Merge pull request #207 from SasView/py37-sascalc

src/sas/sascalc/corfunc/corfunc_calculator.py

@@ -244,7 +244,9 @@ def _porod(self, q, K, sigma, bg):
     def _fit_guinier(self, q, iq):
         """Fit the Guinier region of the curve"""
         A = np.vstack([q**2, np.ones(q.shape)]).T
-        return lstsq(A, np.log(iq), rcond=None)
+        # CRUFT: numpy>=1.14.0 allows rcond=None for the following default
+        rcond = np.finfo(float).eps * max(A.shape)
+        return lstsq(A, np.log(iq), rcond=rcond)
 
     def _fit_porod(self, q, iq):
         """Fit the Porod region of the curve"""

src/sas/sascalc/invariant/invariant.py

@@ -343,8 +343,10 @@ def fit(self, power=None, qmin=None, qmax=None):
             return [a, b], [0, math.sqrt(err)]
         else:
             A = np.vstack([linearized_data.x / linearized_data.dy, 1.0 / linearized_data.dy]).T
+            # CRUFT: numpy>=1.14.0 allows rcond=None for the following default
+            rcond = np.finfo(float).eps * max(A.shape)
             p, residuals, _, _ = np.linalg.lstsq(A, linearized_data.y / linearized_data.dy,
-                                                 rcond=None)
+                                                 rcond=rcond)
 
             # Get the covariance matrix, defined as inv_cov = a_transposed * a
             err = np.zeros(2)

src/sas/sascalc/pr/invertor.py

@@ -473,7 +473,9 @@ def lstsq(self, nfunc=5, nr=20):
             raise RuntimeError("Invertor: could not invert I(Q)\n  %s" % str(exc))
 
         # Perform the inversion (least square fit)
-        c, chi2, _, _ = lstsq(a, b, rcond=-1)
+        # CRUFT: numpy>=1.14.0 allows rcond=None for the following default
+        rcond = np.finfo(float).eps * max(a.shape)
+        c, chi2, _, _ = lstsq(a, b, rcond=rcond)
         # Sanity check
         try:
             float(chi2)