fixed sort_by to respect updated index (upon subsequent adding of new data)
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3caf2c1296
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2648a67dcd
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@ -1,4 +1,3 @@
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import random
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import re
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import re
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import pandas as pd
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import pandas as pd
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@ -24,15 +23,24 @@ class Table():
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self.comments = [] if comments is None else [c for c in comments]
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self.comments = [] if comments is None else [c for c in comments]
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self.data = pd.DataFrame(data=data)
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self.data = pd.DataFrame(data=data)
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self.shapes = shapes
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self.shapes = shapes
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self.__label_condensed()
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def __label_flat(self):
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"""Label data individually, e.g. v v v ==> 1_v 2_v 3_v."""
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labels = []
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for label,shape in self.shapes.items():
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size = np.prod(shape)
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labels += ['{}{}'.format('' if size == 1 else '{}_'.format(i+1),label) for i in range(size)]
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self.data.columns = labels
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def __label_condensed(self):
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"""Label data condensed, e.g. 1_v 2_v 3_v ==> v v v."""
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labels = []
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labels = []
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for label,shape in self.shapes.items():
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for label,shape in self.shapes.items():
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labels += [label] * np.prod(shape)
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labels += [label] * np.prod(shape)
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self.data.columns = labels
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if len(labels) != self.data.shape[1]:
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raise IndexError('Mismatch between shapes and data')
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self.data.rename(columns=dict(zip(range(len(labels)),labels)),inplace=True)
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def __add_comment(self,label,shape,info):
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def __add_comment(self,label,shape,info):
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@ -87,7 +95,7 @@ class Table():
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return Table(data,shapes,comments)
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return Table(data,shapes,comments)
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@property
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def labels(self):
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def labels(self):
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"""Return the labels of all columns."""
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"""Return the labels of all columns."""
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return list(self.shapes.keys())
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return list(self.shapes.keys())
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@ -105,9 +113,11 @@ class Table():
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"""
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"""
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if re.match(r'[0-9]*?_',label):
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if re.match(r'[0-9]*?_',label):
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idx,key = label.split('_',1)
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idx,key = label.split('_',1)
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return self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
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data = self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
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else:
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else:
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return self.data[label].to_numpy().reshape((-1,)+self.shapes[label]) # better return shape (N) instead of (N,1), i.e. no reshaping?
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data = self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
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return data.astype(type(data.flatten()[0]))
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def set(self,label,data,info=None):
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def set(self,label,data,info=None):
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@ -152,10 +162,11 @@ class Table():
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self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
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self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
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size = np.prod(data.shape[1:],dtype=int)
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size = np.prod(data.shape[1:],dtype=int)
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self.data = pd.concat([self.data,
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new = pd.DataFrame(data=data.reshape(-1,size),
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pd.DataFrame(data=data.reshape(-1,size),
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columns=[label]*size,
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columns=[label]*size)],
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)
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axis=1)
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new.index = self.data.index
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self.data = pd.concat([self.data,new],axis=1)
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def delete(self,label):
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def delete(self,label):
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@ -201,24 +212,15 @@ class Table():
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Parameters
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Parameters
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----------
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----------
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label : list of str or str
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label : str or list
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Column labels.
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Column labels.
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ascending : bool, optional
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ascending : bool or list, optional
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Set sort order.
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Set sort order.
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"""
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"""
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_temp = []
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self.__label_flat()
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_labels = []
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self.data.sort_values(labels,axis=0,inplace=True,ascending=ascending)
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for label in labels if isinstance(labels,list) else [labels]:
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self.__label_condensed()
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if re.match(r'[0-9]*?_',label):
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_temp.append(str(random.getrandbits(128)))
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self.add(_temp[-1],self.get(label))
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_labels.append(_temp[-1])
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else:
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_labels.append(label)
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self.data.sort_values(_labels,axis=0,inplace=True,ascending=ascending)
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for t in _temp: self.delete(t)
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self.comments.append('sorted by [{}]'.format(', '.join(labels)))
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self.comments.append('sorted by [{}]'.format(', '.join(labels)))
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@ -9,7 +9,7 @@ from damask import Table
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@pytest.fixture
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@pytest.fixture
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def default():
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def default():
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"""Simple Table."""
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"""Simple Table."""
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x = np.ones((5,13))
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x = np.ones((5,13),dtype=float)
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return Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['test data','contains only ones'])
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return Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['test data','contains only ones'])
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@pytest.fixture
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@pytest.fixture
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@ -58,7 +58,7 @@ class TestTable:
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assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
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assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
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def test_labels(self,default):
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def test_labels(self,default):
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assert default.labels() == ['F','v','s']
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assert default.labels == ['F','v','s']
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def test_add(self,default):
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def test_add(self,default):
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d = np.random.random((5,9))
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d = np.random.random((5,9))
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@ -82,9 +82,9 @@ class TestTable:
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default.get('v')
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default.get('v')
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def test_invalid_initialization(self,default):
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def test_invalid_initialization(self):
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x = default.get('v')
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x = np.random.random((5,10))
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with pytest.raises(IndexError):
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with pytest.raises(ValueError):
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Table(x,{'F':(3,3)})
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Table(x,{'F':(3,3)})
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def test_invalid_set(self,default):
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def test_invalid_set(self,default):
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@ -115,7 +115,14 @@ class TestTable:
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def test_sort_revert(self):
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def test_sort_revert(self):
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x = np.random.random((5,12))
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x = np.random.random((5,12))
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t = Table(x,{'F':(3,3),'v':(3,)},['random test data'])
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t = Table(x,{'F':(3,3),'v':(3,)},['random test data'])
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t.sort_by('4_F',False)
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t.sort_by('4_F',ascending=False)
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sort = t.get('4_F')
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sort = t.get('4_F')
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assert np.all(np.sort(sort,0)==sort[::-1,:])
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assert np.all(np.sort(sort,0)==sort[::-1,:])
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def test_sort(self):
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t = Table(np.array([[0,1,],[2,1,]]),
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{'v':(2,)},
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['test data'])
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t.add('s',np.array(['b','a']))
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t.sort_by('s')
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assert np.all(t.get('1_v') == np.array([2,0]).reshape((2,1)))
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