diff options
Diffstat (limited to 'silx/math/fit/test/test_fitmanager.py')
| -rw-r--r-- | silx/math/fit/test/test_fitmanager.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/silx/math/fit/test/test_fitmanager.py b/silx/math/fit/test/test_fitmanager.py index 7a643cb..acac242 100644 --- a/silx/math/fit/test/test_fitmanager.py +++ b/silx/math/fit/test/test_fitmanager.py @@ -125,7 +125,7 @@ class TestFitmanager(ParametricTestCase): """Test fit manager on synthetic data using a gaussian function and a linear background""" # Create synthetic data with a sum of gaussian functions - x = numpy.arange(1000).astype(numpy.float) + x = numpy.arange(1000).astype(numpy.float64) p = [1000, 100., 250, 255, 650., 45, @@ -186,7 +186,7 @@ class TestFitmanager(ParametricTestCase): """Test FitManager using a custom fit function defined in an external file and imported with FitManager.loadtheories""" # Create synthetic data with a sum of gaussian functions - x = numpy.arange(100).astype(numpy.float) + x = numpy.arange(100).astype(numpy.float64) # a, b, c are the fit parameters # d is a known scaling parameter that is set using configure() @@ -233,7 +233,7 @@ class TestFitmanager(ParametricTestCase): """Test FitManager using a custom fit function defined in an external file and imported with FitManager.loadtheories (legacy PyMca format)""" # Create synthetic data with a sum of gaussian functions - x = numpy.arange(100).astype(numpy.float) + x = numpy.arange(100).astype(numpy.float64) # a, b, c are the fit parameters # d is a known scaling parameter that is set using configure() @@ -279,7 +279,7 @@ class TestFitmanager(ParametricTestCase): """Test FitManager using a custom fit function imported with FitManager.addtheory""" # Create synthetic data with a sum of gaussian functions - x = numpy.arange(100).astype(numpy.float) + x = numpy.arange(100).astype(numpy.float64) # a, b, c are the fit parameters # d is a known scaling parameter that is set using configure() @@ -369,7 +369,7 @@ class TestFitmanager(ParametricTestCase): for theory_name, theory_fun in (('Step Down', sum_stepdown), ('Step Up', sum_stepup)): # Create synthetic data with a sum of gaussian functions - x = numpy.arange(1000).astype(numpy.float) + x = numpy.arange(1000).astype(numpy.float64) # ('Height', 'Position', 'FWHM') p = [1000, 439, 250] @@ -407,7 +407,7 @@ def cubic(x, a, b, c, d): class TestPolynomials(unittest.TestCase): """Test polynomial fit theories and fit background""" def setUp(self): - self.x = numpy.arange(100).astype(numpy.float) + self.x = numpy.arange(100).astype(numpy.float64) def testQuadraticBg(self): gaussian_params = [100, 45, 8] |