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Fixed bug in data handling
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Houman.M_Dastjerdi committed Aug 6, 2024
1 parent 17764a9 commit 8bfc9a9
Showing 1 changed file with 93 additions and 34 deletions.
127 changes: 93 additions & 34 deletions piscat/Trajectory/data_handling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,64 @@ def protein_trajectories_list2dic(v_shape_list):
dic_all = {}

if type(v_shape_list) is list:
v_shape_list = np.asarray(v_shape_list)
for idx_, n_particle in enumerate(v_shape_list):
dic_particles = {}

if isinstance(n_particle, list):
dic_particles["intensity_horizontal"] = np.asarray(fixed_length(n_particle[0]))
dic_particles["intensity_vertical"] = np.asarray(fixed_length(n_particle[1]))
dic_particles["center_int"] = np.asarray(n_particle[2])
dic_particles["center_int_flow"] = np.asarray(n_particle[3])
dic_particles["frame_number"] = np.asarray(n_particle[4])
dic_particles["frame_number_flow"] = np.asarray(n_particle[5])
dic_particles["sigma"] = np.asarray(n_particle[6])
dic_particles["x_center"] = np.asarray(n_particle[7])
dic_particles["y_center"] = np.asarray(n_particle[8])
dic_particles["particle_ID"] = np.asarray(n_particle[9])
else:
dic_particles["intensity_horizontal"] = n_particle[0].ravel()
dic_particles["intensity_vertical"] = n_particle[1].ravel()
dic_particles["center_int"] = n_particle[2].ravel()
dic_particles["center_int_flow"] = n_particle[3].ravel()
dic_particles["frame_number"] = n_particle[4].ravel()
dic_particles["frame_number_flow"] = n_particle[5].ravel()
dic_particles["sigma"] = n_particle[6].ravel()
dic_particles["x_center"] = n_particle[7].ravel()
dic_particles["y_center"] = n_particle[8].ravel()
dic_particles["particle_ID"] = n_particle[9].ravel()

# Check the number of parameters to handle additional data
num_parameters = len(n_particle)

if num_parameters == 22:
if isinstance(n_particle, list):
dic_particles["fit_intensity"] = np.asarray(n_particle[10])
dic_particles["fit_x"] = np.asarray(n_particle[11])
dic_particles["fit_y"] = np.asarray(n_particle[12])
dic_particles["fit_X_sigma"] = np.asarray(n_particle[13])
dic_particles["fit_Y_sigma"] = np.asarray(n_particle[14])
dic_particles["fit_Bias"] = np.asarray(n_particle[15])
dic_particles["fit_intensity_error"] = np.asarray(n_particle[16])
dic_particles["fit_x_error"] = np.asarray(n_particle[17])
dic_particles["fit_y_error"] = np.asarray(n_particle[18])
dic_particles["fit_X_sigma_error"] = np.asarray(n_particle[19])
dic_particles["fit_Y_sigma_error"] = np.asarray(n_particle[20])
dic_particles["fit_Bias_error"] = np.asarray(n_particle[21])
else:
dic_particles["fit_intensity"] = n_particle[10].ravel()
dic_particles["fit_x"] = n_particle[11].ravel()
dic_particles["fit_y"] = n_particle[12].ravel()
dic_particles["fit_X_sigma"] = n_particle[13].ravel()
dic_particles["fit_Y_sigma"] = n_particle[14].ravel()
dic_particles["fit_Bias"] = n_particle[15].ravel()
dic_particles["fit_intensity_error"] = n_particle[16].ravel()
dic_particles["fit_x_error"] = n_particle[17].ravel()
dic_particles["fit_y_error"] = n_particle[18].ravel()
dic_particles["fit_X_sigma_error"] = n_particle[19].ravel()
dic_particles["fit_Y_sigma_error"] = n_particle[20].ravel()
dic_particles["fit_Bias_error"] = n_particle[21].ravel()
dic_all["#" + str(idx_)] = dic_particles
return dic_all

if type(v_shape_list) is np.ndarray:
for n_particle in range(v_shape_list.shape[0]):
Expand All @@ -65,52 +122,54 @@ def protein_trajectories_list2dic(v_shape_list):
dic_particles["center_int"] = np.asarray(v_shape_list[n_particle][2])
dic_particles["center_int_flow"] = np.asarray(v_shape_list[n_particle][3])
dic_particles["frame_number"] = np.asarray(v_shape_list[n_particle][4])
dic_particles["sigma"] = np.asarray(v_shape_list[n_particle][5])
dic_particles["x_center"] = np.asarray(v_shape_list[n_particle][6])
dic_particles["y_center"] = np.asarray(v_shape_list[n_particle][7])
dic_particles["particle_ID"] = np.asarray(v_shape_list[n_particle][8])
dic_particles["frame_number_flow"] = np.asarray(v_shape_list[n_particle][5])
dic_particles["sigma"] = np.asarray(v_shape_list[n_particle][6])
dic_particles["x_center"] = np.asarray(v_shape_list[n_particle][7])
dic_particles["y_center"] = np.asarray(v_shape_list[n_particle][8])
dic_particles["particle_ID"] = np.asarray(v_shape_list[n_particle][9])
else:
dic_particles["intensity_horizontal"] = v_shape_list[n_particle][0].ravel()
dic_particles["intensity_vertical"] = v_shape_list[n_particle][1].ravel()
dic_particles["center_int"] = v_shape_list[n_particle][2].ravel()
dic_particles["center_int_flow"] = v_shape_list[n_particle][3].ravel()
dic_particles["frame_number"] = v_shape_list[n_particle][4].ravel()
dic_particles["sigma"] = v_shape_list[n_particle][5].ravel()
dic_particles["x_center"] = v_shape_list[n_particle][6].ravel()
dic_particles["y_center"] = v_shape_list[n_particle][7].ravel()
dic_particles["particle_ID"] = v_shape_list[n_particle][8].ravel()
dic_particles["frame_number_flow"] = v_shape_list[n_particle][5].ravel()
dic_particles["sigma"] = v_shape_list[n_particle][6].ravel()
dic_particles["x_center"] = v_shape_list[n_particle][7].ravel()
dic_particles["y_center"] = v_shape_list[n_particle][8].ravel()
dic_particles["particle_ID"] = v_shape_list[n_particle][9].ravel()

num_parameters = len(v_shape_list[n_particle])

if num_parameters == 21:
if num_parameters == 22:
if type(v_shape_list[n_particle][0]) is list:
dic_particles["fit_intensity"] = np.asarray(v_shape_list[n_particle][9])
dic_particles["fit_x"] = np.asarray(v_shape_list[n_particle][10])
dic_particles["fit_y"] = np.asarray(v_shape_list[n_particle][11])
dic_particles["fit_X_sigma"] = np.asarray(v_shape_list[n_particle][12])
dic_particles["fit_Y_sigma"] = np.asarray(v_shape_list[n_particle][13])
dic_particles["fit_Bias"] = np.asarray(v_shape_list[n_particle][14])
dic_particles["fit_intensity"] = np.asarray(v_shape_list[n_particle][10])
dic_particles["fit_x"] = np.asarray(v_shape_list[n_particle][11])
dic_particles["fit_y"] = np.asarray(v_shape_list[n_particle][12])
dic_particles["fit_X_sigma"] = np.asarray(v_shape_list[n_particle][13])
dic_particles["fit_Y_sigma"] = np.asarray(v_shape_list[n_particle][14])
dic_particles["fit_Bias"] = np.asarray(v_shape_list[n_particle][15])
dic_particles["fit_intensity_error"] = np.asarray(
v_shape_list[n_particle][15]
v_shape_list[n_particle][16]
)
dic_particles["fit_x_error"] = np.asarray(v_shape_list[n_particle][16])
dic_particles["fit_y_error"] = np.asarray(v_shape_list[n_particle][17])
dic_particles["fit_X_sigma_error"] = np.asarray(v_shape_list[n_particle][18])
dic_particles["fit_Y_sigma_error"] = np.asarray(v_shape_list[n_particle][19])
dic_particles["fit_Bias_error"] = np.asarray(v_shape_list[n_particle][20])
dic_particles["fit_x_error"] = np.asarray(v_shape_list[n_particle][17])
dic_particles["fit_y_error"] = np.asarray(v_shape_list[n_particle][18])
dic_particles["fit_X_sigma_error"] = np.asarray(v_shape_list[n_particle][19])
dic_particles["fit_Y_sigma_error"] = np.asarray(v_shape_list[n_particle][20])
dic_particles["fit_Bias_error"] = np.asarray(v_shape_list[n_particle][21])

else:
dic_particles["fit_intensity"] = v_shape_list[n_particle][9].ravel()
dic_particles["fit_x"] = v_shape_list[n_particle][10].ravel()
dic_particles["fit_y"] = v_shape_list[n_particle][11].ravel()
dic_particles["fit_X_sigma"] = v_shape_list[n_particle][12].ravel()
dic_particles["fit_Y_sigma"] = v_shape_list[n_particle][13].ravel()
dic_particles["fit_Bias"] = v_shape_list[n_particle][14].ravel()
dic_particles["fit_intensity_error"] = v_shape_list[n_particle][15].ravel()
dic_particles["fit_x_error"] = v_shape_list[n_particle][16].ravel()
dic_particles["fit_y_error"] = v_shape_list[n_particle][17].ravel()
dic_particles["fit_X_sigma_error"] = v_shape_list[n_particle][18].ravel()
dic_particles["fit_Y_sigma_error"] = v_shape_list[n_particle][19].ravel()
dic_particles["fit_Bias_error"] = v_shape_list[n_particle][20].ravel()
dic_particles["fit_intensity"] = v_shape_list[n_particle][10].ravel()
dic_particles["fit_x"] = v_shape_list[n_particle][11].ravel()
dic_particles["fit_y"] = v_shape_list[n_particle][12].ravel()
dic_particles["fit_X_sigma"] = v_shape_list[n_particle][13].ravel()
dic_particles["fit_Y_sigma"] = v_shape_list[n_particle][14].ravel()
dic_particles["fit_Bias"] = v_shape_list[n_particle][15].ravel()
dic_particles["fit_intensity_error"] = v_shape_list[n_particle][16].ravel()
dic_particles["fit_x_error"] = v_shape_list[n_particle][17].ravel()
dic_particles["fit_y_error"] = v_shape_list[n_particle][18].ravel()
dic_particles["fit_X_sigma_error"] = v_shape_list[n_particle][19].ravel()
dic_particles["fit_Y_sigma_error"] = v_shape_list[n_particle][20].ravel()
dic_particles["fit_Bias_error"] = v_shape_list[n_particle][21].ravel()
dic_all["#" + str(n_particle)] = dic_particles
return dic_all

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