def draw_heatmap_img(slide_score, patient_id, node_id, step):
cfg = init.config()
path_info = init.path_info()
gate = init.get_positive_gate()
if slide_score.shape[0] == 100:
if slide_score.shape[1] == 100:
return 0
if cfg.output_heatmap_mode == 1:
#draw raw_heatmap
file_name = gname.gen_raw_heatmap_img_name(patient_id, node_id, step)
dat_path = os.path.join(path_info.heatmap, file_name)
draw.drae_raw_heatmap(slide_score, dat_path)
#draw heatmap1
file_name = gname.gen_heatmap_img_name(patient_id, node_id, step, gate)
dat_path = os.path.join(path_info.heatmap, file_name)
draw.draw_heatmap(slide_score, gate, dat_path)
#heatmap
'''
file_name = gname.gen_heatmap_img_name(patient_id, node_id,step,cfg.positive_gate_map1)
dat_path = os.path.join(path_info.heatmap, file_name)
draw.draw_heatmap(slide_score, cfg.positive_gate_map1, dat_path)
file_name = gname.gen_heatmap_img_name(patient_id, node_id,step,cfg.positive_gate_map2)
dat_path = os.path.join(path_info.heatmap, file_name)
draw.draw_heatmap(slide_score, cfg.positive_gate_map2, dat_path)
'''
else:
print("skip output heatmap")
def get_slide_info_file_path():
cfg = init.config()
gate = init.get_positive_gate()
path_info = init.path_info()
file_name = "%s_%1.4lf.csv" % (cfg.slide_info_file, gate)
path_file = os.path.join(path_info.slide_info, file_name)
return path_file
def get_pnstage_file_path():
cfg = init.config()
path_info = init.path_info()
pnstage_file_name = "%s_%1.3lf.csv" % (cfg.result_csv_file,
init.get_positive_gate())
result_path = os.path.join(path_info.pns_info, pnstage_file_name)
return result_path
def write_pn_stage_kappa():
path_info = init.path_info()
stat_cfg = init.stat_config()
gate = init.get_positive_gate()
c17_gt_path = os.path.join(path_info.config, stat_cfg.c17_pnstage)
c17_eva_path = gname.get_pnstage_file_path()
kappa_score = eva.pnstage_kappa(c17_eva_path, c17_gt_path)
file_path = gname.get_pnstage_kappa_file_path()
result_pnstage_kappa = open(file_path, "ab+")
context_str = "%lf,%lf\n" % (gate, kappa_score)
result_pnstage_kappa.write(context_str)
result_pnstage_kappa.close()
def write_kappa_score(rate, kappa):
stat_cfg = init.stat_config()
#path_info = init.path_info()
#outs_path = os.path.join(path_info.outs,stat_cfg.info_file)
outs_path = gname.get_result_info_path()
fd_outs = open(outs_path, "ab+")
gate = init.get_positive_gate()
context = "Threshold:,%lf\n" % (gate)
context = context + "Kappa:,%1.5lf\n" % (kappa)
context = context + "\n\n"
context = context + "#,#,#,#,#,#,#,#,#,#,#,#,#,#\n"
fd_outs.write(context)
fd_outs.close()
outs_path = gname.get_kappa_file_path()
fd_outs = open(outs_path, "ab+")
context = "%1.4lf,%lf,%lf\n" % (gate, kappa, rate)
fd_outs.write(context)
fd_outs.close()
def get_VS_file_path():
path_info = init.path_info()
stat_cfg = init.stat_config()
file_name = "%s_%1.3lf.csv" % (stat_cfg.vs_file, init.get_positive_gate())
path_file = os.path.join(path_info.outs, file_name)
return path_file