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/petsc/src/dm/partitioner/impls/simple/
H A Dpartsimple.c50 PetscInt Np = 1, Nr, np, nk, nj, ni, pk, pj, pi, ck, cj, ci, i; in PetscPartitionerPartition_Simple_Grid() local
78 …for (np = 0; np < nparts; ++np) PetscCall(PetscSectionSetDof(partSection, np, numVertices / nparts… in PetscPartitionerPartition_Simple_Grid()
81 for (np = 0; np < nparts; ++np) PetscCall(PetscSectionGetOffset(partSection, np, &offsets[np])); in PetscPartitionerPartition_Simple_Grid()
111 …np = 1; np < nparts; ++np) PetscCheck(offsets[np] - offsets[np - 1] == numVertices / nparts, PETSC… in PetscPartitionerPartition_Simple_Grid()
121 PetscInt np, *tpwgts = NULL, sumw = 0, numVerticesGlobal = 0; in PetscPartitionerPartition_Simple() local
135 for (np = 0; np < nparts; ++np) { in PetscPartitionerPartition_Simple()
136 PetscCall(PetscSectionGetDof(targetSection, np, &tpwgts[np])); in PetscPartitionerPartition_Simple()
137 sumw += tpwgts[np]; in PetscPartitionerPartition_Simple()
141 for (np = 0; np < nparts; ++np) tpwgts[np] = (tpwgts[np] * numVerticesGlobal) / sumw; in PetscPartitionerPartition_Simple()
142 for (np = 0, m = -1, mp = 0, sumw = 0; np < nparts; ++np) { in PetscPartitionerPartition_Simple()
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/petsc/src/binding/petsc4py/demo/legacy/ode/
H A Dfastslowsplit.py15 import numpy as np namespace
26 u[0] = np.sqrt(2.0)
27 u[1] = np.sqrt(3.0)
32 -2.0 * (-1.0 + u[0] * u[0] - np.cos(t)) / (2.0 * u[0])
33 + 0.05 * (-2.0 + u[1] * u[1] - np.cos(5.0 * t)) / (2.0 * u[1])
34 - np.sin(t) / (2.0 * u[0])
37 0.05 * (-1.0 + u[0] * u[0] - np.cos(t)) / (2.0 * u[0])
38 - (-2.0 + u[1] * u[1] - np.cos(5.0 * t)) / (2.0 * u[1])
39 - 5.0 * np.sin(5.0 * t) / (2.0 * u[1])
45 -2.0 * (-1.0 + u[0] * u[0] - np.cos(t)) / (2.0 * u[0])
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H A Drober.py81 import numpy as np namespace
83 ii = np.asarray([v[0] for v in history])
84 tt = np.asarray([v[1] for v in history])
85 xx = np.asarray([v[2] for v in history])
92 np.diff(tt),
/petsc/lib/petsc/bin/
H A DPetscBinaryIO_tests.py19 array = np.array([1.1, 2.2, 3.3])
28 self.assertTrue(np.allclose(array, result))
32 array = np.array([1.1, 2.2, 3.3])
41 self.assertTrue(np.allclose(array, vec[...]))
46 indices = np.array([3,4,5])
64 vals = np.array([1.1,2.1,3.1])
65 counts = np.array([0,2,3])
66 cols = np.array([0,1,1])
74 self.assertTrue(np.allclose(vals, result[1][2]))
81 vals = np.array([1.1,2.1,3.1])
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H A Dpetsc_tas_analysis.py2 import numpy as np namespace
421 dofs = np.array(dofs, dtype=object)
422 errors = np.array(errors, dtype=object)
424 times = np.array(times)
425 meanTime = np.array(meanTime)
426 timesMin = np.array(timesMin)
427 timeGrowthRate = np.array(timeGrowthRate)
429 flops = np.array(flops)
430 meanFlop = np.array(meanFlop)
431 flopsMax = np.array(flopsMax)
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H A DPetscBinaryIO.py40 import numpy as np namespace
124 class Vec(np.ndarray):
135 class MatDense(np.matrix):
158 class IS(np.ndarray):
217 self._inttype = np.dtype('>i8')
219 self._inttype = np.dtype('>i4')
241 vals = np.fromfile(fh, dtype=self._scalartype, count=1)
252 nz = np.fromfile(fh, dtype=self._inttype, count=1)[0]
254 vals = np.fromfile(fh, dtype=self._scalartype, count=nz)
265 metadata = np.array([Vec._classid, len(vec)], dtype=self._inttype)
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H A DPetscBinaryIOTrajectory.py10 import numpy as np namespace
26 t.append(np.fromfile(fh, dtype=io._scalartype, count=1)[0])
33 nstrings = np.fromfile(fh, dtype=io._inttype, count=1)[0]
34 sizes = np.fromfile(fh, dtype=io._inttype, count=nstrings)
36 s = np.fromfile(fh, dtype=np.byte, count=sizes[i])
/petsc/src/tao/leastsquares/tutorials/matlab/
H A DProblemFinalize.m15 Results{SolverNumber,np}.alg = 'TAO Pounders';
16 Results{SolverNumber,np}.problem = ['problem ' num2str(np) ' from More/Wild'];
17 Results{SolverNumber,np}.H = fvals;
18 Results{SolverNumber,np}.X = X_hist;
19 Results{SolverNumber,np}.fvecs = fvecs;
48 Results{SolverNumber,np}.alg = 'fminsearch';
49 Results{SolverNumber,np}.problem = ['problem ' num2str(np) ' from More/Wild'];
50 Results{SolverNumber,np}.H = fvals;
51 Results{SolverNumber,np}.X = X_hist;
52 Results{SolverNumber,np}.fvecs = fvecs;
H A DProblemInitialize.m3 % The taopounders driver sets np, the problem instance number
6 nprob = dfo(np,1); % Internal index for the problem
7 n = dfo(np,2); % Number of variables
8 m = dfo(np,3); % Number of residuals
12 factor_power = dfo(np,4);
H A DTestingPlot.m20 for np = to_solve
22 H(1:length(Results{s,np}.H),np,s) = Results{s,np}.H;
/petsc/src/ksp/ksp/tests/
H A Dex22.c12 PetscInt n, np, i, j; in test_solve() local
18 np = 2; in test_solve()
32 PetscCall(MatMPIAIJSetPreallocation(A11, np, NULL, np, NULL)); in test_solve()
39 PetscCall(MatSetSizes(A12, PETSC_DECIDE, PETSC_DECIDE, n, np)); in test_solve()
41 PetscCall(MatSeqAIJSetPreallocation(A12, np, NULL)); in test_solve()
42 PetscCall(MatMPIAIJSetPreallocation(A12, np, NULL, np, NULL)); in test_solve()
45 for (j = 0; j < np; j++) PetscCall(MatSetValue(A12, i, j, i + j * n, INSERT_VALUES)); in test_solve()
122 PetscInt n, np, i, j; in test_solve_matgetvecs() local
130 np = 2; in test_solve_matgetvecs()
144 PetscCall(MatMPIAIJSetPreallocation(A11, np, NULL, np, NULL)); in test_solve_matgetvecs()
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/petsc/src/binding/petsc4py/demo/legacy/taosolve/
H A Dchwirut.py4 import numpy as np namespace
19 np.random.seed(456)
20 x = np.random.rand(NOBSERVATIONS)
21 e = np.random.rand(NOBSERVATIONS)
23 y = np.exp(-BETA[0]*x)/(BETA[1] + BETA[2]*x) + e
45 F.array = y - np.exp(-b1*x)/(b2 + b3*x)
54 u = np.linspace(x.min(), x.max(), 100)
55 v = np.exp(-b1*u)/(b2+b3*u)
/petsc/src/dm/partitioner/impls/gather/
H A Dpartgather.c16 PetscInt np; in PetscPartitionerPartition_Gather() local
21 for (np = 1; np < nparts; ++np) PetscCall(PetscSectionSetDof(partSection, np, 0)); in PetscPartitionerPartition_Gather()
/petsc/src/dm/impls/swarm/
H A Dswarmpic_da.c6 static PetscErrorCode private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular(PetscInt dim, PetscInt np[… in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular() argument
16 npoints = np[0]; in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
19 npoints = np[0] * np[1]; in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
22 npoints = np[0] * np[1] * np[2]; in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
25 for (d = 0; d < dim; d++) ds[d] = 2.0 / ((PetscReal)np[d]); in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
31 for (ii = 0; ii < np[0]; ii++) { in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
39 for (jj = 0; jj < np[1]; jj++) { in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
40 for (ii = 0; ii < np[0]; ii++) { in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
50 for (kk = 0; kk < np[2]; kk++) { in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
51 for (jj = 0; jj < np[1]; jj++) { in private_DMSwarmCreateCellLocalCoords_DA_Q1_Regular()
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H A Ddata_ex.c374 PetscMPIInt i, np; in _DMSwarmDataExConvertProcIdToLocalIndex() local
377 np = de->n_neighbour_procs; in _DMSwarmDataExConvertProcIdToLocalIndex()
379 for (i = 0; i < np; ++i) { in _DMSwarmDataExConvertProcIdToLocalIndex()
438 PetscMPIInt i, np; in _DMSwarmDataExInitializeTmpStorage() local
441 np = de->n_neighbour_procs; in _DMSwarmDataExInitializeTmpStorage()
442 for (i = 0; i < np; ++i) { in _DMSwarmDataExInitializeTmpStorage()
459 PetscMPIInt i, np; in DMSwarmDataExPackInitialize() local
468 np = de->n_neighbour_procs; in DMSwarmDataExPackInitialize()
471 for (i = 0; i < np; ++i) { in DMSwarmDataExPackInitialize()
486 for (i = 1; i < np; ++i) { in DMSwarmDataExPackInitialize()
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/petsc/src/binding/petsc4py/demo/legacy/dmplex/
H A Ddistribute_field.py11 import numpy as np namespace
15 coords = np.asarray([[0.0, 0.0],
24 cells = np.asarray([[0,1,4,3],
29 coords = np.zeros((0, 2), dtype=PETSc.RealType)
30 cells = np.zeros((0, 4), dtype=PETSc.IntType)
/petsc/share/petsc/matlab/
H A Dlaunch.m1 function result = launch(program,np,opt)
3 % launch(program,np)
16 np = 1; variable
25 %command = ['petscmpiexec -np ' int2str(np) ' ' program opt ' &'];
/petsc/src/binding/petsc4py/demo/regressor/
H A Dtest_regressor_synthetic.py7 import numpy as np namespace
52 rows_ix = np.arange(ntr,dtype=np.int32)
53 cols_ix = np.arange(nfeature,dtype=np.int32)
69 rows_ix = np.arange(nte,dtype=np.int32)
94 plt_ind_list = np.arange(6)+231
/petsc/src/binding/petsc4py/src/petsc4py/
H A Dtyping.py15 import numpy as np namespace
114 ArrayBool = NDArray[np.bool_]
117 ArrayInt = NDArray[np.integer]
120 ArrayReal = NDArray[np.floating]
123 ArrayComplex = NDArray[np.complexfloating]
126 ArrayScalar = NDArray[np.floating | np.complexfloating]
384 TSIndicatorFunction = Callable[[TS, float, Vec, NDArray[np.floating]], None]
387 TSPostEventFunction = Callable[[TS, NDArray[np.integer], float, Vec, bool], None]
/petsc/src/vec/vec/tutorials/
H A Dex42.m1 function ex42(np,opt)
3 % ex42(np,opt) - launches ./ex42 and runs a loop 1000 times sending and then receiving a one dimen…
13 np = 1; variable
18 launch('./ex42 ',np,opt);
/petsc/src/dm/tests/
H A Dex12.m1 function ex12(np,opt)
3 % From MATLAB run ex12(np)
16 np = 1; variable
22 launch(['./ex12 -time ' int2str(time) opt],np);
/petsc/src/ksp/ksp/tutorials/
H A Dex41.m1 function ex41(np,opt)
3 % ex41(np,opt) - receives a matrix and vector from MATLAB via socket
14 np = 1; variable
19 launch('./ex41 ',np,opt);
/petsc/src/ksp/ksp/impls/symmlq/
H A Dsymmlq.c20 PetscReal np = 0.0, s_prod; in KSPSolve_SYMMLQ() local
84 PetscCall(VecNorm(Z, NORM_2, &np)); /* np <- ||z|| */ in KSPSolve_SYMMLQ()
85 KSPCheckNorm(ksp, np); in KSPSolve_SYMMLQ()
87 PetscCall(KSPLogResidualHistory(ksp, np)); in KSPSolve_SYMMLQ()
88 PetscCall(KSPMonitor(ksp, 0, np)); in KSPSolve_SYMMLQ()
89 ksp->rnorm = np; in KSPSolve_SYMMLQ()
90 PetscCall((*ksp->converged)(ksp, 0, np, &ksp->reason, ksp->cnvP)); /* test for convergence */ in KSPSolve_SYMMLQ()
162 if (c == 0.0) np = s_prod * 1.e16; in KSPSolve_SYMMLQ()
163 else np = s_prod / PetscAbsScalar(c); /* residual norm for xc_k (CGNORM) */ in KSPSolve_SYMMLQ()
165 if (ksp->normtype != KSP_NORM_NONE) ksp->rnorm = np; in KSPSolve_SYMMLQ()
/petsc/config/BuildSystem/config/packages/
H A Dpetsc4py.py89 np = self.make.make_test_np
91 np = 1
93 np = min(np,4)
95 np = self.argDB['with-petsc4py-test-np']
96 self.addMakeMacro('PETSC4PY_NP',np)
/petsc/src/binding/petsc4py/src/petsc4py/lib/_pytypes/viewer/
H A Dpetscpyvista.py2 import numpy as np namespace
80 cells = np.zeros((conesLength), dtype=np.uint32)
94 celltypes = np.zeros((cEnd - cStart), dtype=np.uint32)
97 points = np.zeros((vEnd - vStart, 3), dtype=np.float32)
122 vecs = np.zeros((scalars[1].shape[0] // scalars[2], 3))
141 …grid.point_data["magnitudes"] = self.glyphScale * np.linalg.norm(grid.point_data[scalars[0]], axis…
160 points = np.zeros((n, 3))
168 field = np.zeros((n,))

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