Skip to content

addressed the issue for np.float depreciation #2

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
shivanshsharma8834 wants to merge 1 commit into
base: master
Choose a base branch
from
Open

addressed the issue for np.float depreciation #2

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 5 additions & 5 deletions pystripe/core.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -333,9 +333,9 @@ def hist_match(source, template):
# take the cumsum of the counts and normalize by the number of pixels to
# get the empirical cumulative distribution functions for the source and
# template images (maps pixel value --> quantile)
s_quantiles = np.cumsum(s_counts).astype(np.float64)
s_quantiles = np.cumsum(s_counts).astype(float)
s_quantiles /= s_quantiles[-1]
t_quantiles = np.cumsum(t_counts).astype(np.float64)
t_quantiles = np.cumsum(t_counts).astype(float)
t_quantiles /= t_quantiles[-1]

# interpolate linearly to find the pixel values in the template image
Expand Down Expand Up @@ -432,7 +432,7 @@ def filter_streaks(img, sigma, level=0, wavelet='db3', crossover=10, threshold=-
except ValueError:
threshold = 1

img = np.array(img, dtype=np.float)
img = np.array(img, dtype=float)
#
# Need to pad image to multiple of 2
#
Expand Down Expand Up @@ -579,7 +579,7 @@ def read_filter_save(input_path, output_path, sigma, level=0, wavelet='db3',
selem=(background_window_size, background_window_size, 1),
spacing=(25, 25, 1),
interpolate=1,
dtype=np.float32,
dtype=float,
step=(2, 2, 1)),
lightsheet_vs_background=lightsheet_vs_background
).reshape(img.shape[0], img.shape[1])
Expand Down Expand Up @@ -746,7 +746,7 @@ def batch_filter(input_path, output_path, workers, chunks, sigma, level=0, wavel


def normalize_flat(flat):
flat_float = flat.astype(np.float32)
flat_float = flat.astype(float)
return flat_float / flat_float.max()


Expand Down