fixed sort_by to respect updated index (upon subsequent adding of new data)

This commit is contained in:
Philip Eisenlohr 2019-12-05 12:00:59 -05:00
parent 3caf2c1296
commit 2648a67dcd
2 changed files with 44 additions and 35 deletions

View File

@ -1,4 +1,3 @@
import random
import re
import pandas as pd
@ -24,15 +23,24 @@ class Table():
self.comments = [] if comments is None else [c for c in comments]
self.data = pd.DataFrame(data=data)
self.shapes = shapes
self.__label_condensed()
def __label_flat(self):
"""Label data individually, e.g. v v v ==> 1_v 2_v 3_v."""
labels = []
for label,shape in self.shapes.items():
size = np.prod(shape)
labels += ['{}{}'.format('' if size == 1 else '{}_'.format(i+1),label) for i in range(size)]
self.data.columns = labels
def __label_condensed(self):
"""Label data condensed, e.g. 1_v 2_v 3_v ==> v v v."""
labels = []
for label,shape in self.shapes.items():
labels += [label] * np.prod(shape)
if len(labels) != self.data.shape[1]:
raise IndexError('Mismatch between shapes and data')
self.data.rename(columns=dict(zip(range(len(labels)),labels)),inplace=True)
self.data.columns = labels
def __add_comment(self,label,shape,info):
@ -87,7 +95,7 @@ class Table():
return Table(data,shapes,comments)
@property
def labels(self):
"""Return the labels of all columns."""
return list(self.shapes.keys())
@ -105,9 +113,11 @@ class Table():
"""
if re.match(r'[0-9]*?_',label):
idx,key = label.split('_',1)
return self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
data = self.data[key].to_numpy()[:,int(idx)-1].reshape((-1,1))
else:
return self.data[label].to_numpy().reshape((-1,)+self.shapes[label]) # better return shape (N) instead of (N,1), i.e. no reshaping?
data = self.data[label].to_numpy().reshape((-1,)+self.shapes[label])
return data.astype(type(data.flatten()[0]))
def set(self,label,data,info=None):
@ -149,13 +159,14 @@ class Table():
"""
self.__add_comment(label,data.shape[1:],info)
self.shapes[label] = data.shape[1:] if len(data.shape) > 1 else (1,)
size = np.prod(data.shape[1:],dtype=int)
self.data = pd.concat([self.data,
pd.DataFrame(data=data.reshape(-1,size),
columns=[label]*size)],
axis=1)
size = np.prod(data.shape[1:],dtype=int)
new = pd.DataFrame(data=data.reshape(-1,size),
columns=[label]*size,
)
new.index = self.data.index
self.data = pd.concat([self.data,new],axis=1)
def delete(self,label):
@ -201,24 +212,15 @@ class Table():
Parameters
----------
label : list of str or str
label : str or list
Column labels.
ascending : bool, optional
ascending : bool or list, optional
Set sort order.
"""
_temp = []
_labels = []
for label in labels if isinstance(labels,list) else [labels]:
if re.match(r'[0-9]*?_',label):
_temp.append(str(random.getrandbits(128)))
self.add(_temp[-1],self.get(label))
_labels.append(_temp[-1])
else:
_labels.append(label)
self.data.sort_values(_labels,axis=0,inplace=True,ascending=ascending)
for t in _temp: self.delete(t)
self.__label_flat()
self.data.sort_values(labels,axis=0,inplace=True,ascending=ascending)
self.__label_condensed()
self.comments.append('sorted by [{}]'.format(', '.join(labels)))

View File

@ -9,7 +9,7 @@ from damask import Table
@pytest.fixture
def default():
"""Simple Table."""
x = np.ones((5,13))
x = np.ones((5,13),dtype=float)
return Table(x,{'F':(3,3),'v':(3,),'s':(1,)},['test data','contains only ones'])
@pytest.fixture
@ -58,7 +58,7 @@ class TestTable:
assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
def test_labels(self,default):
assert default.labels() == ['F','v','s']
assert default.labels == ['F','v','s']
def test_add(self,default):
d = np.random.random((5,9))
@ -82,9 +82,9 @@ class TestTable:
default.get('v')
def test_invalid_initialization(self,default):
x = default.get('v')
with pytest.raises(IndexError):
def test_invalid_initialization(self):
x = np.random.random((5,10))
with pytest.raises(ValueError):
Table(x,{'F':(3,3)})
def test_invalid_set(self,default):
@ -115,7 +115,14 @@ class TestTable:
def test_sort_revert(self):
x = np.random.random((5,12))
t = Table(x,{'F':(3,3),'v':(3,)},['random test data'])
t.sort_by('4_F',False)
t.sort_by('4_F',ascending=False)
sort = t.get('4_F')
assert np.all(np.sort(sort,0)==sort[::-1,:])
def test_sort(self):
t = Table(np.array([[0,1,],[2,1,]]),
{'v':(2,)},
['test data'])
t.add('s',np.array(['b','a']))
t.sort_by('s')
assert np.all(t.get('1_v') == np.array([2,0]).reshape((2,1)))