                        indptr[i] = l
-                        data[l:l+len(val[i])] = val[i]
-                        l += len(val[i])
-                    indptr[-1] = l
+                        indptr[i] = listItems
+                        data[listItems:listItems+len(val[i])] = val[i]
+                        listItems += len(val[i])
+                    indptr[-1] = listItems
                     g.create_dataset('indptr', data=indptr)
                     g.create_dataset('data', data=data)
                 elif isinstance(val[0], str):
@@ -325,20 +325,20 @@ def loadDictFromHDF5(f):
         if isinstance(f[key], h5py.Group):
             if 'type' in f[key].attrs:
                 if f[key].attrs['type'] == 'list':
-                    l = []
+                    myList = []
                     for k in range(len(f[key].attrs)-1):
-                        l.append(f[key].attrs[str(k)])
-                    params[key] = l
+                        myList.append(f[key].attrs[str(k)])
+                    params[key] = myList
                 elif f[key].attrs['type'] == 'compressedList':
-                    l = []
+                    myCompressedList = []
                     indptr = np.array(f[key]['indptr'], dtype=INDEX)
                     if isinstance(f[key]['data'], (int, INDEX)):
                         data = np.array(f[key]['data'], dtype=INDEX)
                     else:
                         data = np.array(f[key]['data'], dtype=REAL)
                     for i in range(len(indptr)-1):
-                        l.append(data[indptr[i]:indptr[i+1]].tolist())
-                    params[key] = l
+                        myCompressedList.append(data[indptr[i]:indptr[i+1]].tolist())
+                    params[key] = myCompressedList
                 elif f[key].attrs['type'] == 'series':
                     d = loadDictFromHDF5(f[key])
                     grp = seriesOutputGroup(key)
@@ -359,10 +359,10 @@ def loadDictFromHDF5(f):
         else:
             params[key] = np.array(f[key])
             try:
-                l = []
+                myList = []
                 for i in range(len(params[key])):
-                    l.append(params[key][i].decode('utf-8'))
-                params[key] = l
+                    myList.append(params[key][i].decode('utf-8'))
+                params[key] = myList
             except:
                 pass
     return params
@@ -501,7 +501,8 @@ def __init__(self, filename, comm, mode=MPI.MODE_WRONLY | MPI.MODE_CREATE):
         # keep the absolute path, otherwise derived classes which use this
         # may come a cropper when the current directory changes
         self.baseFilename = os.path.abspath(filename)
-        assert len(self.baseFilename) <= 245, 'The length of the log file path \"{}\" is too long and will probably crash MPI. Try running with \"--disableFileLog\"'.format(self.baseFilename)
+        assert len(self.baseFilename) <= 245, ('The length of the log file path \"{}\" is too long ' +
+                                               'and will probably crash MPI. Try running with \"--disableFileLog\"').format(self.baseFilename)
         if Path(self.baseFilename).exists() and comm.rank == 0:
             from os import remove
             remove(self.baseFilename)
@@ -538,16 +539,16 @@ def close(self):
 
 def columns(lines, returnColWidth=False, colWidth=0):
     if colWidth == 0:
-        for l, _, _ in lines:
-            colWidth = max(len(l), colWidth)
+        for line, _, _ in lines:
+            colWidth = max(len(line), colWidth)
     s = []
-    for l, f, v in lines:
+    for line, f, v in lines:
         if isinstance(f, str):
             lf = '{:<'+str(colWidth+2)+'}'+f
-            s.append(lf.format(l+':', v))
+            s.append(lf.format(line+':', v))
         else:
             lf = '{:<'+str(colWidth+2)+'}'+'{}'
-            s.append(lf.format(l+':', f(v)))
+            s.append(lf.format(line+':', f(v)))
     s = '\n'.join(s)
     if returnColWidth:
         return s, colWidth
@@ -1488,18 +1489,22 @@ def __call__(self):
                     if isinstance(newValue, np.ndarray):
                         cached_args[prop] = newValue.copy()
                         if (newValue != oldValue).any():
-                            dependencyLogger.log(self.logLevel, 'Values for {} differ: \'{}\' != \'{}\', calling \'{}\''.format(prop, oldValue, newValue, self.fun.__name__))
+                            dependencyLogger.log(self.logLevel, 'Values for {} differ: \'{}\' != \'{}\', calling \'{}\''.format(prop, oldValue,
+                                                                                                                                newValue, self.fun.__name__))
                             needToBuild = True
                         else:
                             dependencyLogger.log(self.logLevel, 'Values for {} are identical: \'{}\' == \'{}\''.format(prop, oldValue, newValue))
                     elif newValue != oldValue:
                         cached_args[prop] = newValue
-                        dependencyLogger.log(self.logLevel, 'Values for {} differ: \'{}\' != \'{}\', calling \'{}\''.format(prop, oldValue, newValue, self.fun.__name__))
+                        dependencyLogger.log(self.logLevel, 'Values for {} differ: \'{}\' != \'{}\', calling \'{}\''.format(prop, oldValue,
+                                                                                                                            newValue, self.fun.__name__))
                         needToBuild = True
                     else:
                         dependencyLogger.log(self.logLevel, 'Values for {} are identical: \'{}\' == \'{}\''.format(prop, oldValue, newValue))
                 except Exception as e:
-                    dependencyLogger.log(logging.WARN, 'Cannot compare values {}, {} for property \'{}\', exception {}, force call \'{}\''.format(oldValue, newValue, prop, e, self.fun.__name__))
+                    dependencyLogger.log(logging.WARN,
+                                         'Cannot compare values {}, {} for property \'{}\', exception {}, force call \'{}\''.format(oldValue, newValue,
+                                                                                                                                    prop, e, self.fun.__name__))
                     needToBuild = True
             except AttributeError:
                 raise AttributeError('Method \'{}\' has unsatisfied dependency on \'{}\''.format(self.fun.__name__, prop))
@@ -1768,6 +1773,7 @@ def changeLogLevel(self, properties, logLevel):
 class driverAddon:
     def __init__(self, driver):
         self.driver = driver
+        self._timer = None
         self.__parametrized_args__ = {}
         self.flags = []
         self.setDriverArgs()
@@ -1788,7 +1794,10 @@ def interpreter(v):
             for p in parametrizedArgs:
                 if self.parametrizedArg(p).match(v):
                     return v
-            raise ArgumentTypeError("\"{}\" is not in list of accepted values {} or cannot be interpreted as parametrized arg {}.".format(v, acceptedValues, [repr(self.parametrizedArg(p)) for p in parametrizedArgs]))
+            raise ArgumentTypeError(("\"{}\" is not in list of accepted values {} " +
+                                     "or cannot be interpreted as parametrized arg {}.").format(v, acceptedValues,
+                                                                                                [repr(self.parametrizedArg(p))
+                                                                                                 for p in parametrizedArgs]))
 
         return interpreter
 

drivers/runParallelGMG.py

@@ -282,8 +282,10 @@
         P0.num_columns = numGlobalDoFs0
         P.append(P0.to_csr())
 
-        coords.append(d.comm.reduce(P[-1].T @ (overlaps.getDistributeAsDiagonalOperator(lvl).to_csr()@hM[FINE].algebraicLevels[lvl].DoFMap.getDoFCoordinates())))
-        nullspace.append(d.comm.reduce(P[-1].T @ (overlaps.getDistributeAsDiagonalOperator(lvl).to_csr()@hM[FINE].algebraicLevels[lvl].DoFMap.ones())))
+        coords.append(d.comm.reduce(P[-1].T @ (overlaps.getDistributeAsDiagonalOperator(lvl).to_csr() @
+                                               hM[FINE].algebraicLevels[lvl].DoFMap.getDoFCoordinates())))
+        nullspace.append(d.comm.reduce(P[-1].T @ (overlaps.getDistributeAsDiagonalOperator(lvl).to_csr() @
+                                                  hM[FINE].algebraicLevels[lvl].DoFMap.ones())))
 
         A.append(d.comm.reduce((P[-1].T @ hM[FINE].algebraicLevels[lvl].A.to_csr() @ P[-1]).tocsr()))
 
@@ -294,7 +296,8 @@
     for k in range(len(lvls)-1):
         lvlC = lvls[k]
         lvlF = lvls[k+1]
-        P_ops.append(d.comm.reduce((P[lvlF].T @ overlaps.getDistributeAsDiagonalOperator(lvlF).to_csr() @ hM[FINE].algebraicLevels[lvlF].P.to_csr() @ P[lvlC]).tocsr()))
+        P_ops.append(d.comm.reduce((P[lvlF].T @ overlaps.getDistributeAsDiagonalOperator(lvlF).to_csr() @
+                                    hM[FINE].algebraicLevels[lvlF].P.to_csr() @ P[lvlC]).tocsr()))
 
     if d.comm.rank == 0:
         from scipy.io import mmwrite
@@ -319,8 +322,10 @@
         # A_global = CSR_LinearOperator.from_csr(A_global)
         # A2_global = CSR_LinearOperator.from_csr(A2_global)
         # P_global = CSR_LinearOperator.from_csr(P_global)
-        # mg = solverFactory('mg', hierarchy=[{'A': A2_global}, {'A': A_global, 'P': P_global, 'R': P_global.transpose()}], setup=True, smoother=('jacobi', {'presmoothingSteps': 2,
-        #                                                                                                                                                    'postsmoothingSteps': 2}))
+        # mg = solverFactory('mg', hierarchy=[{'A': A2_global}, {'A': A_global, 'P': P_global, 'R': P_global.transpose()}],
+        #                    setup=True,
+        #                    smoother=('jacobi', {'presmoothingSteps': 2,
+        #                                         'postsmoothingSteps': 2}))
         # print(mg)
         # cg = solverFactory('cg', A=A_global, setup=True, maxIter=d.maxiter, tolerance=tol)
         # cg.setPreconditioner(mg.asPreconditioner(), False)

fem/PyNucleus_fem/factories.py

@@ -176,6 +176,9 @@ def __call__(self, mesh, *args, **kwargs):
 meshFactory.register('circle', circle, 2, aliases=['disc', 'unitDisc', 'ball2d', '2dball'])
 meshFactory.register('graded_circle', graded_circle, 2, aliases=['gradedCircle'])
 meshFactory.register('discWithInteraction', discWithInteraction, 2)
+meshFactory.register('twinDisc', twinDisc, 2)
+meshFactory.register('dumbbell', dumbbell, 2)
+meshFactory.register('wrench', wrench, 2)
 meshFactory.register('cutoutCircle', cutoutCircle, 2, aliases=['cutoutDisc'])
 meshFactory.register('squareWithCircularCutout', squareWithCircularCutout, 2)
 meshFactory.register('boxWithBallCutout', boxWithBallCutout, 3, aliases=['boxMinusBall'])

fem/PyNucleus_fem/mesh.py

@@ -250,9 +250,9 @@ def doubleIntervalWithInteractions(a=0., b=1., c=2.,
                                    horizon1=0.1, horizon2=0.2,
                                    h=None):
 
-    def getNumCells(l, r):
+    def getNumCells(left, right):
         eps = 1e-8
-        return int(np.ceil((r-l-eps)/h))
+        return int(np.ceil((right-left-eps)/h))
 
     assert horizon2 >= horizon1
     assert horizon1 >= 0
@@ -341,7 +341,7 @@ def squareWithInteractions(ax, ay, bx, by,
         d1 = (circularSegment(bottomLeft, horizon, np.pi, 1.5*np.pi, numPointsPerUnitLength) +
               line(bottomLeft, bottomLeft-horizontalOffset) +
               line(bottomLeft, bottomLeft-verticalOffset) +
-              (lineHorizontal+bottomLeft)+
+              (lineHorizontal+bottomLeft) +
               (lineHorizontal+(bottomLeft-verticalOffset)))
 
         d2 = (circularSegment(bottomRight, horizon, -0.5*np.pi, 0., numPointsPerUnitLength) +
@@ -386,11 +386,11 @@ def squareWithInteractions(ax, ay, bx, by,
             assert np.allclose(yVals1, yVals2), (yVals1, yVals2)
 
             idx3 = np.logical_and(np.absolute(mesh.vertices_as_array[:, 1]-ay) < eps,
-                                np.logical_and(mesh.vertices_as_array[:, 0] >= ax-eps,
-                                               mesh.vertices_as_array[:, 0] <= bx+eps))
+                                  np.logical_and(mesh.vertices_as_array[:, 0] >= ax-eps,
+                                                 mesh.vertices_as_array[:, 0] <= bx+eps))
             idx4 = np.logical_and(np.absolute(mesh.vertices_as_array[:, 1]-by) < eps,
-                                np.logical_and(mesh.vertices_as_array[:, 0] >= ax-eps,
-                                               mesh.vertices_as_array[:, 0] <= bx+eps))
+                                  np.logical_and(mesh.vertices_as_array[:, 0] >= ax-eps,
+                                                 mesh.vertices_as_array[:, 0] <= bx+eps))
             xVals3 = np.sort(mesh.vertices_as_array[idx3, 0])
             xVals4 = np.sort(mesh.vertices_as_array[idx4, 0])
             assert np.allclose(xVals3, xVals4), (xVals3, xVals4)
@@ -2676,7 +2676,7 @@ class mesh3d(meshNd):
 
     def plot(self):
         import matplotlib.pyplot as plt
-        from mpl_toolkits.mplot3d import Axes3D
+        from mpl_toolkits.mplot3d import Axes3D  # noqa: F401
         from itertools import combinations
         fig = plt.figure()
         ax = fig.add_subplot(111, projection='3d')
@@ -2688,7 +2688,7 @@ def plot(self):
 
     def plot_surface(self, boundary=False):
         import matplotlib.pyplot as plt
-        from mpl_toolkits.mplot3d import Axes3D
+        from mpl_toolkits.mplot3d import Axes3D  # noqa: F401
         from mpl_toolkits.mplot3d.art3d import Poly3DCollection
         # from matplotlib import rcParams
         # from itertools import combinations

fem/PyNucleus_fem/meshConstruction.py

@@ -276,7 +276,7 @@ def rectangle(a, b, num_points=None, num_points_per_unit_len=None):
     def meshTransformation(x1, x2, xNew):
         eps = 1e-10
         if ((a[0]-eps <= x1[0] <= b[0]+eps) and (a[1]-eps <= x1[1] <= b[1]+eps) and
-            (a[0]-eps <= x2[0] <= b[0]+eps) and (a[1]-eps <= x2[1] <= b[1]+eps)):
+                (a[0]-eps <= x2[0] <= b[0]+eps) and (a[1]-eps <= x2[1] <= b[1]+eps)):
             xNew[:] = 0.5*(x1+x2)
             return True
 
@@ -290,6 +290,6 @@ def __init__(self, seg, p1, p2):
         for t in seg.meshTransformations:
             def transform(x1, x2, xNew):
                 if ((p1[0] <= xNew[0]) and (xNew[0] <= p2[0]) and
-                    (p1[1] <= xNew[1]) and (xNew[1] <= p2[1])):
+                        (p1[1] <= xNew[1]) and (xNew[1] <= p2[1])):
                     t(x1, x2, xNew)
             self.meshTransformations.append(transform)

multilevelSolver/PyNucleus_multilevelSolver/connectors.py

@@ -11,14 +11,12 @@
 from mpi4py import MPI
 import logging
 import numpy as np
-from PyNucleus_base.myTypes import REAL, INDEX, TAG
-from PyNucleus_base import uninitialized
+from PyNucleus_base.myTypes import REAL, INDEX
 from . levels import meshLevel, algebraicLevel
 from . hierarchies import EmptyHierarchy, hierarchy, pCoarsenHierarchy
 from PyNucleus_base.utilsFem import TimerManager
 from PyNucleus_fem.factories import meshFactory
 from PyNucleus_fem.repartitioner import Repartitioner
-from PyNucleus_fem.meshOverlaps import meshOverlap, interfaceManager
 
 LOGGER = logging.getLogger(__name__)
 
@@ -214,13 +212,15 @@ def getLocalOverlap(self):
         if self.is_overlapping and self.comm1 is not None:
             subdomain = self.hierarchy1.meshLevels[-1].mesh
             if self.global_comm.rank in self.OM.overlaps:
-                print('cells kept local on rank {} in repartitioning: {:,} / target: {:,}'.format(self.global_comm.rank,
-                                                                                                  self.OM.overlaps[self.global_comm.rank].num_cells/subdomain.num_cells,
-                                                                                                  self.comm1.size/self.global_comm.size))
+                print(('cells kept local on rank {} in repartitioning: ' +
+                       '{:,} / target: {:,}').format(self.global_comm.rank,
+                                                     self.OM.overlaps[self.global_comm.rank].num_cells/subdomain.num_cells,
+                                                     self.comm1.size/self.global_comm.size))
             else:
-                print('cells kept local on rank {} in repartitioning: {:,} / target: {:,}'.format(self.global_comm.rank,
-                                                                                                  0.,
-                                                                                                  self.comm1.size/self.global_comm.size))
+                print(('cells kept local on rank {} in repartitioning: ' +
+                       '{:,} / target: {:,}').format(self.global_comm.rank,
+                                                     0.,
+                                                     self.comm1.size/self.global_comm.size))
 
     def build(self):
         if self.hierarchy1 is not None:

multilevelSolver/PyNucleus_multilevelSolver/geometricMG.py

@@ -8,9 +8,7 @@
 from __future__ import division
 import logging
 import numpy as np
-from PyNucleus_base.utilsFem import getLoggingTimer
-from PyNucleus_base import REAL, INDEX, uninitialized
-from PyNucleus_fem import P1_DoFMap
+from PyNucleus_base import INDEX, uninitialized
 from PyNucleus_base.linear_operators import LinearOperator
 
 LOGGER = logging.getLogger(__name__)