Merge branch '151_typehints-readability' into 'development'
better readabiliy for python See merge request damask/DAMASK!511
This commit is contained in:
Sharan Roongta
commit
225a5d9086
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@ -47,27 +47,32 @@ class Colormap(mpl.colors.ListedColormap):
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"""
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def __eq__(self, other: object) -> bool:
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def __eq__(self,
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other: object) -> bool:
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"""Test equality of colormaps."""
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if not isinstance(other, Colormap):
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return NotImplemented
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return len(self.colors) == len(other.colors) \
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and bool(np.all(self.colors == other.colors))
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def __add__(self, other: 'Colormap') -> 'Colormap':
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def __add__(self,
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other: 'Colormap') -> 'Colormap':
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"""Concatenate."""
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return Colormap(np.vstack((self.colors,other.colors)),
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f'{self.name}+{other.name}')
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def __iadd__(self, other: 'Colormap') -> 'Colormap':
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def __iadd__(self,
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other: 'Colormap') -> 'Colormap':
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"""Concatenate (in-place)."""
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return self.__add__(other)
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def __mul__(self, factor: int) -> 'Colormap':
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def __mul__(self,
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factor: int) -> 'Colormap':
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"""Repeat."""
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return Colormap(np.vstack([self.colors]*factor),f'{self.name}*{factor}')
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def __imul__(self, factor: int) -> 'Colormap':
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def __imul__(self,
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factor: int) -> 'Colormap':
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"""Repeat (in-place)."""
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return self.__mul__(factor)
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@ -161,7 +166,8 @@ class Colormap(mpl.colors.ListedColormap):
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@staticmethod
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def from_predefined(name: str, N: int = 256) -> 'Colormap':
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def from_predefined(name: str,
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N: int = 256) -> 'Colormap':
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"""
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Select from a set of predefined colormaps.
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@ -260,10 +266,8 @@ class Colormap(mpl.colors.ListedColormap):
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l,r = (field[mask].min(),field[mask].max()) if bounds is None else \
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(bounds[0],bounds[1])
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delta,avg = r-l,0.5*abs(r+l)
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if abs(delta) * 1e8 <= avg: # delta is similar to numerical noise
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l,r = l-0.5*avg*np.sign(delta),r+0.5*avg*np.sign(delta), # extend range to have actual data centered within
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if abs(delta := r-l) * 1e8 <= (avg := 0.5*abs(r+l)): # delta is similar to numerical noise
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l,r = (l-0.5*avg*np.sign(delta),r+0.5*avg*np.sign(delta)) # extend range to have actual data centered within
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return Image.fromarray(
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(np.dstack((
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@ -275,7 +279,8 @@ class Colormap(mpl.colors.ListedColormap):
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mode='RGBA')
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def reversed(self, name: str = None) -> 'Colormap':
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def reversed(self,
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name: str = None) -> 'Colormap':
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"""
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Reverse.
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@ -296,7 +301,7 @@ class Colormap(mpl.colors.ListedColormap):
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>>> damask.Colormap.from_predefined('stress').reversed()
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"""
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rev = super(Colormap,self).reversed(name)
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rev = super().reversed(name)
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return Colormap(np.array(rev.colors),rev.name[:-4] if rev.name.endswith('_r_r') else rev.name)
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@ -328,7 +333,8 @@ class Colormap(mpl.colors.ListedColormap):
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return fname
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def save_paraview(self, fname: FileHandle = None):
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def save_paraview(self,
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fname: FileHandle = None):
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"""
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Save as JSON file for use in Paraview.
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@ -355,7 +361,8 @@ class Colormap(mpl.colors.ListedColormap):
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fhandle.write('\n')
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def save_ASCII(self, fname: FileHandle = None):
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def save_ASCII(self,
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fname: FileHandle = None):
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"""
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Save as ASCII file.
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@ -390,7 +397,8 @@ class Colormap(mpl.colors.ListedColormap):
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self._get_file_handle(fname,'.legend').write(GOM_str)
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def save_gmsh(self, fname: FileHandle = None):
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def save_gmsh(self,
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fname: FileHandle = None):
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"""
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Save as ASCII file for use in gmsh.
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@ -428,11 +436,11 @@ class Colormap(mpl.colors.ListedColormap):
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def adjust_hue(msh_sat, msh_unsat):
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"""If saturation of one of the two colors is much less than the other, hue of the less."""
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if msh_sat[0] >= msh_unsat[0]:
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return msh_sat[2]
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else:
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hSpin = msh_sat[1]/np.sin(msh_sat[1])*np.sqrt(msh_unsat[0]**2.0-msh_sat[0]**2)/msh_sat[0]
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if msh_sat[2] < - np.pi/3.0: hSpin *= -1.0
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return msh_sat[2] + hSpin
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return msh_sat[2]
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hSpin = msh_sat[1]/np.sin(msh_sat[1])*np.sqrt(msh_unsat[0]**2.0-msh_sat[0]**2)/msh_sat[0]
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if msh_sat[2] < - np.pi/3.0: hSpin *= -1.0
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return msh_sat[2] + hSpin
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lo = np.array(low)
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hi = np.array(high)
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@ -445,9 +453,9 @@ class Colormap(mpl.colors.ListedColormap):
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else:
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lo = np.array([M_mid,0.0,0.0])
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frac = 2.0*frac - 1.0
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if lo[1] < 0.05 and hi[1] > 0.05:
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if lo[1] < 0.05 < hi[1]:
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lo[2] = adjust_hue(hi,lo)
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elif lo[1] > 0.05 and hi[1] < 0.05:
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elif hi[1] < 0.05 < lo[1]:
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hi[2] = adjust_hue(lo,hi)
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return (1.0 - frac) * lo + frac * hi
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@ -476,7 +484,7 @@ class Colormap(mpl.colors.ListedColormap):
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'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg',
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'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar']}
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_predefined_DAMASK = {'orientation': {'low': [0.933334,0.878432,0.878431],
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_predefined_DAMASK = {'orientation': {'low': [0.933334,0.878432,0.878431], # noqa
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'high': [0.250980,0.007843,0.000000]},
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'strain': {'low': [0.941177,0.941177,0.870588],
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'high': [0.266667,0.266667,0.000000]},
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@ -621,7 +629,8 @@ class Colormap(mpl.colors.ListedColormap):
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@staticmethod
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def _lab2xyz(lab: np.ndarray, ref_white: np.ndarray = _REF_WHITE) -> np.ndarray:
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def _lab2xyz(lab: np.ndarray,
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ref_white: np.ndarray = _REF_WHITE) -> np.ndarray:
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"""
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CIE Lab to CIE Xyz.
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@ -652,7 +661,8 @@ class Colormap(mpl.colors.ListedColormap):
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])*ref_white
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@staticmethod
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def _xyz2lab(xyz: np.ndarray, ref_white: np.ndarray = _REF_WHITE) -> np.ndarray:
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def _xyz2lab(xyz: np.ndarray,
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ref_white: np.ndarray = _REF_WHITE) -> np.ndarray:
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"""
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CIE Xyz to CIE Lab.
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@ -33,9 +33,9 @@ class Crystal():
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def __init__(self,*,
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family = None,
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lattice = None,
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a = None,b = None,c = None,
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alpha = None,beta = None,gamma = None,
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degrees = False):
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a: float = None, b: float = None, c: float = None,
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alpha: float = None, beta: float = None, gamma: float = None,
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degrees: bool = False):
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"""
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Representation of crystal in terms of crystal family or Bravais lattice.
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@ -62,7 +62,7 @@ class Crystal():
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Angles are given in degrees. Defaults to False.
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"""
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if family not in [None] + list(lattice_symmetries.values()):
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if family is not None and family not in list(lattice_symmetries.values()):
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raise KeyError(f'invalid crystal family "{family}"')
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if lattice is not None and family is not None and family != lattice_symmetries[lattice]:
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raise KeyError(f'incompatible family "{family}" for lattice "{lattice}"')
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@ -107,9 +107,6 @@ class Crystal():
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if np.any([np.roll([self.alpha,self.beta,self.gamma],r)[0]
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>= np.sum(np.roll([self.alpha,self.beta,self.gamma],r)[1:]) for r in range(3)]):
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raise ValueError ('each lattice angle must be less than sum of others')
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else:
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self.a = self.b = self.c = None
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self.alpha = self.beta = self.gamma = None
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def __repr__(self):
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@ -122,7 +119,8 @@ class Crystal():
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'α={:.5g}°, β={:.5g}°, γ={:.5g}°'.format(*np.degrees(self.parameters[3:]))])
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def __eq__(self,other):
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def __eq__(self,
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other: object) -> bool:
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"""
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Equal to other.
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@ -132,6 +130,8 @@ class Crystal():
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Crystal to check for equality.
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"""
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if not isinstance(other, Crystal):
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return NotImplemented
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return self.lattice == other.lattice and \
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self.parameters == other.parameters and \
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self.family == other.family
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@ -139,8 +139,7 @@ class Crystal():
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@property
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def parameters(self):
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"""Return lattice parameters a, b, c, alpha, beta, gamma."""
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return (self.a,self.b,self.c,self.alpha,self.beta,self.gamma)
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if hasattr(self,'a'): return (self.a,self.b,self.c,self.alpha,self.beta,self.gamma)
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@property
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def immutable(self):
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@ -269,7 +268,7 @@ class Crystal():
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https://doi.org/10.1063/1.1661333
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"""
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if None in self.parameters:
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if self.parameters is None:
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raise KeyError('missing crystal lattice parameters')
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return np.array([
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[1,0,0],
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@ -315,7 +314,9 @@ class Crystal():
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+ _lattice_points.get(self.lattice if self.lattice == 'hP' else \
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self.lattice[-1],None),dtype=float)
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def to_lattice(self, *, direction: np.ndarray = None, plane: np.ndarray = None) -> np.ndarray:
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def to_lattice(self, *,
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direction: np.ndarray = None,
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plane: np.ndarray = None) -> np.ndarray:
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"""
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Calculate lattice vector corresponding to crystal frame direction or plane normal.
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@ -339,7 +340,9 @@ class Crystal():
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return np.einsum('il,...l',basis,axis)
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def to_frame(self, *, uvw: np.ndarray = None, hkl: np.ndarray = None) -> np.ndarray:
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def to_frame(self, *,
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uvw: np.ndarray = None,
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hkl: np.ndarray = None) -> np.ndarray:
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"""
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Calculate crystal frame vector along lattice direction [uvw] or plane normal (hkl).
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@ -362,7 +365,8 @@ class Crystal():
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return np.einsum('il,...l',basis,axis)
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def kinematics(self, mode: str) -> Dict[str, List[np.ndarray]]:
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def kinematics(self,
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mode: str) -> Dict[str, List[np.ndarray]]:
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"""
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Return crystal kinematics systems.
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@ -621,7 +625,8 @@ class Crystal():
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'plane': [m[:,3:6] for m in master]}
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def relation_operations(self, model: str) -> Tuple[str, Rotation]:
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def relation_operations(self,
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model: str) -> Tuple[str, Rotation]:
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"""
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Crystallographic orientation relationships for phase transformations.
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@ -4,7 +4,7 @@ import warnings
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import multiprocessing as mp
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from functools import partial
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import typing
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from typing import Union, Optional, TextIO, List, Sequence, Literal
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from typing import Union, Optional, TextIO, List, Sequence
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from pathlib import Path
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import numpy as np
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@ -33,7 +33,7 @@ class Grid:
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material: np.ndarray,
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size: FloatSequence,
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origin: FloatSequence = np.zeros(3),
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comments: Union[str, Sequence[str]] = []):
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comments: Union[str, Sequence[str]] = None):
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"""
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New geometry definition for grid solvers.
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@ -53,7 +53,7 @@ class Grid:
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self.material = material
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self.size = size # type: ignore
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self.origin = origin # type: ignore
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self.comments = comments # type: ignore
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self.comments = [] if comments is None else comments # type: ignore
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def __repr__(self) -> str:
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@ -77,7 +77,8 @@ class Grid:
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copy = __copy__
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def __eq__(self, other: object) -> bool:
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def __eq__(self,
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other: object) -> bool:
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"""
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Test equality of other.
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@ -101,17 +102,18 @@ class Grid:
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return self._material
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@material.setter
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def material(self, material: np.ndarray):
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def material(self,
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material: np.ndarray):
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if len(material.shape) != 3:
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raise ValueError(f'invalid material shape {material.shape}')
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elif material.dtype not in np.sctypes['float'] and material.dtype not in np.sctypes['int']:
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if material.dtype not in np.sctypes['float'] and material.dtype not in np.sctypes['int']:
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raise TypeError(f'invalid material data type {material.dtype}')
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else:
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self._material = np.copy(material)
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if self.material.dtype in np.sctypes['float'] and \
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np.all(self.material == self.material.astype(int).astype(float)):
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self._material = self.material.astype(int)
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self._material = np.copy(material)
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if self.material.dtype in np.sctypes['float'] and \
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np.all(self.material == self.material.astype(int).astype(float)):
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self._material = self.material.astype(int)
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@property
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@ -120,11 +122,12 @@ class Grid:
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return self._size
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@size.setter
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def size(self, size: FloatSequence):
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def size(self,
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size: FloatSequence):
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if len(size) != 3 or any(np.array(size) < 0):
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raise ValueError(f'invalid size {size}')
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else:
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self._size = np.array(size)
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self._size = np.array(size)
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@property
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def origin(self) -> np.ndarray:
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@ -132,11 +135,12 @@ class Grid:
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return self._origin
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@origin.setter
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def origin(self, origin: FloatSequence):
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def origin(self,
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origin: FloatSequence):
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if len(origin) != 3:
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raise ValueError(f'invalid origin {origin}')
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else:
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self._origin = np.array(origin)
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self._origin = np.array(origin)
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@property
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def comments(self) -> List[str]:
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@ -144,7 +148,8 @@ class Grid:
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return self._comments
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@comments.setter
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def comments(self, comments: Union[str, Sequence[str]]):
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def comments(self,
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comments: Union[str, Sequence[str]]):
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self._comments = [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
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@ -229,8 +234,7 @@ class Grid:
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content = f.readlines()
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for i,line in enumerate(content[:header_length]):
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items = line.split('#')[0].lower().strip().split()
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key = items[0] if items else ''
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if key == 'grid':
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if (key := items[0] if items else '') == 'grid':
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cells = np.array([ int(dict(zip(items[1::2],items[2::2]))[i]) for i in ['a','b','c']])
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elif key == 'size':
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size = np.array([float(dict(zip(items[1::2],items[2::2]))[i]) for i in ['x','y','z']])
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@ -242,8 +246,7 @@ class Grid:
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material = np.empty(int(cells.prod())) # initialize as flat array
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i = 0
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for line in content[header_length:]:
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items = line.split('#')[0].split()
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if len(items) == 3:
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if len(items := line.split('#')[0].split()) == 3:
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if items[1].lower() == 'of':
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material_entry = np.ones(int(items[0]))*float(items[2])
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elif items[1].lower() == 'to':
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@ -387,7 +390,9 @@ class Grid:
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@staticmethod
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def _find_closest_seed(seeds: np.ndarray, weights: np.ndarray, point: np.ndarray) -> np.integer:
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def _find_closest_seed(seeds: np.ndarray,
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weights: np.ndarray,
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point: np.ndarray) -> np.integer:
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return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
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@staticmethod
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@ -624,7 +629,9 @@ class Grid:
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|||
)
|
||||
|
||||
|
||||
def save(self, fname: Union[str, Path], compress: bool = True):
|
||||
def save(self,
|
||||
fname: Union[str, Path],
|
||||
compress: bool = True):
|
||||
"""
|
||||
Save as VTK image data file.
|
||||
|
||||
|
|
@ -643,7 +650,8 @@ class Grid:
|
|||
v.save(fname,parallel=False,compress=compress)
|
||||
|
||||
|
||||
def save_ASCII(self, fname: Union[str, TextIO]):
|
||||
def save_ASCII(self,
|
||||
fname: Union[str, TextIO]):
|
||||
"""
|
||||
Save as geom file.
|
||||
|
||||
|
|
@ -770,15 +778,16 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def mirror(self, directions: Sequence[str], reflect: bool = False) -> 'Grid':
|
||||
def mirror(self,
|
||||
directions: Sequence[str],
|
||||
reflect: bool = False) -> 'Grid':
|
||||
"""
|
||||
Mirror grid along given directions.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
directions : (sequence of) str
|
||||
directions : (sequence of) {'x', 'y', 'z'}
|
||||
Direction(s) along which the grid is mirrored.
|
||||
Valid entries are 'x', 'y', 'z'.
|
||||
reflect : bool, optional
|
||||
Reflect (include) outermost layers. Defaults to False.
|
||||
|
||||
|
|
@ -801,8 +810,7 @@ class Grid:
|
|||
# materials: 1
|
||||
|
||||
"""
|
||||
valid = ['x','y','z']
|
||||
if not set(directions).issubset(valid):
|
||||
if not set(directions).issubset(valid := ['x', 'y', 'z']):
|
||||
raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
|
||||
|
||||
limits: Sequence[Optional[int]] = [None,None] if reflect else [-2,0]
|
||||
|
|
@ -822,15 +830,15 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def flip(self, directions: Union[Literal['x', 'y', 'z'], Sequence[Literal['x', 'y', 'z']]]) -> 'Grid':
|
||||
def flip(self,
|
||||
directions: Sequence[str]) -> 'Grid':
|
||||
"""
|
||||
Flip grid along given directions.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
directions : (sequence of) str
|
||||
directions : (sequence of) {'x', 'y', 'z'}
|
||||
Direction(s) along which the grid is flipped.
|
||||
Valid entries are 'x', 'y', 'z'.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -838,8 +846,7 @@ class Grid:
|
|||
Updated grid-based geometry.
|
||||
|
||||
"""
|
||||
valid = ['x','y','z']
|
||||
if not set(directions).issubset(valid):
|
||||
if not set(directions).issubset(valid := ['x', 'y', 'z']):
|
||||
raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
|
||||
|
||||
|
||||
|
|
@ -852,7 +859,9 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def scale(self, cells: IntSequence, periodic: bool = True) -> 'Grid':
|
||||
def scale(self,
|
||||
cells: IntSequence,
|
||||
periodic: bool = True) -> 'Grid':
|
||||
"""
|
||||
Scale grid to new cells.
|
||||
|
||||
|
|
@ -958,7 +967,9 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def rotate(self, R: Rotation, fill: int = None) -> 'Grid':
|
||||
def rotate(self,
|
||||
R: Rotation,
|
||||
fill: int = None) -> 'Grid':
|
||||
"""
|
||||
Rotate grid (pad if required).
|
||||
|
||||
|
|
@ -1049,7 +1060,9 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def substitute(self, from_material: IntSequence, to_material: IntSequence) -> 'Grid':
|
||||
def substitute(self,
|
||||
from_material: IntSequence,
|
||||
to_material: IntSequence) -> 'Grid':
|
||||
"""
|
||||
Substitute material indices.
|
||||
|
||||
|
|
@ -1150,7 +1163,9 @@ class Grid:
|
|||
)
|
||||
|
||||
|
||||
def get_grain_boundaries(self, periodic: bool = True, directions: Sequence[str] = 'xyz'):
|
||||
def get_grain_boundaries(self,
|
||||
periodic: bool = True,
|
||||
directions: Sequence[str] = 'xyz') -> VTK:
|
||||
"""
|
||||
Create VTK unstructured grid containing grain boundaries.
|
||||
|
||||
|
|
@ -1158,9 +1173,9 @@ class Grid:
|
|||
----------
|
||||
periodic : bool, optional
|
||||
Assume grid to be periodic. Defaults to True.
|
||||
directions : (sequence of) string, optional
|
||||
directions : (sequence of) {'x', 'y', 'z'}, optional
|
||||
Direction(s) along which the boundaries are determined.
|
||||
Valid entries are 'x', 'y', 'z'. Defaults to 'xyz'.
|
||||
Defaults to 'xyz'.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -1168,8 +1183,7 @@ class Grid:
|
|||
VTK-based geometry of grain boundary network.
|
||||
|
||||
"""
|
||||
valid = ['x','y','z']
|
||||
if not set(directions).issubset(valid):
|
||||
if not set(directions).issubset(valid := ['x', 'y', 'z']):
|
||||
raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
|
||||
|
||||
o = [[0, self.cells[0]+1, np.prod(self.cells[:2]+1)+self.cells[0]+1, np.prod(self.cells[:2]+1)],
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import re
|
||||
import copy
|
||||
from pathlib import Path
|
||||
from typing import Union, Optional, Tuple, List
|
||||
from typing import Union, Tuple, List
|
||||
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
|
|
@ -12,7 +12,10 @@ from . import util
|
|||
class Table:
|
||||
"""Manipulate multi-dimensional spreadsheet-like data."""
|
||||
|
||||
def __init__(self, data: np.ndarray, shapes: dict, comments: Optional[Union[str, list]] = None):
|
||||
def __init__(self,
|
||||
data: np.ndarray,
|
||||
shapes: dict,
|
||||
comments: Union[str, list] = None):
|
||||
"""
|
||||
New spreadsheet.
|
||||
|
||||
|
|
@ -41,7 +44,8 @@ class Table:
|
|||
return '\n'.join(['# '+c for c in self.comments])+'\n'+data_repr
|
||||
|
||||
|
||||
def __getitem__(self, item: Union[slice, Tuple[slice, ...]]) -> 'Table':
|
||||
def __getitem__(self,
|
||||
item: Union[slice, Tuple[slice, ...]]) -> 'Table':
|
||||
"""
|
||||
Slice the Table according to item.
|
||||
|
||||
|
|
@ -100,7 +104,9 @@ class Table:
|
|||
copy = __copy__
|
||||
|
||||
|
||||
def _label(self, what: Union[str, List[str]], how: str) -> List[str]:
|
||||
def _label(self,
|
||||
what: Union[str, List[str]],
|
||||
how: str) -> List[str]:
|
||||
"""
|
||||
Expand labels according to data shape.
|
||||
|
||||
|
|
@ -131,7 +137,8 @@ class Table:
|
|||
return labels
|
||||
|
||||
|
||||
def _relabel(self, how: str):
|
||||
def _relabel(self,
|
||||
how: str):
|
||||
"""
|
||||
Modify labeling of data in-place.
|
||||
|
||||
|
|
@ -147,7 +154,10 @@ class Table:
|
|||
self.data.columns = self._label(self.shapes,how) #type: ignore
|
||||
|
||||
|
||||
def _add_comment(self, label: str, shape: Tuple[int, ...], info: Optional[str]):
|
||||
def _add_comment(self,
|
||||
label: str,
|
||||
shape: Tuple[int, ...],
|
||||
info: str = None):
|
||||
if info is not None:
|
||||
specific = f'{label}{" "+str(shape) if np.prod(shape,dtype=int) > 1 else ""}: {info}'
|
||||
general = util.execution_stamp('Table')
|
||||
|
|
@ -309,8 +319,7 @@ class Table:
|
|||
data = np.loadtxt(content)
|
||||
|
||||
shapes = {'eu':3, 'pos':2, 'IQ':1, 'CI':1, 'ID':1, 'intensity':1, 'fit':1}
|
||||
remainder = data.shape[1]-sum(shapes.values())
|
||||
if remainder > 0: # 3.8 can do: if (remainder := data.shape[1]-sum(shapes.values())) > 0
|
||||
if (remainder := data.shape[1]-sum(shapes.values())) > 0:
|
||||
shapes['unknown'] = remainder
|
||||
|
||||
return Table(data,shapes,comments)
|
||||
|
|
@ -321,7 +330,8 @@ class Table:
|
|||
return list(self.shapes)
|
||||
|
||||
|
||||
def get(self, label: str) -> np.ndarray:
|
||||
def get(self,
|
||||
label: str) -> np.ndarray:
|
||||
"""
|
||||
Get column data.
|
||||
|
||||
|
|
@ -341,7 +351,10 @@ class Table:
|
|||
return data.astype(type(data.flatten()[0]))
|
||||
|
||||
|
||||
def set(self, label: str, data: np.ndarray, info: str = None) -> 'Table':
|
||||
def set(self,
|
||||
label: str,
|
||||
data: np.ndarray,
|
||||
info: str = None) -> 'Table':
|
||||
"""
|
||||
Set column data.
|
||||
|
||||
|
|
@ -362,8 +375,7 @@ class Table:
|
|||
"""
|
||||
dup = self.copy()
|
||||
dup._add_comment(label, data.shape[1:], info)
|
||||
m = re.match(r'(.*)\[((\d+,)*(\d+))\]',label)
|
||||
if m:
|
||||
if m := re.match(r'(.*)\[((\d+,)*(\d+))\]',label):
|
||||
key = m.group(1)
|
||||
idx = np.ravel_multi_index(tuple(map(int,m.group(2).split(","))),
|
||||
self.shapes[key])
|
||||
|
|
@ -374,7 +386,10 @@ class Table:
|
|||
return dup
|
||||
|
||||
|
||||
def add(self, label: str, data: np.ndarray, info: str = None) -> 'Table':
|
||||
def add(self,
|
||||
label: str,
|
||||
data: np.ndarray,
|
||||
info: str = None) -> 'Table':
|
||||
"""
|
||||
Add column data.
|
||||
|
||||
|
|
@ -406,7 +421,8 @@ class Table:
|
|||
return dup
|
||||
|
||||
|
||||
def delete(self, label: str) -> 'Table':
|
||||
def delete(self,
|
||||
label: str) -> 'Table':
|
||||
"""
|
||||
Delete column data.
|
||||
|
||||
|
|
@ -427,7 +443,10 @@ class Table:
|
|||
return dup
|
||||
|
||||
|
||||
def rename(self, old: Union[str, List[str]], new: Union[str, List[str]], info: str = None) -> 'Table':
|
||||
def rename(self,
|
||||
old: Union[str, List[str]],
|
||||
new: Union[str, List[str]],
|
||||
info: str = None) -> 'Table':
|
||||
"""
|
||||
Rename column data.
|
||||
|
||||
|
|
@ -453,7 +472,9 @@ class Table:
|
|||
return dup
|
||||
|
||||
|
||||
def sort_by(self, labels: Union[str, List[str]], ascending: Union[bool, List[bool]] = True) -> 'Table':
|
||||
def sort_by(self,
|
||||
labels: Union[str, List[str]],
|
||||
ascending: Union[bool, List[bool]] = True) -> 'Table':
|
||||
"""
|
||||
Sort table by values of given labels.
|
||||
|
||||
|
|
@ -472,8 +493,7 @@ class Table:
|
|||
"""
|
||||
labels_ = [labels] if isinstance(labels,str) else labels.copy()
|
||||
for i,l in enumerate(labels_):
|
||||
m = re.match(r'(.*)\[((\d+,)*(\d+))\]',l)
|
||||
if m:
|
||||
if m := re.match(r'(.*)\[((\d+,)*(\d+))\]',l):
|
||||
idx = np.ravel_multi_index(tuple(map(int,m.group(2).split(','))),
|
||||
self.shapes[m.group(1)])
|
||||
labels_[i] = f'{1+idx}_{m.group(1)}'
|
||||
|
|
@ -486,7 +506,8 @@ class Table:
|
|||
return dup
|
||||
|
||||
|
||||
def append(self, other: 'Table') -> 'Table':
|
||||
def append(self,
|
||||
other: 'Table') -> 'Table':
|
||||
"""
|
||||
Append other table vertically (similar to numpy.vstack).
|
||||
|
||||
|
|
@ -505,13 +526,14 @@ class Table:
|
|||
"""
|
||||
if self.shapes != other.shapes or not self.data.columns.equals(other.data.columns):
|
||||
raise KeyError('Labels or shapes or order do not match')
|
||||
else:
|
||||
dup = self.copy()
|
||||
dup.data = dup.data.append(other.data,ignore_index=True)
|
||||
return dup
|
||||
|
||||
dup = self.copy()
|
||||
dup.data = dup.data.append(other.data,ignore_index=True)
|
||||
return dup
|
||||
|
||||
|
||||
def join(self, other: 'Table') -> 'Table':
|
||||
def join(self,
|
||||
other: 'Table') -> 'Table':
|
||||
"""
|
||||
Append other table horizontally (similar to numpy.hstack).
|
||||
|
||||
|
|
@ -530,15 +552,16 @@ class Table:
|
|||
"""
|
||||
if set(self.shapes) & set(other.shapes) or self.data.shape[0] != other.data.shape[0]:
|
||||
raise KeyError('Duplicated keys or row count mismatch')
|
||||
else:
|
||||
dup = self.copy()
|
||||
dup.data = dup.data.join(other.data)
|
||||
for key in other.shapes:
|
||||
dup.shapes[key] = other.shapes[key]
|
||||
return dup
|
||||
|
||||
dup = self.copy()
|
||||
dup.data = dup.data.join(other.data)
|
||||
for key in other.shapes:
|
||||
dup.shapes[key] = other.shapes[key]
|
||||
return dup
|
||||
|
||||
|
||||
def save(self, fname: FileHandle):
|
||||
def save(self,
|
||||
fname: FileHandle):
|
||||
"""
|
||||
Save as plain text file.
|
||||
|
||||
|
|
|
|||
|
|
@ -22,7 +22,8 @@ class VTK:
|
|||
High-level interface to VTK.
|
||||
"""
|
||||
|
||||
def __init__(self, vtk_data: vtk.vtkDataSet):
|
||||
def __init__(self,
|
||||
vtk_data: vtk.vtkDataSet):
|
||||
"""
|
||||
New spatial visualization.
|
||||
|
||||
|
|
@ -38,7 +39,9 @@ class VTK:
|
|||
|
||||
|
||||
@staticmethod
|
||||
def from_image_data(cells: IntSequence, size: FloatSequence, origin: FloatSequence = np.zeros(3)) -> 'VTK':
|
||||
def from_image_data(cells: IntSequence,
|
||||
size: FloatSequence,
|
||||
origin: FloatSequence = np.zeros(3)) -> 'VTK':
|
||||
"""
|
||||
Create VTK of type vtk.vtkImageData.
|
||||
|
||||
|
|
@ -68,7 +71,9 @@ class VTK:
|
|||
|
||||
|
||||
@staticmethod
|
||||
def from_rectilinear_grid(grid: np.ndarray, size: FloatSequence, origin: FloatSequence = np.zeros(3)) -> 'VTK':
|
||||
def from_rectilinear_grid(grid: np.ndarray,
|
||||
size: FloatSequence,
|
||||
origin: FloatSequence = np.zeros(3)) -> 'VTK':
|
||||
"""
|
||||
Create VTK of type vtk.vtkRectilinearGrid.
|
||||
|
||||
|
|
@ -100,7 +105,9 @@ class VTK:
|
|||
|
||||
|
||||
@staticmethod
|
||||
def from_unstructured_grid(nodes: np.ndarray, connectivity: np.ndarray, cell_type: str) -> 'VTK':
|
||||
def from_unstructured_grid(nodes: np.ndarray,
|
||||
connectivity: np.ndarray,
|
||||
cell_type: str) -> 'VTK':
|
||||
"""
|
||||
Create VTK of type vtk.vtkUnstructuredGrid.
|
||||
|
||||
|
|
@ -195,8 +202,7 @@ class VTK:
|
|||
"""
|
||||
if not os.path.isfile(fname): # vtk has a strange error handling
|
||||
raise FileNotFoundError(f'No such file: {fname}')
|
||||
ext = Path(fname).suffix
|
||||
if ext == '.vtk' or dataset_type is not None:
|
||||
if (ext := Path(fname).suffix) == '.vtk' or dataset_type is not None:
|
||||
reader = vtk.vtkGenericDataObjectReader()
|
||||
reader.SetFileName(str(fname))
|
||||
if dataset_type is None:
|
||||
|
|
@ -238,7 +244,11 @@ class VTK:
|
|||
def _write(writer):
|
||||
"""Wrapper for parallel writing."""
|
||||
writer.Write()
|
||||
def save(self, fname: Union[str, Path], parallel: bool = True, compress: bool = True):
|
||||
|
||||
def save(self,
|
||||
fname: Union[str, Path],
|
||||
parallel: bool = True,
|
||||
compress: bool = True):
|
||||
"""
|
||||
Save as VTK file.
|
||||
|
||||
|
|
@ -284,7 +294,9 @@ class VTK:
|
|||
|
||||
# Check https://blog.kitware.com/ghost-and-blanking-visibility-changes/ for missing data
|
||||
# Needs support for damask.Table
|
||||
def add(self, data: Union[np.ndarray, np.ma.MaskedArray], label: str = None):
|
||||
def add(self,
|
||||
data: Union[np.ndarray, np.ma.MaskedArray],
|
||||
label: str = None):
|
||||
"""
|
||||
Add data to either cells or points.
|
||||
|
||||
|
|
@ -331,7 +343,8 @@ class VTK:
|
|||
raise TypeError
|
||||
|
||||
|
||||
def get(self, label: str) -> np.ndarray:
|
||||
def get(self,
|
||||
label: str) -> np.ndarray:
|
||||
"""
|
||||
Get either cell or point data.
|
||||
|
||||
|
|
@ -383,7 +396,8 @@ class VTK:
|
|||
return []
|
||||
|
||||
|
||||
def set_comments(self, comments: Union[str, List[str]]):
|
||||
def set_comments(self,
|
||||
comments: Union[str, List[str]]):
|
||||
"""
|
||||
Set comments.
|
||||
|
||||
|
|
@ -400,7 +414,8 @@ class VTK:
|
|||
self.vtk_data.GetFieldData().AddArray(s)
|
||||
|
||||
|
||||
def add_comments(self, comments: Union[str, List[str]]):
|
||||
def add_comments(self,
|
||||
comments: Union[str, List[str]]):
|
||||
"""
|
||||
Add comments.
|
||||
|
||||
|
|
@ -440,7 +455,7 @@ class VTK:
|
|||
width = tk.winfo_screenwidth()
|
||||
height = tk.winfo_screenheight()
|
||||
tk.destroy()
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
width = 1024
|
||||
height = 768
|
||||
|
||||
|
|
|
|||
|
|
@ -20,7 +20,9 @@ import numpy as _np
|
|||
from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence
|
||||
|
||||
|
||||
def _ks(size: _FloatSequence, cells: _IntSequence, first_order: bool = False) -> _np.ndarray:
|
||||
def _ks(size: _FloatSequence,
|
||||
cells: _IntSequence,
|
||||
first_order: bool = False) -> _np.ndarray:
|
||||
"""
|
||||
Get wave numbers operator.
|
||||
|
||||
|
|
@ -47,7 +49,8 @@ def _ks(size: _FloatSequence, cells: _IntSequence, first_order: bool = False) ->
|
|||
return _np.stack(_np.meshgrid(k_sk,k_sj,k_si,indexing = 'ij'), axis=-1)
|
||||
|
||||
|
||||
def curl(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||
def curl(size: _FloatSequence,
|
||||
f: _np.ndarray) -> _np.ndarray:
|
||||
u"""
|
||||
Calculate curl of a vector or tensor field in Fourier space.
|
||||
|
||||
|
|
@ -78,7 +81,8 @@ def curl(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
|||
return _np.fft.irfftn(curl_,axes=(0,1,2),s=f.shape[:3])
|
||||
|
||||
|
||||
def divergence(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||
def divergence(size: _FloatSequence,
|
||||
f: _np.ndarray) -> _np.ndarray:
|
||||
u"""
|
||||
Calculate divergence of a vector or tensor field in Fourier space.
|
||||
|
||||
|
|
@ -105,7 +109,8 @@ def divergence(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
|||
return _np.fft.irfftn(div_,axes=(0,1,2),s=f.shape[:3])
|
||||
|
||||
|
||||
def gradient(size: _FloatSequence, f: _np.ndarray) -> _np.ndarray:
|
||||
def gradient(size: _FloatSequence,
|
||||
f: _np.ndarray) -> _np.ndarray:
|
||||
u"""
|
||||
Calculate gradient of a scalar or vector field in Fourier space.
|
||||
|
||||
|
|
@ -163,7 +168,8 @@ def coordinates0_point(cells: _IntSequence,
|
|||
axis = -1)
|
||||
|
||||
|
||||
def displacement_fluct_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_fluct_point(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Cell center displacement field from fluctuation part of the deformation gradient field.
|
||||
|
||||
|
|
@ -195,7 +201,8 @@ def displacement_fluct_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarra
|
|||
return _np.fft.irfftn(displacement,axes=(0,1,2),s=F.shape[:3])
|
||||
|
||||
|
||||
def displacement_avg_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_avg_point(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Cell center displacement field from average part of the deformation gradient field.
|
||||
|
||||
|
|
@ -216,7 +223,8 @@ def displacement_avg_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
|||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_point(F.shape[:3],size))
|
||||
|
||||
|
||||
def displacement_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_point(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Cell center displacement field from deformation gradient field.
|
||||
|
||||
|
|
@ -236,7 +244,9 @@ def displacement_point(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
|||
return displacement_avg_point(size,F) + displacement_fluct_point(size,F)
|
||||
|
||||
|
||||
def coordinates_point(size: _FloatSequence, F: _np.ndarray, origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||
def coordinates_point(size: _FloatSequence,
|
||||
F: _np.ndarray,
|
||||
origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||
"""
|
||||
Cell center positions.
|
||||
|
||||
|
|
@ -335,7 +345,8 @@ def coordinates0_node(cells: _IntSequence,
|
|||
axis = -1)
|
||||
|
||||
|
||||
def displacement_fluct_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_fluct_node(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Nodal displacement field from fluctuation part of the deformation gradient field.
|
||||
|
||||
|
|
@ -355,7 +366,8 @@ def displacement_fluct_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray
|
|||
return point_to_node(displacement_fluct_point(size,F))
|
||||
|
||||
|
||||
def displacement_avg_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_avg_node(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Nodal displacement field from average part of the deformation gradient field.
|
||||
|
||||
|
|
@ -376,7 +388,8 @@ def displacement_avg_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
|||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_node(F.shape[:3],size))
|
||||
|
||||
|
||||
def displacement_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
||||
def displacement_node(size: _FloatSequence,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Nodal displacement field from deformation gradient field.
|
||||
|
||||
|
|
@ -396,7 +409,9 @@ def displacement_node(size: _FloatSequence, F: _np.ndarray) -> _np.ndarray:
|
|||
return displacement_avg_node(size,F) + displacement_fluct_node(size,F)
|
||||
|
||||
|
||||
def coordinates_node(size: _FloatSequence, F: _np.ndarray, origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||
def coordinates_node(size: _FloatSequence,
|
||||
F: _np.ndarray,
|
||||
origin: _FloatSequence = _np.zeros(3)) -> _np.ndarray:
|
||||
"""
|
||||
Nodal positions.
|
||||
|
||||
|
|
@ -526,7 +541,9 @@ def coordinates0_valid(coordinates0: _np.ndarray) -> bool:
|
|||
return False
|
||||
|
||||
|
||||
def regrid(size: _FloatSequence, F: _np.ndarray, cells: _IntSequence) -> _np.ndarray:
|
||||
def regrid(size: _FloatSequence,
|
||||
F: _np.ndarray,
|
||||
cells: _IntSequence) -> _np.ndarray:
|
||||
"""
|
||||
Return mapping from coordinates in deformed configuration to a regular grid.
|
||||
|
||||
|
|
|
|||
|
|
@ -122,7 +122,9 @@ def rotation(T: _np.ndarray) -> _rotation.Rotation:
|
|||
return _rotation.Rotation.from_matrix(_polar_decomposition(T,'R')[0])
|
||||
|
||||
|
||||
def strain(F: _np.ndarray, t: str, m: float) -> _np.ndarray:
|
||||
def strain(F: _np.ndarray,
|
||||
t: str,
|
||||
m: float) -> _np.ndarray:
|
||||
"""
|
||||
Calculate strain tensor (Seth–Hill family).
|
||||
|
||||
|
|
@ -162,7 +164,8 @@ def strain(F: _np.ndarray, t: str, m: float) -> _np.ndarray:
|
|||
return eps
|
||||
|
||||
|
||||
def stress_Cauchy(P: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
||||
def stress_Cauchy(P: _np.ndarray,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Calculate the Cauchy stress (true stress).
|
||||
|
||||
|
|
@ -184,7 +187,8 @@ def stress_Cauchy(P: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
|||
return _tensor.symmetric(_np.einsum('...,...ij,...kj',1.0/_np.linalg.det(F),P,F))
|
||||
|
||||
|
||||
def stress_second_Piola_Kirchhoff(P: _np.ndarray, F: _np.ndarray) -> _np.ndarray:
|
||||
def stress_second_Piola_Kirchhoff(P: _np.ndarray,
|
||||
F: _np.ndarray) -> _np.ndarray:
|
||||
"""
|
||||
Calculate the second Piola-Kirchhoff stress.
|
||||
|
||||
|
|
@ -243,7 +247,8 @@ def stretch_right(T: _np.ndarray) -> _np.ndarray:
|
|||
return _polar_decomposition(T,'U')[0]
|
||||
|
||||
|
||||
def _polar_decomposition(T: _np.ndarray, requested: _Sequence[str]) -> tuple:
|
||||
def _polar_decomposition(T: _np.ndarray,
|
||||
requested: _Sequence[str]) -> tuple:
|
||||
"""
|
||||
Perform singular value decomposition.
|
||||
|
||||
|
|
@ -251,7 +256,7 @@ def _polar_decomposition(T: _np.ndarray, requested: _Sequence[str]) -> tuple:
|
|||
----------
|
||||
T : numpy.ndarray, shape (...,3,3)
|
||||
Tensor of which the singular values are computed.
|
||||
requested : iterable of str
|
||||
requested : sequence of {'R', 'U', 'V'}
|
||||
Requested outputs: ‘R’ for the rotation tensor,
|
||||
‘V’ for left stretch tensor and ‘U’ for right stretch tensor.
|
||||
|
||||
|
|
@ -273,7 +278,8 @@ def _polar_decomposition(T: _np.ndarray, requested: _Sequence[str]) -> tuple:
|
|||
return tuple(output)
|
||||
|
||||
|
||||
def _equivalent_Mises(T_sym: _np.ndarray, s: float) -> _np.ndarray:
|
||||
def _equivalent_Mises(T_sym: _np.ndarray,
|
||||
s: float) -> _np.ndarray:
|
||||
"""
|
||||
Base equation for Mises equivalent of a stress or strain tensor.
|
||||
|
||||
|
|
|
|||
|
|
@ -10,7 +10,9 @@ from . import util as _util
|
|||
from . import grid_filters as _grid_filters
|
||||
|
||||
|
||||
def from_random(size: _FloatSequence, N_seeds: int, cells: _IntSequence = None,
|
||||
def from_random(size: _FloatSequence,
|
||||
N_seeds: int,
|
||||
cells: _IntSequence = None,
|
||||
rng_seed=None) -> _np.ndarray:
|
||||
"""
|
||||
Place seeds randomly in space.
|
||||
|
|
@ -46,8 +48,12 @@ def from_random(size: _FloatSequence, N_seeds: int, cells: _IntSequence = None,
|
|||
return coords
|
||||
|
||||
|
||||
def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, distance: float,
|
||||
periodic: bool = True, rng_seed=None) -> _np.ndarray:
|
||||
def from_Poisson_disc(size: _FloatSequence,
|
||||
N_seeds: int,
|
||||
N_candidates: int,
|
||||
distance: float,
|
||||
periodic: bool = True,
|
||||
rng_seed=None) -> _np.ndarray:
|
||||
"""
|
||||
Place seeds according to a Poisson disc distribution.
|
||||
|
||||
|
|
@ -86,10 +92,9 @@ def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, dis
|
|||
tree = _spatial.cKDTree(coords[:s],boxsize=size) if periodic else \
|
||||
_spatial.cKDTree(coords[:s])
|
||||
distances = tree.query(candidates)[0]
|
||||
best = distances.argmax()
|
||||
if distances[best] > distance: # require minimum separation
|
||||
if distances.max() > distance: # require minimum separation
|
||||
i = 0
|
||||
coords[s] = candidates[best] # maximum separation to existing point cloud
|
||||
coords[s] = candidates[distances.argmax()] # maximum separation to existing point cloud
|
||||
s += 1
|
||||
progress.update(s)
|
||||
|
||||
|
|
@ -99,8 +104,11 @@ def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, dis
|
|||
return coords
|
||||
|
||||
|
||||
def from_grid(grid, selection: _IntSequence = None, invert_selection: bool = False,
|
||||
average: bool = False, periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
|
||||
def from_grid(grid,
|
||||
selection: _IntSequence = None,
|
||||
invert_selection: bool = False,
|
||||
average: bool = False,
|
||||
periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
|
||||
"""
|
||||
Create seeds from grid description.
|
||||
|
||||
|
|
|
|||
|
|
@ -45,7 +45,8 @@ def eigenvalues(T_sym: _np.ndarray) -> _np.ndarray:
|
|||
return _np.linalg.eigvalsh(symmetric(T_sym))
|
||||
|
||||
|
||||
def eigenvectors(T_sym: _np.ndarray, RHS: bool = False) -> _np.ndarray:
|
||||
def eigenvectors(T_sym: _np.ndarray,
|
||||
RHS: bool = False) -> _np.ndarray:
|
||||
"""
|
||||
Eigenvectors of a symmetric tensor.
|
||||
|
||||
|
|
@ -63,14 +64,14 @@ def eigenvectors(T_sym: _np.ndarray, RHS: bool = False) -> _np.ndarray:
|
|||
associated eigenvalues.
|
||||
|
||||
"""
|
||||
(u,v) = _np.linalg.eigh(symmetric(T_sym))
|
||||
_,v = _np.linalg.eigh(symmetric(T_sym))
|
||||
|
||||
if RHS:
|
||||
v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
|
||||
if RHS: v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
|
||||
return v
|
||||
|
||||
|
||||
def spherical(T: _np.ndarray, tensor: bool = True) -> _np.ndarray:
|
||||
def spherical(T: _np.ndarray,
|
||||
tensor: bool = True) -> _np.ndarray:
|
||||
"""
|
||||
Calculate spherical part of a tensor.
|
||||
|
||||
|
|
|
|||
|
|
@ -7,7 +7,7 @@ import subprocess
|
|||
import shlex
|
||||
import re
|
||||
import fractions
|
||||
import collections.abc as abc
|
||||
from collections import abc
|
||||
from functools import reduce
|
||||
from typing import Union, Tuple, Iterable, Callable, Dict, List, Any, Literal, Optional
|
||||
from pathlib import Path
|
||||
|
|
@ -16,7 +16,7 @@ import numpy as np
|
|||
import h5py
|
||||
|
||||
from . import version
|
||||
from ._typehints import FloatSequence
|
||||
from ._typehints import IntSequence, FloatSequence
|
||||
|
||||
# limit visibility
|
||||
__all__=[
|
||||
|
|
@ -54,7 +54,8 @@ _colors = {
|
|||
####################################################################################################
|
||||
# Functions
|
||||
####################################################################################################
|
||||
def srepr(msg, glue: str = '\n') -> str:
|
||||
def srepr(msg,
|
||||
glue: str = '\n') -> str:
|
||||
r"""
|
||||
Join items with glue string.
|
||||
|
||||
|
|
@ -76,7 +77,7 @@ def srepr(msg, glue: str = '\n') -> str:
|
|||
hasattr(msg, '__iter__'))):
|
||||
return glue.join(str(x) for x in msg)
|
||||
else:
|
||||
return msg if isinstance(msg,str) else repr(msg)
|
||||
return msg if isinstance(msg,str) else repr(msg)
|
||||
|
||||
|
||||
def emph(msg) -> str:
|
||||
|
|
@ -148,7 +149,10 @@ def strikeout(msg) -> str:
|
|||
return _colors['crossout']+srepr(msg)+_colors['end_color']
|
||||
|
||||
|
||||
def run(cmd: str, wd: str = './', env: Dict[str, str] = None, timeout: int = None) -> Tuple[str, str]:
|
||||
def run(cmd: str,
|
||||
wd: str = './',
|
||||
env: Dict[str, str] = None,
|
||||
timeout: int = None) -> Tuple[str, str]:
|
||||
"""
|
||||
Run a command.
|
||||
|
||||
|
|
@ -226,15 +230,15 @@ def show_progress(iterable: Iterable,
|
|||
|
||||
"""
|
||||
if isinstance(iterable,abc.Sequence):
|
||||
if N_iter is None:
|
||||
N = len(iterable)
|
||||
else:
|
||||
raise ValueError('N_iter given for sequence')
|
||||
if N_iter is None:
|
||||
N = len(iterable)
|
||||
else:
|
||||
raise ValueError('N_iter given for sequence')
|
||||
else:
|
||||
if N_iter is None:
|
||||
raise ValueError('N_iter not given')
|
||||
else:
|
||||
N = N_iter
|
||||
if N_iter is None:
|
||||
raise ValueError('N_iter not given')
|
||||
|
||||
N = N_iter
|
||||
|
||||
if N <= 1:
|
||||
for item in iterable:
|
||||
|
|
@ -301,16 +305,20 @@ def project_equal_angle(vector: np.ndarray,
|
|||
normalize : bool
|
||||
Ensure unit length of input vector. Defaults to True.
|
||||
keepdims : bool
|
||||
Maintain three-dimensional output coordinates. Defaults to False.
|
||||
Two-dimensional output uses right-handed frame spanned by
|
||||
the next and next-next axis relative to the projection direction,
|
||||
e.g. x-y when projecting along z and z-x when projecting along y.
|
||||
Maintain three-dimensional output coordinates.
|
||||
Defaults to False.
|
||||
|
||||
Returns
|
||||
-------
|
||||
coordinates : numpy.ndarray, shape (...,2 | 3)
|
||||
Projected coordinates.
|
||||
|
||||
Notes
|
||||
-----
|
||||
Two-dimensional output uses right-handed frame spanned by
|
||||
the next and next-next axis relative to the projection direction,
|
||||
e.g. x-y when projecting along z and z-x when projecting along y.
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> import damask
|
||||
|
|
@ -345,16 +353,21 @@ def project_equal_area(vector: np.ndarray,
|
|||
normalize : bool
|
||||
Ensure unit length of input vector. Defaults to True.
|
||||
keepdims : bool
|
||||
Maintain three-dimensional output coordinates. Defaults to False.
|
||||
Two-dimensional output uses right-handed frame spanned by
|
||||
the next and next-next axis relative to the projection direction,
|
||||
e.g. x-y when projecting along z and z-x when projecting along y.
|
||||
Maintain three-dimensional output coordinates.
|
||||
Defaults to False.
|
||||
|
||||
Returns
|
||||
-------
|
||||
coordinates : numpy.ndarray, shape (...,2 | 3)
|
||||
Projected coordinates.
|
||||
|
||||
Notes
|
||||
-----
|
||||
Two-dimensional output uses right-handed frame spanned by
|
||||
the next and next-next axis relative to the projection direction,
|
||||
e.g. x-y when projecting along z and z-x when projecting along y.
|
||||
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> import damask
|
||||
|
|
@ -373,14 +386,17 @@ def project_equal_area(vector: np.ndarray,
|
|||
return np.roll(np.block([v[...,:2]/np.sqrt(1.0+np.abs(v[...,2:3])),np.zeros_like(v[...,2:3])]),
|
||||
-shift if keepdims else 0,axis=-1)[...,:3 if keepdims else 2]
|
||||
|
||||
def execution_stamp(class_name: str, function_name: str = None) -> str:
|
||||
def execution_stamp(class_name: str,
|
||||
function_name: str = None) -> str:
|
||||
"""Timestamp the execution of a (function within a) class."""
|
||||
now = datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S%z')
|
||||
_function_name = '' if function_name is None else f'.{function_name}'
|
||||
return f'damask.{class_name}{_function_name} v{version} ({now})'
|
||||
|
||||
|
||||
def hybrid_IA(dist: np.ndarray, N: int, rng_seed = None) -> np.ndarray:
|
||||
def hybrid_IA(dist: np.ndarray,
|
||||
N: int,
|
||||
rng_seed: Union[int, IntSequence] = None) -> np.ndarray:
|
||||
"""
|
||||
Hybrid integer approximation.
|
||||
|
||||
|
|
@ -447,7 +463,7 @@ def shapeshifter(fro: Tuple[int, ...],
|
|||
|
||||
|
||||
"""
|
||||
if not len(fro) and not len(to): return ()
|
||||
if len(fro) == 0 and len(to) == 0: return ()
|
||||
|
||||
beg = dict(left ='(^.*\\b)',
|
||||
right='(^.*?\\b)')
|
||||
|
|
@ -455,8 +471,8 @@ def shapeshifter(fro: Tuple[int, ...],
|
|||
right='(.*?\\b)')
|
||||
end = dict(left ='(.*?$)',
|
||||
right='(.*$)')
|
||||
fro = (1,) if not len(fro) else fro
|
||||
to = (1,) if not len(to) else to
|
||||
fro = (1,) if len(fro) == 0 else fro
|
||||
to = (1,) if len(to) == 0 else to
|
||||
try:
|
||||
match = re.match(beg[mode]
|
||||
+f',{sep[mode]}'.join(map(lambda x: f'{x}'
|
||||
|
|
@ -473,7 +489,8 @@ def shapeshifter(fro: Tuple[int, ...],
|
|||
return fill[:-1]
|
||||
|
||||
|
||||
def shapeblender(a: Tuple[int, ...], b: Tuple[int, ...]) -> Tuple[int, ...]:
|
||||
def shapeblender(a: Tuple[int, ...],
|
||||
b: Tuple[int, ...]) -> Tuple[int, ...]:
|
||||
"""
|
||||
Return a shape that overlaps the rightmost entries of 'a' with the leftmost of 'b'.
|
||||
|
||||
|
|
@ -517,7 +534,8 @@ def extend_docstring(extra_docstring: str) -> Callable:
|
|||
return _decorator
|
||||
|
||||
|
||||
def extended_docstring(f: Callable, extra_docstring: str) -> Callable:
|
||||
def extended_docstring(f: Callable,
|
||||
extra_docstring: str) -> Callable:
|
||||
"""
|
||||
Decorator: Combine another function's docstring with a given docstring.
|
||||
|
||||
|
|
@ -593,7 +611,9 @@ def DREAM3D_cell_data_group(fname: Union[str, Path]) -> str:
|
|||
return cell_data_group
|
||||
|
||||
|
||||
def Bravais_to_Miller(*, uvtw: np.ndarray = None, hkil: np.ndarray = None) -> np.ndarray:
|
||||
def Bravais_to_Miller(*,
|
||||
uvtw: np.ndarray = None,
|
||||
hkil: np.ndarray = None) -> np.ndarray:
|
||||
"""
|
||||
Transform 4 Miller–Bravais indices to 3 Miller indices of crystal direction [uvw] or plane normal (hkl).
|
||||
|
||||
|
|
@ -620,7 +640,9 @@ def Bravais_to_Miller(*, uvtw: np.ndarray = None, hkil: np.ndarray = None) -> np
|
|||
return np.einsum('il,...l',basis,axis)
|
||||
|
||||
|
||||
def Miller_to_Bravais(*, uvw: np.ndarray = None, hkl: np.ndarray = None) -> np.ndarray:
|
||||
def Miller_to_Bravais(*,
|
||||
uvw: np.ndarray = None,
|
||||
hkl: np.ndarray = None) -> np.ndarray:
|
||||
"""
|
||||
Transform 3 Miller indices to 4 Miller–Bravais indices of crystal direction [uvtw] or plane normal (hkil).
|
||||
|
||||
|
|
@ -710,7 +732,10 @@ class ProgressBar:
|
|||
Works for 0-based loops, ETA is estimated by linear extrapolation.
|
||||
"""
|
||||
|
||||
def __init__(self, total: int, prefix: str, bar_length: int):
|
||||
def __init__(self,
|
||||
total: int,
|
||||
prefix: str,
|
||||
bar_length: int):
|
||||
"""
|
||||
Set current time as basis for ETA estimation.
|
||||
|
||||
|
|
@ -733,12 +758,12 @@ class ProgressBar:
|
|||
sys.stderr.write(f"{self.prefix} {'░'*self.bar_length} 0% ETA n/a")
|
||||
sys.stderr.flush()
|
||||
|
||||
def update(self, iteration: int) -> None:
|
||||
def update(self,
|
||||
iteration: int) -> None:
|
||||
|
||||
fraction = (iteration+1) / self.total
|
||||
filled_length = int(self.bar_length * fraction)
|
||||
|
||||
if filled_length > int(self.bar_length * self.fraction_last) or \
|
||||
if filled_length := int(self.bar_length * fraction) > int(self.bar_length * self.fraction_last) or \
|
||||
datetime.datetime.now() - self.time_last_update > datetime.timedelta(seconds=10):
|
||||
self.time_last_update = datetime.datetime.now()
|
||||
bar = '█' * filled_length + '░' * (self.bar_length - filled_length)
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
[mypy]
|
||||
warn_redundant_casts = True
|
||||
[mypy-scipy.*]
|
||||
ignore_missing_imports = True
|
||||
[mypy-h5py.*]
|
||||
|
|
|
|||
Loading…
Reference in New Issue