Merge remote-tracking branch 'origin/typehints_rngseed' into development

python/damask/_typehints.py

@@ -9,3 +9,4 @@ import numpy as np
 FloatSequence = Union[np.ndarray,Sequence[float]]
 IntSequence = Union[np.ndarray,Sequence[int]]
 FileHandle = Union[TextIO, str, Path]
+NumpyRngSeed = Union[int, IntSequence, np.random.SeedSequence, np.random.BitGenerator, np.random.Generator]

python/damask/seeds.py

@@ -1,3 +1,4 @@
+
 """Functionality for generation of seed points for Voronoi or Laguerre tessellation."""
 
 from typing import Tuple as _Tuple
@@ -5,7 +6,7 @@ from typing import Tuple as _Tuple
 from scipy import spatial as _spatial
 import numpy as _np
 
-from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence
+from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence, NumpyRngSeed as _NumpyRngSeed
 from . import util as _util
 from . import grid_filters as _grid_filters
 
@@ -13,7 +14,7 @@ from . import grid_filters as _grid_filters
 def from_random(size: _FloatSequence,
                 N_seeds: int,
                 cells: _IntSequence = None,
-                rng_seed=None) -> _np.ndarray:
+                rng_seed: _NumpyRngSeed = None) -> _np.ndarray:
     """
     Place seeds randomly in space.
 
@@ -53,7 +54,7 @@ def from_Poisson_disc(size: _FloatSequence,
                       N_candidates: int,
                       distance: float,
                       periodic: bool = True,
-                      rng_seed=None) -> _np.ndarray:
+                      rng_seed: _NumpyRngSeed = None) -> _np.ndarray:
     """
     Place seeds according to a Poisson disc distribution.
 

python/damask/util.py

@@ -16,7 +16,7 @@ import numpy as np
 import h5py
 
 from . import version
-from ._typehints import IntSequence, FloatSequence
+from ._typehints import FloatSequence, NumpyRngSeed
 
 # limit visibility
 __all__=[
@@ -396,7 +396,7 @@ def execution_stamp(class_name: str,
 
 def hybrid_IA(dist: np.ndarray,
               N: int,
-              rng_seed: Union[int, IntSequence] = None) -> np.ndarray:
+              rng_seed: NumpyRngSeed = None) -> np.ndarray:
     """
     Hybrid integer approximation.
 

src/polynomials.f90

@@ -163,7 +163,7 @@ subroutine selfTest
            'T_ref: '//trim(adjustl(x_ref_s))//IO_EOL
   Dict => YAML_parse_str(trim(YAML_s))
   p2 = polynomial(dict%asDict(),'C','T')
-  if (dNeq(p1%at(x),p2%at(x),1.0e-12_pReal))                      error stop 'polynomials: init'
+  if (dNeq(p1%at(x),p2%at(x),1.0e-10_pReal))                      error stop 'polynomials: init'
 
   p1 = polynomial(coef*[0.0_pReal,1.0_pReal,0.0_pReal],x_ref)
   if (dNeq(p1%at(x_ref+x),-p1%at(x_ref-x),1.0e-10_pReal))         error stop 'polynomials: eval(odd)'