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src/s/c/scipy-0.13.3/scipy/sparse/compressed.py   scipy(Download)
from .base import spmatrix, isspmatrix, SparseEfficiencyWarning
from .data import _data_matrix, _minmax_mixin
from .dia import dia_matrix
from . import sparsetools
from .sputils import upcast, upcast_char, to_native, isdense, isshape, \
            # Row vector times matrix. other is a row.
            elif other.shape[0] == 1 and self.shape[1] == other.shape[1]:
                other = dia_matrix((other.toarray().ravel(), [0]),
                                    shape=(other.shape[1], other.shape[1]))
                return self._mul_sparse_matrix(other)
            # self is a row.
            elif self.shape[0] == 1 and self.shape[1] == other.shape[1]:
                copy = dia_matrix((self.toarray().ravel(), [0]),
            # Column vector times matrix. other is a column.
            elif other.shape[1] == 1 and self.shape[0] == other.shape[0]:
                other = dia_matrix((other.toarray().ravel(), [0]),
                                    shape=(other.shape[0], other.shape[0]))
                return other._mul_sparse_matrix(self)
            # self is a column.
            elif self.shape[1] == 1 and self.shape[0] == other.shape[0]:
                copy = dia_matrix((self.toarray().ravel(), [0]),

src/s/c/scipy-0.13.3/scipy/sparse/coo.py   scipy(Download)
    def todia(self):
        from .dia import dia_matrix
 
        ks = self.col - self.row  # the diagonal for each nonzero
        diags = np.unique(ks)
            data[np.searchsorted(diags,ks), self.col] = self.data
 
        return dia_matrix((data,diags), shape=self.shape)
 
    def todok(self):

src/s/c/scipy-HEAD/scipy/sparse/coo.py   scipy(Download)
    def todia(self):
        from dia import dia_matrix
 
        ks = self.col - self.row  #the diagonal for each nonzero
        diags = np.unique(ks)
        data[ np.searchsorted(diags,ks), self.col ] = self.data
 
        return dia_matrix((data,diags), shape=self.shape)
 
    def todok(self):

src/s/c/scipy-0.13.3/scipy/sparse/construct.py   scipy(Download)
from .coo import coo_matrix
from .lil import lil_matrix
from .dia import dia_matrix
 
from .base import issparse

src/s/c/scipy-HEAD/scipy/sparse/construct.py   scipy(Download)
from coo import coo_matrix
from lil import lil_matrix
from dia import dia_matrix
 
from base import issparse