Python 3.8 magic: The walrus operator ":="
This commit is contained in:
Martin Diehl
parent
6fe6be7a34
commit
609f13c590
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@ -266,9 +266,7 @@ 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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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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@ -234,8 +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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@ -247,8 +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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@ -813,8 +811,7 @@ class Grid:
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# materials: 1
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"""
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valid = ['x','y','z']
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if not set(directions).issubset(valid):
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if not set(directions).issubset(valid := ['x', 'y', 'z']):
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raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
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limits: Sequence[Optional[int]] = [None,None] if reflect else [-2,0]
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@ -852,8 +849,7 @@ class Grid:
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Updated grid-based geometry.
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"""
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valid = ['x','y','z']
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if not set(directions).issubset(valid):
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if not set(directions).issubset(valid := ['x', 'y', 'z']):
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raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
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@ -1190,8 +1186,7 @@ class Grid:
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VTK-based geometry of grain boundary network.
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"""
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valid = ['x','y','z']
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if not set(directions).issubset(valid):
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if not set(directions).issubset(valid := ['x', 'y', 'z']):
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raise ValueError(f'invalid direction {set(directions).difference(valid)} specified')
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o = [[0, self.cells[0]+1, np.prod(self.cells[:2]+1)+self.cells[0]+1, np.prod(self.cells[:2]+1)],
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@ -319,8 +319,7 @@ class Table:
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data = np.loadtxt(content)
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shapes = {'eu':3, 'pos':2, 'IQ':1, 'CI':1, 'ID':1, 'intensity':1, 'fit':1}
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remainder = data.shape[1]-sum(shapes.values())
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if remainder > 0: # 3.8 can do: if (remainder := data.shape[1]-sum(shapes.values())) > 0
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if (remainder := data.shape[1]-sum(shapes.values())) > 0:
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shapes['unknown'] = remainder
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return Table(data,shapes,comments)
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@ -376,8 +375,7 @@ class Table:
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"""
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dup = self.copy()
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dup._add_comment(label, data.shape[1:], info)
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m = re.match(r'(.*)\[((\d+,)*(\d+))\]',label)
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if m:
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if m := re.match(r'(.*)\[((\d+,)*(\d+))\]',label):
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key = m.group(1)
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idx = np.ravel_multi_index(tuple(map(int,m.group(2).split(","))),
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self.shapes[key])
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@ -495,8 +493,7 @@ class Table:
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"""
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labels_ = [labels] if isinstance(labels,str) else labels.copy()
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for i,l in enumerate(labels_):
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m = re.match(r'(.*)\[((\d+,)*(\d+))\]',l)
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if m:
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if m := re.match(r'(.*)\[((\d+,)*(\d+))\]',l):
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idx = np.ravel_multi_index(tuple(map(int,m.group(2).split(','))),
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self.shapes[m.group(1)])
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labels_[i] = f'{1+idx}_{m.group(1)}'
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@ -22,7 +22,7 @@ class VTK:
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High-level interface to VTK.
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"""
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def __init__(self,
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def __init__(self,
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vtk_data: vtk.vtkDataSet):
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"""
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New spatial visualization.
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@ -202,8 +202,7 @@ class VTK:
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"""
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if not os.path.isfile(fname): # vtk has a strange error handling
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raise FileNotFoundError(f'No such file: {fname}')
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ext = Path(fname).suffix
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if ext == '.vtk' or dataset_type is not None:
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if (ext := Path(fname).suffix) == '.vtk' or dataset_type is not None:
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reader = vtk.vtkGenericDataObjectReader()
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reader.SetFileName(str(fname))
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if dataset_type is None:
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@ -92,10 +92,9 @@ def from_Poisson_disc(size: _FloatSequence,
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tree = _spatial.cKDTree(coords[:s],boxsize=size) if periodic else \
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_spatial.cKDTree(coords[:s])
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distances = tree.query(candidates)[0]
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best = distances.argmax()
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if distances[best] > distance: # require minimum separation
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if distances.max() > distance: # require minimum separation
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i = 0
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coords[s] = candidates[best] # maximum separation to existing point cloud
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coords[s] = candidates[distances.argmax()] # maximum separation to existing point cloud
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s += 1
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progress.update(s)
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@ -66,8 +66,7 @@ def eigenvectors(T_sym: _np.ndarray,
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"""
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(u,v) = _np.linalg.eigh(symmetric(T_sym))
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if RHS:
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v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
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if RHS: v[_np.linalg.det(v) < 0.0,:,2] *= -1.0
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return v
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@ -753,9 +753,8 @@ class ProgressBar:
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iteration: int) -> None:
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fraction = (iteration+1) / self.total
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filled_length = int(self.bar_length * fraction)
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if filled_length > int(self.bar_length * self.fraction_last) or \
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if filled_length := int(self.bar_length * fraction) > int(self.bar_length * self.fraction_last) or \
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datetime.datetime.now() - self.time_last_update > datetime.timedelta(seconds=10):
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self.time_last_update = datetime.datetime.now()
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bar = '█' * filled_length + '░' * (self.bar_length - filled_length)
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