def analyze_allometry_slm(output_dir, log_file, slm_handling, slm, args):
curves_processor = common.get_processor(output_dir, log_file, args.verbose,
False)
curves_processor.preprocess_curves(slm, True)
curves_processor.analyze_allometry(output_dir,
output_dir,
slm_handling=slm_handling)
def compute_means(slm, output_dir, log_file, slm_handling, args):
curves_processor = common.get_processor(output_dir, log_file, args.verbose)
logging.info('Preprocess curves')
curves_processor.preprocess_curves(slm, True)
logging.info('Analyze variability')
curves_processor.analyze_variability(output_dir,
output_dir,
slm_handling=slm_handling)
def generate_loading_visualization(input_dir, output_dir, log_file):
curves_processor = common.get_processor(input_dir, log_file)
common.mkdir_if_not_exist(output_dir)
for i in range(curves_processor.get_groups_count() - 1):
curves_processor.visualize_loadings(input_dir,
output_dir,
opts=get_vis_opts(
output_dir, [0.03, 0.1], i))
def generate_means_visualization(input_dir, output_dir, log_file, args):
curves_processor = common.get_processor(input_dir, log_file)
common.mkdir_if_not_exist(output_dir)
logging.info('Visualize all means')
curves_processor.visualize_means(input_dir,
opts=get_vis_opts(output_dir, 0.03, None))
groups_count = curves_processor.get_groups_count()
females_shift = int(groups_count / 2)
logging.info('Visualize group mean diffs to all mean')
for i in range(groups_count):
curves_processor.visualize_mean_difference(
input_dir,
opts=get_vis_opts(output_dir, [0.03, 0.10], [[groups_count, i]],
groups_count))
logging.info('Visualize subsequent means diffs')
for sex_name, sex_shift in dict(male=0, female=females_shift).items():
logging.info('Visualize subsequent means diffs for %s' % sex_name)
for i in range(sex_shift, sex_shift + females_shift - 1):
curves_processor.visualize_mean_difference(
input_dir,
opts=get_vis_opts(output_dir, [0.03, 0.10], [[i, i + 1]],
groups_count))
logging.info('Visualize 0-3, 3-6, 0-6')
for sex_shift in (0, females_shift):
for groups in ([0, 3], [3, 6], [0, 6]):
curves_processor.visualize_mean_difference(
input_dir,
opts=get_vis_opts(
output_dir, [0.03, 0.10],
[[sex_shift + groups[0], sex_shift + groups[1]]]))
logging.info('Visualize sex diffs for 3, 5')
for group in (3, 5):
curves_processor.visualize_mean_difference(
input_dir,
opts=get_vis_opts(output_dir, [0.03, 0.10],
[[group, females_shift + group]]))
def analyze_io_error_slm(slm, data_dir, output_dir, log_file):
curves_processor = common.get_processor(data_dir, log_file)
curves_processor.preprocess_curves(slm, True)
curves_processor.analyze_io_error(data_dir,
common.mkdir_if_not_exist(output_dir))
def compute_variability(slm, output_dir, log_file, slm_handling):
curves_processor = common.get_processor(output_dir, log_file)
curves_processor.preprocess_curves(slm, True)
curves_processor.analyze_variability(output_dir,
output_dir,
slm_handling=slm_handling)
#!/usr/bin/python3
import os
from projects.tibiacurve import common
from base import rscriptsupport
OUTPUT_DIR = os.path.join(common.TARGET_ROOT,
'TIBIA/CURVATURE/results/length_analysis')
OUTPUT_LOG = 'output.txt'
curves_processor = common.get_processor(OUTPUT_DIR, OUTPUT_LOG)
curves, names = curves_processor.load_all_curves(None)
curves_lengths = curves_processor.measure_length(curves)
rscript = rscriptsupport.RScripInterface(OUTPUT_DIR)
rscript.write_csv('curves_lengths.csv', curves_lengths)
curves_processor.length_analysis(OUTPUT_DIR)