def test_stat3D(): import samri.plotting.maps as maps stat_map = "/usr/share/mouse-brain-atlases/dsurqec_200micron_roi-dr.nii" template = "/usr/share/mouse-brain-atlases/dsurqec_40micron_masked.nii" maps.stat3D(stat_map, template=template, save_as="_stat3D.png", show_plot=False, threshold=0.5, threshold_mesh = 0.5, )
def test_stat3D_mask(): import samri.plotting.maps as maps stat_map = '/usr/share/mouse-brain-templates/dsurqec_200micron_roi-dr.nii' template = '/usr/share/mouse-brain-templates/dsurqec_40micron_masked.nii' maps.stat3D(stat_map, template=template, save_as="_stat3D_mask.png", show_plot=False, threshold=0.5, threshold_mesh = 0.5, )
def test_stat3D_heatmap():
import samri.plotting.maps as maps
bindata_dir = '/usr/share/samri_bidsdata'
heatmap_image = '{}/l1/sub-4007/ses-ofM/sub-4007_ses-ofM_task-JogB_acq-EPIlowcov_run-1_cbv_tstat.nii.gz'.format(bindata_dir)
template = '/usr/share/mouse-brain-templates/dsurqec_40micron_masked.nii'
maps.stat3D(heatmap_image,
cut_coords=(0.0,-4.6,-3.4),
template=template,
save_as="_stat3D_heatmap.png",
show_plot=False,
threshold=4,
threshold_mesh=4,
)
def test_stat3D_overlay():
"""No explicit `threshold_mesh` specification, in order to test implicit behaviour."""
import samri.plotting.maps as maps
bindata_dir = '/usr/share/samri_bidsdata'
heatmap_image = '{}/l1/sub-4007/ses-ofM/sub-4007_ses-ofM_task-JogB_acq-EPIlowcov_run-1_cbv_tstat.nii.gz'.format(bindata_dir)
overlay = '/usr/share/mouse-brain-templates/dsurqec_200micron_roi-dr.nii'
template = '/usr/share/mouse-brain-templates/dsurqec_40micron_masked.nii'
maps.stat3D(heatmap_image,
cut_coords=(0.0,-4.6,-3.4),
overlays=[overlay],
template=template,
save_as="_stat3D_overlay.png",
show_plot=False,
threshold=4,
)
def plot_results(stat_map,results,hits = 3, template = "/usr/share/mouse-brain-atlases/ambmc2dsurqec_15micron_masked.obj",comparison='gene',vs = "expression",path_to_genes="usr/share/ABI-expression-data",percentile_threshold=94):
"""
Plots the input feature map as well as the top three scores
Parameters:
stat_map: str
path to the input feature map NIfTI file
results: list
sorted results of the similarity analyis
template: str
brain template .obj file to be used for 3D visualization
percentile_threshold: int, optional
percentile to determine the treshold used for displaying the feature maps
path_to_genes: str
path to folder of ABI-expression-library
"""
# TODO: put into stat3D or stat, to avoid loading the data twice threshold = fast_abs_percentile(stat_map)
dis = dict()
img_s = nibabel.load(stat_map)
img_data_s = img_s.get_fdata()
tresh_s = fast_abs_percentile(img_data_s[img_data_s >0],percentile=percentile_threshold)
print(tresh_s)
display_stat = maps.stat3D(stat_map,template="/usr/share/mouse-brain-atlases/dsurqec_200micron_masked.nii",save_as= '_stat.png',threshold=tresh_s,positive_only=True,figure_title=os.path.basename(stat_map))
dis["main"] = display_stat
for i in range(0,hits):
gene_name = results[i][0].split("_")[0] #TODO:this should work in both cases (also for connectivity??)
full_path_to_gene = results[i][1][1] #TODO what ??????
print("now plotting: ")
print(full_path_to_gene)
img = nibabel.load(full_path_to_gene)
img_data = img.get_fdata()
tresh = fast_abs_percentile(img_data[img_data > 0],percentile=98)
display = maps.stat3D(full_path_to_gene,template="/usr/share/mouse-brain-atlases/dsurqec_200micron_masked.nii",save_as=str(i) + '.png',threshold=tresh,positive_only=True,figure_title=gene_name)
dis[str(i)] = display
_plot(dis,stat_map,vs)
print(tresh_s)
print(tresh)
#TODO:sep.function?
return