tens_gr_square_loss: Calculate square loss term in gradient of objective function
In lambdamoses/novoSpaRc: Spatial Reconstruction of Tissues from scRNA-seq Data

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 `calc_graph_dist` in this package.
`tD_loc`	Transpose of the graph-based distance matrix between pairs of locations generated from function `calc_graph_dist` in this package. Since the k-nearest neighbor graph is directed, the matrix is not necessarily symmetric.
`T_tmp`	A matrix for probabilistic assignment of cells (in rows) to locations (in columns). This matrix will be updated in gradient descent.