Description Usage Arguments Value

Projected gradient descent is used to numerically solve the optimization
problem of finding a probabilistic assignment of cells to locations. The
gradient of the loss function has a term *L(C_1, C_2) \otimes T*. This
function calculates that term when *L(a,b) = \frac 1 2 (a - b)^2*, namely
the square loss.

1 | ```
tens_gr_square_loss(D_cell, tD_loc, T_tmp)
``` |

`D_cell` |
Graph-based distance matrix between pairs of cells, generated
from function |

`tD_loc` |
Transpose of the graph-based distance matrix between pairs of
locations generated from function |

`T_tmp` |
A matrix for probabilistic assignment of cells (in rows) to locations (in columns). This matrix will be updated in gradient descent. |

A numeric matrix with cells in rows and locations in columns.

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