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Sc/edits2023 #22

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5eb5edf
renamed and moved the data for morph paper
ShuonanChen Mar 11, 2022
781eee4
updateing some code
ShuonanChen Nov 17, 2023
b1a7771
remove deplicated functions
ShuonanChen Nov 17, 2023
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0 ...arks/GTvox_isotropic_x2304_y1984_z512.pkl → ...rcodediscovery/barcode_discovery_data.pkl
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24 changes: 12 additions & 12 deletions bardensr/benchmarks/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -224,7 +224,7 @@ def meanmin_divergence(u,v):


def downsample1(x,ds,axis=0):
newshape=np.array(x.shape,dtype=np.int)
newshape=np.array(x.shape,dtype=int)
newshape[axis]=np.ceil(newshape[axis]/ds)
newguy=np.zeros(newshape,dtype=x.dtype)

Expand Down Expand Up @@ -273,9 +273,9 @@ def downsample(self,dsd):
R,C=self.codebook.shape[:2]
bc3=self.copy()
bc3.X=np.array([[downsample_nd(bc3.X[r,c],dsd) for c in range(C)] for r in range(R)])
bc3.rolonies['m0']=np.require(bc3.rolonies['m0']//dsd,dtype=np.int)
bc3.rolonies['m1']=np.require(bc3.rolonies['m1']//dsd,dtype=np.int)
bc3.rolonies['m2']=np.require(bc3.rolonies['m2']//dsd,dtype=np.int)
bc3.rolonies['m0']=np.require(bc3.rolonies['m0']//dsd,dtype=int)
bc3.rolonies['m1']=np.require(bc3.rolonies['m1']//dsd,dtype=int)
bc3.rolonies['m2']=np.require(bc3.rolonies['m2']//dsd,dtype=int)
return bc3

def copy(self,copy_imagestack=False,copy_codebook=False):
Expand Down Expand Up @@ -307,7 +307,7 @@ def save_hdf5(self,fn):
f.create_dataset('codebook',data=self.codebook)
f.create_group('rolonies')
for nm in ['j','m0','m1','m2']:
ds=np.array(self.rolonies[nm]).astype(np.int)
ds=np.array(self.rolonies[nm]).astype(int)
f.create_dataset('rolonies/'+nm,data=ds)
for nm in ['remarks','status']:
ds=np.array(self.rolonies[nm]).astype("S")
Expand All @@ -319,7 +319,7 @@ def save_hdf5(self,fn):
if self.GT_voxels is not None:
f.create_group('GT_voxels')
for nm in ['j','m0','m1','m2']:
ds=np.array(self.GT_voxels[nm]).astype(np.int)
ds=np.array(self.GT_voxels[nm]).astype(int)
f.create_dataset('GT_voxels/'+nm,data=ds)

if self.GT_meshes is not None:
Expand Down Expand Up @@ -388,14 +388,14 @@ def voxel_meanmin_divergences(self,df,barcode_pairing=None,use_tqdm_notebook=Fal
def rolony_fpfn(self,df,radius,good_subset=None):
if len(df)==0:
noro=locsdf.locs_and_j_to_df(
np.zeros((0,3),dtype=np.int),
np.zeros(0,dtype=np.int),
np.zeros((0,3),dtype=int),
np.zeros(0,dtype=int),
),
return RolonyFPFNResult(
fn=self.n_spots,
fp=0,
fn_indices=np.zeros(0,dtype=np.int),
fp_indices=np.zeros(0,dtype=np.int),
fn_indices=np.zeros(0,dtype=int),
fp_indices=np.zeros(0,dtype=int),
fp_rolonies=noro,
fn_rolonies=self.rolonies.copy(),
agreement_rolonies=noro,
Expand Down Expand Up @@ -483,15 +483,15 @@ def load_h5py(fn):

rn={}
for nm in ['j','m0','m1','m2']:
rn[nm]=f['rolonies/'+nm][:].astype(np.int)
rn[nm]=f['rolonies/'+nm][:].astype(int)
for nm in ['remarks','status']:
rn[nm]=f['rolonies/'+nm][:].astype('U')
dct['rolonies']=pd.DataFrame(rn)

if 'GT_voxels' in f:
rn={}
for nm in ['j','m0','m1','m2']:
rn[nm]=f['GT_voxels/'+nm][:].astype(np.int)
rn[nm]=f['GT_voxels/'+nm][:].astype(int)
dct['GT_voxels']=pd.DataFrame(rn)
else:
dct['GT_voxels']=None
Expand Down