141903a21846d54aaf09aa95a3bcdd8b673ee116,starry/ops/theano_op.py,StarryGradOp,perform,#StarryGradOp#Any#Any#Any#,67

Before Change

        self.base_op.map[:, :] = y
        self.base_op.map[:] = u

        ro_ = tt.switch(tt.lt(zo, 0.0), ro, 0.0).eval()
        _, grads = self.base_op.map.flux(theta=theta, xo=xo, yo=yo, 
                                         ro=ro_, gradient=True)

After Change

        self.base_op.map[:, :] = y
        // HACK: nudge at least one ylm away from zero
        // to force starry to compute all derivatives
        if (len(y) > 2) and (y[2] == 0):
            self.base_op.map[1, 0] = 1.e-15
        _, grads = self.base_op.map.flux(theta=theta, xo=xo, yo=yo, zo=zo,
                                         ro=ro, gradient=True)

Instances