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-rw-r--r--doc/source/Tutorials/fit.rst6
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/source/Tutorials/fit.rst b/doc/source/Tutorials/fit.rst
index b1b28e5..d9671f4 100644
--- a/doc/source/Tutorials/fit.rst
+++ b/doc/source/Tutorials/fit.rst
@@ -234,7 +234,7 @@ the previous tutorial (See `Weighted fit`_)
from silx.math.fit.fitmanager import FitManager
# Create synthetic data with a sum of gaussian functions
- x = numpy.arange(1000).astype(numpy.float)
+ x = numpy.arange(1000).astype(numpy.float64)
y = 2.4 * x**4 - 10. * x**3 + 15.2 * x**2 - 24.6 * x + 150.
# define our fit function: a generic polynomial of degree 4
@@ -304,7 +304,7 @@ data, generated using another *silx* module: :mod:`silx.math.fit.functions`.
from silx.math.fit.fitmanager import FitManager
# Create synthetic data with a sum of gaussian functions
- x = numpy.arange(1000).astype(numpy.float)
+ x = numpy.arange(1000).astype(numpy.float64)
# height, center x, fwhm
p = [1000, 100., 250, # 1st peak
@@ -526,7 +526,7 @@ Simple usage
from silx.gui.fit import FitWidget
from silx.math.fit.functions import sum_gauss
- x = numpy.arange(2000).astype(numpy.float)
+ x = numpy.arange(2000).astype(numpy.float64)
constant_bg = 3.14
# gaussian parameters: height, position, fwhm