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# scipy.ndimage.gaussian_filter

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```        if mode!="gaussian":
print "apply Gaussian filter in image_process()"
return ndimage.gaussian_filter(data, sigma=sigma, order=order)

```

```import numpy as np
import scipy.ndimage as ndi
from scipy.ndimage import (gaussian_filter, convolve,
generate_binary_structure, binary_erosion, label)

```
```    if mask is None:
fsmooth = lambda x: gaussian_filter(x, sigma, mode='constant')
jsobel = ndi.sobel(smoothed, axis=1)
```

```points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = ndimage.gaussian_filter(im, sigma=l/(4.*n))

```

```points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = ndimage.gaussian_filter(im, sigma=l/(4.*n))

```

```points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = ndimage.gaussian_filter(im, sigma=l/(4.*n))

```

```
lena = scipy.misc.lena()
blurred_lena = ndimage.gaussian_filter(lena, sigma=3)
very_blurred = ndimage.gaussian_filter(lena, sigma=5)
local_mean = ndimage.uniform_filter(lena, size=11)
```

```points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = ndimage.gaussian_filter(im, sigma=l/(4.*n))

```

```points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im = ndimage.gaussian_filter(im, sigma=l/(4.*n))

```

```import cellprofiler.cpimage as cpi

from scipy.ndimage import gaussian_filter
from cellprofiler.cpmath.filter import sobel

```
```        pixel_data = image.pixel_data
if self.filter_choice == S_GAUSSIAN:
pixel_data = gaussian_filter(pixel_data, sigma=self.sigma.value)
else:
pixel_data = sobel(pixel_data)
```

```import cellprofiler.cpmodule as cpm
import cellprofiler.settings as cps
import cellprofiler.cpimage as cpi

from scipy.ndimage import gaussian_filter
```
```        pixel_data = image.pixel_data
if self.filter_choice == S_GAUSSIAN:
pixel_data = gaussian_filter(pixel_data, sigma=1)
else:
pixel_data = sobel(pixel_data)
```

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