Merge branch 'improved-table-slicing' into 'development'
Extended slicing functionality of Table See merge request damask/DAMASK!522
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commit
d4f7114164
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@ -44,6 +44,13 @@ class Table:
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return '\n'.join(['# '+c for c in self.comments])+'\n'+data_repr
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return '\n'.join(['# '+c for c in self.comments])+'\n'+data_repr
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def __eq__(self,
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other: object) -> bool:
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"""Compare to other Table."""
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return NotImplemented if not isinstance(other,Table) else \
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self.shapes == other.shapes and self.data.equals(other.data)
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def __getitem__(self,
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def __getitem__(self,
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item: Union[slice, Tuple[slice, ...]]) -> 'Table':
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item: Union[slice, Tuple[slice, ...]]) -> 'Table':
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"""
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"""
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@ -75,17 +82,19 @@ class Table:
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colB colA
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colB colA
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0 1 0
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0 1 0
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2 7 6
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2 7 6
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>>> tbl[1:2,'colB']
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>>> tbl[[True,False,False,True],'colB']
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colB
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colB
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1 4
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0 1
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2 7
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3 10
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"""
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"""
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item = (item,slice(None,None,None)) if isinstance(item,slice) else \
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item_ = (item,slice(None,None,None)) if isinstance(item,(slice,np.ndarray)) else \
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item if isinstance(item[0],slice) else \
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(np.array(item),slice(None,None,None)) if isinstance(item,list) and np.array(item).dtype == np.bool_ else \
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(np.array(item[0]),item[1]) if isinstance(item[0],list) else \
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item if isinstance(item[0],(slice,np.ndarray)) else \
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(slice(None,None,None),item)
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(slice(None,None,None),item)
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sliced = self.data.loc[item]
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sliced = self.data.loc[item_]
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cols = np.array(sliced.columns if isinstance(sliced,pd.core.frame.DataFrame) else [item[1]])
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cols = np.array(sliced.columns if isinstance(sliced,pd.core.frame.DataFrame) else [item_[1]])
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_,idx = np.unique(cols,return_index=True)
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_,idx = np.unique(cols,return_index=True)
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return self.__class__(data=sliced,
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return self.__class__(data=sliced,
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shapes={k:self.shapes[k] for k in cols[np.sort(idx)]},
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shapes={k:self.shapes[k] for k in cols[np.sort(idx)]},
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@ -59,10 +59,14 @@ class TestTable:
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@pytest.mark.parametrize('N',[1,3,4])
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@pytest.mark.parametrize('N',[1,3,4])
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def test_slice(self,default,N):
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def test_slice(self,default,N):
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mask = np.random.choice([True,False],len(default))
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assert len(default[:N]) == 1+N
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assert len(default[:N]) == 1+N
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assert len(default[:N,['F','s']]) == 1+N
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assert len(default[:N,['F','s']]) == 1+N
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assert len(default[mask,['F','s']]) == np.count_nonzero(mask)
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assert default[mask,['F','s']] == default[mask][['F','s']] == default[['F','s']][mask]
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assert default[np.logical_not(mask),['F','s']] != default[mask][['F','s']]
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assert default[N:].get('F').shape == (len(default)-N,3,3)
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assert default[N:].get('F').shape == (len(default)-N,3,3)
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assert (default[:N,['v','s']].data == default['v','s'][:N].data).all().all()
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assert default[:N,['v','s']].data.equals(default['v','s'][:N].data)
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@pytest.mark.parametrize('mode',['str','path'])
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@pytest.mark.parametrize('mode',['str','path'])
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def test_write_read(self,default,tmp_path,mode):
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def test_write_read(self,default,tmp_path,mode):
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