Fix numpy.matrix deprecation warnings in bootstrap routines by Copilot · Pull Request #809 · PmagPy/PmagPy

Copilot · 2025-11-06T20:39:54Z

NumPy 1.25+ deprecated implicit scalar coercion from (1,1) matrices/arrays, causing thousands of warnings per bootstrap run. The warnings will become errors in future NumPy releases.

Changes

pmagpy/pmag.py

form_Ghat, form_Mhat, form_Q, find_CR, find_CMDT_CR: Replace np.matrix with np.ndarray, use @ operator for matmul
find_T: Return scalar via .item() instead of (1,1) array
Replace .getT() → .T and .getH() → .conj().T throughout

pmagpy/ipmag.py

common_mean_bootstrap_H23: Replace .getH() with .conj().T, explicit float conversion for Lmin_b[i]

Example

Before:

def form_Ghat(X, Mhat):
    X = np.matrix(X)
    Ghat = np.matrix(np.zeros((2,2)))
    for u in range(2):
        for v in range(2):
            for i in range(n):
                Ghat[u,v] += Mhat_T[:,u].getT()*X[:,i]*X[:,i].getT()*Mhat_T[:,v]  # ⚠️ Warning
    return Ghat

After:

def form_Ghat(X, Mhat):
    X = np.asarray(X)
    Ghat = np.zeros((2,2))
    for u in range(2):
        for v in range(2):
            for i in range(n):
                Ghat[u,v] += (Mhat_T[:,u] @ X[:,i]) * (X[:,i] @ Mhat_T[:,v])  # ✓ Clean
    return Ghat

No functional changes—purely API modernization to eliminate deprecated numpy.matrix usage.

Warning

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Original prompt

This section details on the original issue you should resolve

<issue_title>DeprecationWarnings in ipmag bootstrap routines due to numpy.matrix scalar coercion</issue_title>
<issue_description>Summary

Running mean_bootstrap_confidence, common_mean_bootstrap, common_mean_bootstrap_H23 now floods stderr with DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated…. These warnings come from writing (1, 1) numpy.matrix results into scalar slots. NumPy 1.25 deprecated that behavior and it will become an error in a future NumPy release, so the ipmag bootstrap utilities will eventually fail.

The hottest spots are:

pmagpy/pmag.py:13799 (form_Ghat) when accumulating a (1, 1) matrix into Ghat[u, v].

pmagpy/ipmag.py:431 (mean_bootstrap_confidence) when pmag.find_T(...) returns a matrix that is stored in T_b.

pmagpy/ipmag.py:1371 (common_mean_bootstrap_H23) when np.min(D_b) yields a (1, 1) matrix that is stored in Lmin_b.

Every Monte Carlo iteration repeats the warning, so callers see thousands of messages.

Observed Behavior
pmagpy/pmag.py:13799: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
pmagpy/ipmag.py:431: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
pmagpy/ipmag.py:1371: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
Depending on num_sims, thousands of instances are printed to stderr.

Expected Behavior

Bootstrap routines should run without deprecation warnings on current NumPy releases, and continue to work once NumPy removes implicit numpy.matrix→scalar coercion.

Proposed Fix (high level)

Replace numpy.matrix usage in form_Ghat, form_Mhat, etc. with plain ndarray calculations, extracting scalars explicitly via .item() / float() when needed.

Update pmag.find_T and its call sites to return and store scalars or 1‑D arrays instead of (1, 1) matrices.
</issue_description>

Comments on the Issue (you are @copilot in this section)

Fixes DeprecationWarnings in ipmag bootstrap routines due to numpy.matrix scalar coercion #808

💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.

- Replace numpy.matrix with ndarray in form_Ghat, form_Mhat, form_Q, find_T, find_CR, find_CMDT_CR - Use .item() to explicitly extract scalars from matrix operations - Replace .getT() with .T and .getH() with .conj().T - Fix matrix multiplication to use @ operator instead of * - Tested with NumPy 2.3.4 - no deprecation warnings Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

- Ensure form_Q converts inputs to float to avoid in-place division errors - All tests now pass without warnings Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

Swanson-Hysell · 2026-02-28T13:19:13Z

This has been dealt with in a separate pull request that was just merged #820

Initial plan

52d03fa

Copilot AI assigned Copilot and Swanson-Hysell Nov 6, 2025

Copilot started work on behalf of Swanson-Hysell November 6, 2025 20:40 View session

Copilot AI and others added 4 commits November 6, 2025 20:51

Fix form_Q to handle integer input arrays

f5591d9

- Ensure form_Q converts inputs to float to avoid in-place division errors - All tests now pass without warnings Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

Remove accidentally committed test output files and update .gitignore

dbbde75

Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

Fix typo: boostrap -> bootstrap in comment

27c0bbe

Co-authored-by: Swanson-Hysell <4332322+Swanson-Hysell@users.noreply.github.com>

Copilot AI changed the title ~~[WIP] Fix deprecation warnings in ipmag bootstrap routines~~ Fix numpy.matrix deprecation warnings in bootstrap routines Nov 6, 2025

Copilot finished work on behalf of Swanson-Hysell November 6, 2025 21:05

Copilot AI requested a review from Swanson-Hysell November 6, 2025 21:05

Swanson-Hysell closed this Feb 28, 2026

Swanson-Hysell deleted the copilot/fix-deprecation-warnings-numpy branch February 28, 2026 13:19

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Fix numpy.matrix deprecation warnings in bootstrap routines#809

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Copilot AI commented Nov 6, 2025 •

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Copilot AI commented Nov 6, 2025 •

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