Source code for stimupy.utils.masks
import numpy as np
__all__ = [
"avg_target_values",
"avg_img_values",
"all_img_values",
"img_values",
]
[docs]
def avg_target_values(stim, mask_key="target_mask", f_average=np.median):
"""Average pixel value in each target region of stimulus
Parameters
----------
stim : dict[str: Any]
stimulus-dict with at least "img" and "mask"
containing the stimulus image and integer-mask, respectively.
mask_key : str
string with mask-key name
f_average: function, default=numpy.median
How to average/summarise the pixels in each target region
Returns
-------
list[float]
each entry in the list is the average value of pixels in target region,
index in the list is the integer index in the mask
See Also
--------
avg_img_values
"""
return avg_img_values(image=stim["img"], mask=stim[mask_key], f_average=f_average)
[docs]
def avg_img_values(image, mask, f_average=np.median):
"""Average values of pixels in image, per target region in integer mask
Values are calculated as means or medians, depending on the mode.
Parameters
----------
image : 2D numpy array
2D numpy array containing pixel values of the image
mask : 2D numpy array
2D numpy array of same size as image. Each target patch has an integer value.
Each pixel inside this patch has this integer value.
Patches do not need to be continuous.
f_average: function, default=numpy.median
How to average/summarise the pixels in each target region
Returns
-------
list[float]
each entry in the list is the average value of pixels in target region,
index in the list is the integer index in the mask
See Also
--------
all_img_values
"""
masked_outputs = all_img_values(image, mask)
values = [f_average(o[np.isfinite(o)]) for o in masked_outputs]
return values
[docs]
def all_img_values(img, mask):
"""Isolate all image values/pixels, per target region specified in integer mask
Parameters
----------
img : numpy.ndarray
Image-array of pixel values to be masked
mask : numpy.ndarray
Array of same size as img.
Each region-of-interest in mask is represented by an integer index.
Each pixel inside this patch has this integer value.
Patches do not need to be contiguous.
Returns
-------
list[numpy.arrays]
Each image/element of the list is a numpy.ndarray representing an image.
There is one image for each target patch in the integer mask.
In each image all values are set to NaN
except the ones corresponding to the target values of the respective target patch.
See Also
--------
img_values
"""
idc = np.unique(mask.astype(int))
imgs = [img_values(img, mask == idx) for idx in idc]
return imgs
[docs]
def img_values(img, mask):
"""Isolate only image pixels specified by a binary mask
Parameters
----------
img : numpy.ndarray
Image-array of pixel values to be masked
mask : numpy.ndarray
Array of same size as img.
All non-zero pixels/values are treated as ones in a binary bit mask.
Returns
-------
numpy.ndarray
numpy.ndarray of same size as img.
All bits corresponding to zero bits in the mask are set to NaN.
"""
return np.where(mask, img, np.nan)
