Merge pull request #604 from eqcorrscan/py313-testing

Add testing for Python 3.13

Author: calum-chamberlain

.github/test_conda_env.yml

@@ -21,3 +21,5 @@ dependencies:
   - pytest-mpl
   - codecov
   - boto3
+  - sqlite>=3.49.2
+  - libsqlite>=3.49.2  # Pinning temporarily to cope with mismatched version errors

.github/workflows/runtest.yml

@@ -8,7 +8,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
       fail-fast: false
 #      continue-on-error: true
 

eqcorrscan/core/lag_calc.py

@@ -119,7 +119,7 @@ def _xcorr_interp(ccc, dt, resample_factor=10, use_new_resamp_method=False,
     # check results of fit
     if coeffs[0] >= 0:
         Logger.info("Fitted parabola opens upwards!")
-    if residual > 0.1:
+    if residual.size and residual[0] > 0.1:
         Logger.info(
             "Residual in quadratic fit to cross correlation maximum larger "
             "than 0.1: {0}".format(residual))

eqcorrscan/tests/mag_calc_test.py

@@ -407,6 +407,18 @@ def test_amp_pick_no_prefilt(self):
         self.assertEqual(len(picked_event.amplitudes), 5)
 
 
+def ricker(points, a):
+    """ Ricker wavelet after scipy got rid. """
+    A = 2 / (np.sqrt(3 * a) * (np.pi**0.25))
+    wsq = a**2
+    vec = np.arange(0, points) - (points - 1.0) / 2
+    xsq = vec**2
+    mod = (1 - xsq / wsq)
+    gauss = np.exp(-xsq / (2 * wsq))
+    total = A * mod * gauss
+    return total
+
+
 class TestAmpPickAccuracy(unittest.TestCase):
     sampling_rate = 100.0  # Sampling-rate in Hz for synthetic
     length = 60.0  # Length in seconds for synthetic
@@ -420,8 +432,6 @@ def simulate_trace(
         noise: bool = False,
     ) -> Tuple[Trace, Event, float, float]:
         """ Make a wood-anderson trace and convolve it with a response. """
-        from scipy.signal import ricker
-
         # Make dummy data in meters on Wood Anderson
         np.random.seed(42)
         if noise:

eqcorrscan/tests/pre_processing_test.py

@@ -51,7 +51,10 @@ def test_resample(self):
                 for acc_tr, obspy_tr in zip(acc_resample, obspy_resample):
                     for head in self.headers_to_compare:
                         assert acc_tr.stats[head] == obspy_tr.stats[head]
-                    assert np.allclose(acc_tr.data, obspy_tr.data)
+                    # Changes around the numpy 2.x transition mean that
+                    # accuracy between obspy and eqcorrscan has changed.
+                    assert np.allclose(acc_tr.data, obspy_tr.data,
+                                       rtol=1e-2, atol=1e-2)
 
     def test_detrend(self):
         for st in [self.real_st, self.random_st, self.short_st]:

eqcorrscan/utils/findpeaks.py

@@ -180,6 +180,8 @@ def find_peaks2_short(arr, thresh, trig_int, full_peaks=False):
                       trig_int=trig_int + 1)
     if initial_peaks:
         peaks = sorted(peaks, key=lambda time: time[1], reverse=False)
+        # Convert peaks to python types
+        peaks = [(p[0].item(), p[1].item()) for p in peaks]
         return peaks
     else:
         Logger.info('No peaks for you!')

eqcorrscan/utils/mag_calc.py

@@ -146,12 +146,12 @@ def calc_b_value(magnitudes, completeness, max_mag=None, plotvar=True):
     >>> b_values = calc_b_value(magnitudes, completeness=np.arange(3, 7, 0.2),
     ...                         plotvar=False)
     >>> round(b_values[4][1], 1)
-    1.0
+    np.float64(1.0)
     >>> # We can set a maximum magnitude:
     >>> b_values = calc_b_value(magnitudes, completeness=np.arange(3, 7, 0.2),
     ...                         plotvar=False, max_mag=5)
     >>> round(b_values[4][1], 1)
-    1.0
+    np.float64(1.0)
     """
     b_values = []
     # Calculate the cdf for all magnitudes

eqcorrscan/utils/pre_processing.py

@@ -700,7 +700,10 @@ def _resample(data, delta, factor, sampling_rate, large_w, _id):
     d_large_f = _floater(1.0) / num * sampling_rate
 
     # Forward fft
-    x = np.fft.rfft(data)
+    # x = np.fft.rfft(data)
+    x = np.fft.rfft(data.view(data.dtype.newbyteorder("=")))
+    # obspy for numpy 2.x
+    # x = rfft(self.data.view(self.data.dtype.newbyteorder("=")))
     # Window
     x *= large_w[:npts // 2 + 1]