#Visualization- need to modify
#extract coordinates from atlas
mniCoordsFile = open("../../Atlases/MNI_Gordon.txt", "rb")
coords = []
for line in mniCoordsFile.read().splitlines():
splitedLine = line.decode().split()
newCoord = []
for part in splitedLine:
if part != '':
newCoord.append(float(part))
coords.append(newCoord)
mniCoordsFile.close()
#Slice DMN
ticks = [0]
min_r = 0
#create a list of indexes to slice
listToSlice = []
network = "Default"
# The networkToIndexDic dictionary contains for each network the location (indexes) in the common matrix.
listToSlice = listToSlice + list(net_dic.dic[network])
ticks.append(ticks[-1] + len(net_dic.dic[network]))
#plot- only significant
vf.plotMatrix(df_corr_mat.values,
os.path.join(args.out_folder, "corr_mat.png"), [network],
"Different Values", ticks)
#Plot brain connectome if all coordinates exists for those networks
if (max(listToSlice) < len(coords)):
coords_sliced = [coords[i] for i in listToSlice]
vf.plotConnectome(df_corr_mat.values, coords_sliced, [network],
args.out_folder, "diff_ROIs", min_r)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--out_folder', required=True, type=str, help='output folder')
parser.add_argument('--mat', required=True, nargs='+', help='path to all matrices')
parser.add_argument('--out_name', default="sig_values", required=False, type=str, help='Name for output files')
args = parser.parse_args()
all_mat = []
for mat in args.mat:
mat_n = pd.read_excel(mat,index_col= 0).to_numpy()
all_mat.append(mat_n)
all_mat_mul = reduce((lambda x, y: x * y), all_mat)
print(all_mat_mul)
# df_mat1 = pd.read_excel(args.mat1,index_col= 0)
# df_mat2 = pd.read_excel(args.mat2,index_col= 0)
# #df_mat3 = pd.read_excel(args.mat3,index_col= 0)
# mat1 = df_mat1.notnull().to_numpy()
# mat2 = df_mat2.notnull().to_numpy()
# #mat3 = df_mat3.notnull().to_numpy()
# #mat1_mat2_mat3 = mat1*mat2*mat3
# mat1_mat2 = mat1*mat2
# print(mat1_mat2)
network = "Default"
ticks = [0]
ticks.append(ticks[-1] + len(net_dic.dic[network]))
vf.plotMatrix(all_mat_mul, os.path.join(args.out_folder,args.out_name + ".png"), [network], "Significant Values Two Matrices",ticks)
pd.DataFrame(all_mat_mul).to_excel(os.path.join(args.out_folder,args.out_name + ".xlsx"))
newCoord.append(float(part))
coords.append(newCoord)
mniCoordsFile.close()
#Slice DMN
ticks = [0]
min_r = 0
#create a list of indexes to slice
listToSlice = []
network = "Default"
# The networkToIndexDic dictionary contains for each network the location (indexes) in the common matrix.
listToSlice = listToSlice + list(net_dic.dic[network])
ticks.append(ticks[-1] + len(net_dic.dic[network]))
#plot- only significant
vf.plotMatrix(sig_values_mat_1.values,
args.out_folder + "/sig_values_mat_1.png", [network],
"Significant Values Matrix 1", ticks)
#Plot brain connectome if all coordinates exists for those networks
if (max(listToSlice) < len(coords)):
coords_sliced = [coords[i] for i in listToSlice]
vf.plotConnectome(sig_values_mat_1.values, coords_sliced, [network],
args.out_folder, "matrix1", min_r)
#plot- significant and effect size
vf.plotMatrix(
sig_and_es_mat_1.values,
args.out_folder + "/sig_mat_1_" + str(effect_size_thr) + ".png",
[network],
"Effect size > " + str(effect_size_thr) + " Values Matrix 1", ticks)
#Plot brain connectome if all coordinates exists for those networks
if (max(listToSlice) < len(coords)):
newCoord.append(float(part)) coords.append(newCoord) mniCoordsFile.close() #Slice DMN ticks = [0] min_r = 0 #create a list of indexes to slice listToSlice = [] network = "Default" # The networkToIndexDic dictionary contains for each network the location (indexes) in the common matrix. listToSlice = listToSlice + list(net_dic.dic[network]) ticks.append(ticks[-1] + len(net_dic.dic[network])) #plot- only significant vf.plotMatrix(df_mat1.values, out+ "/mat_1.png", [network], "Matrix 1",ticks) #Plot brain connectome if all coordinates exists for those networks if(max(listToSlice) < len(coords)): coords_sliced = [coords[i] for i in listToSlice] vf.plotConnectome(df_mat1.values, coords_sliced, [network], out, "matrix1", min_r) #plot- only significant vf.plotMatrix(df_mat2.values, out+ "/mat_2.png", [network], "Matrix 2",ticks) #Plot brain connectome if all coordinates exists for those networks if(max(listToSlice) < len(coords)): coords_sliced = [coords[i] for i in listToSlice] vf.plotConnectome(df_mat2.values, coords_sliced, [network], out, "matrix2", min_r) if(max(listToSlice) < len(coords)): coords_sliced = [coords[i] for i in listToSlice]