Merge pull request #92 from qutech/bugfix/tests

Fix tests and deprectations

Author: thangleiter

examples/randomized_benchmarking.py

@@ -32,7 +32,7 @@
 import qutip as qt
 from numpy import ndarray
 from numpy.random import permutation
-from scipy import io, optimize
+from scipy import io, optimize, integrate
 
 # %%
 
@@ -46,7 +46,7 @@ def state_infidelity(pulse: ff.PulseSequence, S: ndarray, omega: ndarray,
     """Compute state infidelity for input state eigenstate of pauli *ind*"""
     R = pulse.get_control_matrix(omega)
     F = np.einsum('jko->jo', ff.util.abs2(R[:, np.delete([0, 1, 2, 3], ind)]))
-    return np.trapz(F*S, omega)/(2*np.pi*pulse.d)
+    return integrate.trapezoid(F*S, omega)/(2*np.pi*pulse.d)
 
 
 def find_inverse(U: ndarray, cliffords: Sequence[ff.PulseSequence]) -> ndarray:

filter_functions/analytic.py

@@ -80,7 +80,7 @@ def CPMG(z, n):
 
 def CDD(z, g):
     return 2**(2*g + 1)*np.sin(z/2**(g + 1))**2 *\
-        np.product([np.sin(z/2**(k + 1))**2 for k in range(1, g+1)], axis=0)
+        np.prod([np.sin(z/2**(k + 1))**2 for k in range(1, g+1)], axis=0)
 
 
 def UDD(z, n):

filter_functions/basis.py

@@ -174,7 +174,7 @@ def __new__(cls, basis_array: Sequence, traceless: Optional[bool] = None,
                 pass
 
             basis = util.parse_operators(basis_array, 'basis_array')
-            if basis.shape[0] > np.product(basis.shape[1:]):
+            if basis.shape[0] > np.prod(basis.shape[1:]):
                 raise ValueError('Given overcomplete set of basis matrices. '
                                  'Not linearly independent.')
 

filter_functions/plotting.py

@@ -261,7 +261,8 @@ def plot_bloch_vector_evolution(
         b.axes.add_collection3d(lc, zdir='z', zs=segments[:, :, 2])
 
         if add_cbar:
-            default_cbar_kwargs = dict(shrink=2/3, pad=0.05, label=r'$t$ ($\tau$)', ticks=[0, 1])
+            default_cbar_kwargs = dict(shrink=2/3, pad=0.05, label=r'$t$ ($\tau$)', ticks=[0, 1],
+                                       ax=b.axes)
             cbar_kwargs = {**default_cbar_kwargs, **(cbar_kwargs or {})}
             b.fig.colorbar(cm.ScalarMappable(cmap=cmap), **cbar_kwargs)
 

filter_functions/util.py

@@ -227,6 +227,9 @@ def parse_operators(opers: Sequence[Operator], err_loc: str) -> List[ndarray]:
         elif hasattr(oper, 'full'):
             # qutip.Qobj
             parsed_opers.append(oper.full())
+        elif hasattr(oper, 'to_array'):
+            # qutip.Dia object
+            parsed_opers.append(oper.to_array())
         elif hasattr(oper, 'todense'):
             # sparse object
             parsed_opers.append(oper.todense())
@@ -843,7 +846,7 @@ def integrate(f: ndarray, x: Optional[ndarray] = None, dx: float = 1.0) -> Union
 
     See Also
     --------
-    numpy.trapz
+    scipy.integrate.trapezoid
 
     """
     dx = np.diff(x) if x is not None else dx

tests/test_precision.py

@@ -41,7 +41,7 @@ def _get_integrals_first_order(d, E, eigval, dt, t0):
     EdE = np.add.outer(E, dE)
     integrand = np.exp(1j*np.multiply.outer(EdE, tspace - t0))
 
-    integral_numeric = integrate.trapz(integrand, tspace)
+    integral_numeric = integrate.trapezoid(integrand, tspace)
     integral = numeric._first_order_integral(E, eigval, dt, exp_buf, int_buf)
     return integral, integral_numeric
 
@@ -61,12 +61,12 @@ def _get_integrals_second_order(d, E, eigval, dt, t0):
 
     ex = (np.multiply.outer(dE, tspace - t0)
           + np.multiply.outer(E, tspace)[:, None, None])
-    I1 = integrate.cumtrapz(util.cexp(ex), tspace, initial=0)
+    I1 = integrate.cumulative_trapezoid(util.cexp(ex), tspace, initial=0)
     ex = (np.multiply.outer(dE, tspace - t0)
           - np.multiply.outer(E, tspace)[:, None, None])
     integrand = util.cexp(ex)[:, :, :, None, None] * I1[:, None, None]
 
-    integral_numeric = integrate.trapz(integrand, tspace)
+    integral_numeric = integrate.trapezoid(integrand, tspace)
     integral = numeric._second_order_integral(E, eigval, dt, int_buf, frc_bufs, dE_bufs,
                                               exp_buf, msk_bufs)
     return integral, integral_numeric

tests/test_superoperator.py

@@ -129,7 +129,7 @@ def partial_transpose(A):
             self.assertArrayEqual(CP, _CP)
             self.assertTrue(np.all(CP))
             if U_sup.ndim == 2:
-                self.assertIsInstance(CP, (bool, np.bool8))
+                self.assertIsInstance(CP, (bool, np.bool_))
             else:
                 self.assertEqual(CP.shape[0], U_sup.shape[0])
             # Only one nonzero eigenvalue
@@ -143,7 +143,7 @@ def partial_transpose(A):
             CP = superoperator.liouville_is_CP(U_sup, pulse.basis)
 
             self.assertTrue(np.all(CP))
-            self.assertIsInstance(CP, (bool, np.bool8))
+            self.assertIsInstance(CP, (bool, np.bool_))
 
     def test_liouville_is_cCP(self):
         for d in rng.integers(2, 9, (15,)):
@@ -165,7 +165,7 @@ def test_liouville_is_cCP(self):
             self.assertArrayEqual(cCP, _cCP)
             self.assertTrue(np.all(cCP))
             if H_sup.ndim == 2:
-                self.assertIsInstance(cCP, (bool, np.bool8))
+                self.assertIsInstance(cCP, (bool, np.bool_))
             else:
                 self.assertEqual(cCP.shape[0], H_sup.shape[0])
             self.assertArrayAlmostEqual(D, 0, atol=1e-14)
@@ -182,6 +182,6 @@ def test_liouville_is_cCP(self):
 
             self.assertTrue(np.all(cCP))
             if K_sup.ndim == 2:
-                self.assertIsInstance(cCP, (bool, np.bool8))
+                self.assertIsInstance(cCP, (bool, np.bool_))
             else:
                 self.assertEqual(cCP.shape[0], K_sup.shape[0])

tests/test_util.py

@@ -23,6 +23,7 @@
 """
 import numpy as np
 import pytest
+from scipy import integrate
 
 from filter_functions import PulseSequence, util
 from tests import testutil
@@ -415,11 +416,11 @@ def test_mdot(self):
     def test_integrate(self):
         f = rng.standard_normal(32)
         x = rng.random(32)
-        self.assertEqual(util.integrate(f, x), np.trapz(f, x))
+        self.assertEqual(util.integrate(f, x), integrate.trapezoid(f, x))
 
         f = rng.standard_normal((2, 32)).astype(complex)
         x = rng.random(32)
-        self.assertArrayEqual(util.integrate(f, x), np.trapz(f, x))
+        self.assertArrayEqual(util.integrate(f, x), integrate.trapezoid(f, x))
 
         f = rng.standard_normal(32)
         x = np.linspace(0, 1, 32)