Fixed issues with scipy sparse storage in scipy 1.11 #943
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swryan
approved these changes
Jun 28, 2023
| @@ -242,7 +241,8 @@ def _compute_partials_radau(self, inputs, partials): | |||
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| dstau_dt_x_size = np.repeat(dstau_dt, size)[:, np.newaxis] | |||
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| partials[xdotc_name, xd_name] = self.jacs['Ad'][name].multiply(dstau_dt_x_size).data | |||
| dxdotc_dxd = self.jacs['Ad'][name].multiply(dstau_dt_x_size) | |||
| partials[xdotc_name, xd_name] = dxdotc_dxd.data | |||
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Is it ok to still use data here? Will it work the same way in old and new scipy?
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It seems to work fine, ultimately the issue was a change in formats to the matrices involved that I've resolved
Kenneth-T-Moore
approved these changes
Jun 28, 2023
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Summary
Some scipy sparse functions, particularly the
dataattribute, appear to behave somewhat differently in 1.11.Previously we relied on the data attribute with the assumption that data was given in row major order.
While this is true for
csr, matrix operations can result in translations to other format where that assumption does not hold.To resolve the issue, eliminate the use of the data attribute.
Related Issues
Backwards incompatibilities
None
New Dependencies
None