def test_correlation_9(self): "farray.correlation_9" x = self.a1 y = self.a2 x2 = np.empty((2, x.shape[0], x.shape[1])) x2[0] = x x2[1] = x y2 = np.empty((2, y.shape[0], y.shape[1])) y2[0] = y y2[1] = y with np.errstate(invalid='ignore'): corr = correlation(x, y, axis=-1) desired = np.array([nan, 1, -1, -0.5]) aae(corr, desired, err_msg="aggregate of 1d tests") x = self.b1 y = self.b2 x2 = np.empty((2, x.shape[0], x.shape[1])) x2[0] = x x2[1] = x y2 = np.empty((2, y.shape[0], y.shape[1])) y2[0] = y y2[1] = y with np.errstate(invalid='ignore'): corr = correlation(x, y, axis=-1) desired = np.array([nan, 1, -1, -0.5]) aae(corr, desired, err_msg="aggregate of 1d tests")
def test_correlation_3(self): "farray.correlation_3" x = self.a1[0,:] y = self.a2[0,:] corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined") x = self.b1[0,:] y = self.b2[0,:] corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined")
def test_correlation_4(self): "farray.correlation_4" x = self.a1[1,:] y = self.a2[1,:] corr = correlation(x, y) aae(corr, 1, err_msg="Perfect +1 correation") x = self.b1[1,:] y = self.b2[1,:] corr = correlation(x, y) aae(corr, 1, err_msg="Perfect +1 correation")
def test_correlation_5(self): "farray.correlation_5" x = self.a1[2,:] y = self.a2[2,:] corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation") x = self.b1[2,:] y = self.b2[2,:] corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation")
def test_correlation_6(self): "farray.correlation_6" x = self.a1[3,:] y = self.a2[3,:] corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation") x = self.b1[3,:] y = self.b2[3,:] corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation")
def test_correlation_5(self): "farray.correlation_5" x = self.a1[2, :] y = self.a2[2, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation") x = self.b1[2, :] y = self.b2[2, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation")
def test_correlation_3(self): "farray.correlation_3" x = self.a1[0, :] y = self.a2[0, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined") x = self.b1[0, :] y = self.b2[0, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined")
def test_correlation_6(self): "farray.correlation_6" x = self.a1[3,:] y = self.a2[3,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation") x = self.b1[3,:] y = self.b2[3,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation")
def test_correlation_5(self): "farray.correlation_5" x = self.a1[2,:] y = self.a2[2,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation") x = self.b1[2,:] y = self.b2[2,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -1, err_msg="Perfect -1 correation")
def test_correlation_3(self): "farray.correlation_3" x = self.a1[0,:] y = self.a2[0,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined") x = self.b1[0,:] y = self.b2[0,:] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="Correlation undefined")
def test_correlation_6(self): "farray.correlation_6" x = self.a1[3, :] y = self.a2[3, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation") x = self.b1[3, :] y = self.b2[3, :] with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, -0.5, err_msg="-0.5 correation")
def test_correlation_8(self): "farray.correlation_8" x = self.a1.T y = self.a2.T with np.errstate(invalid='ignore'): corr = correlation(x, y, axis=0) desired = np.array([nan, 1, -1, -0.5]) aae(corr, desired, err_msg="aggregate of 1d tests") x = self.b1.T y = self.b2.T with np.errstate(invalid='ignore'): corr = correlation(x, y, axis=0) desired = np.array([nan, 1, -1, -0.5]) aae(corr, desired, err_msg="aggregate of 1d tests")
def test_correlation_1(self): "farray.correlation_1" x = np.array([]) y = np.array([]) with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="Empty correlation should be NaN")
def test_correlation_1(self): "farray.correlation_1" x = np.array([]) y = np.array([]) warnings.simplefilter("ignore") corr = correlation(x, y) aae(corr, np.nan, err_msg="Empty correlation should be NaN")
def test_correlation_2(self): "farray.correlation_2" x = np.array([nan, nan]) y = np.array([nan, nan]) warnings.simplefilter("ignore") corr = correlation(x, y) aae(corr, np.nan, err_msg="All NaN correlation should be NaN")
def test_correlation_2(self): "farray.correlation_2" x = np.array([nan, nan]) y = np.array([nan, nan]) with np.errstate(invalid='ignore'): corr = correlation(x, y) aae(corr, np.nan, err_msg="All NaN correlation should be NaN")
def test_correlation_2(self): "farray.correlation_2" x = np.array([nan, nan]) y = np.array([nan, nan]) corr = correlation(x, y) aae(corr, np.nan, err_msg="All NaN correlation should be NaN")
def test_correlation_1(self): "farray.correlation_1" x = np.array([]) y = np.array([]) corr = correlation(x, y) aae(corr, np.nan, err_msg="Empty correlation should be NaN")