# -*- coding: utf-8 -*-
"""
Created on Tue Jun 5 10:50:24 2018
@author: thomas
"""
import glob
from complexity import complexity, to_table
if __name__ == "__main__":
dir_shapes = ".\\shapes\\*.shp"
dir_img = ".\\images\\*.png"
shapes = glob.glob(dir_shapes)
images = glob.glob(dir_img)
coeff_ampl, coeff_conv = 0.8, 0.2
#Export to latex
filename = "complexity.tex"
tablefmt = "latex_raw"
str_img = "\includegraphics[width=1cm]{{figures/{}.png}}"
gdf = complexity(shapes, images, coeff_ampl, coeff_conv, str_img)
to_table(gdf, tablefmt, filename, str_img)
#Export to html
filename = "complexity.html"
tablefmt = "html"
str_img = '<img src=".//images//{}.png" style="width:10%;">'
to_table(gdf, tablefmt, filename, str_img)
def test_complexity(self): #test for complexity
word8 = 'this text is simple and short'
self.assertEqual(complexity.complexity(word8), 0.0)
word9 = 'whether longer sentences or more words indicate greater complexity'
self.assertEqual(complexity.complexity(word9), 0.1)
vprint( verbose, "[-] Sorry, time budget exceeded, skipping this task")
execution_success = False
continue
# ========= Creating a model ==========
vprint( verbose, "======== Creating model ==========")
training_data = D.load_training_data()
complexity_value = {}
for mid in D.model_ids:
if time_exceeded:
complexity_value[mid] = 'EXCEEDED'
continue
tf.keras.backend.clear_session()
model = D.load_model(mid)
measure_val = complexity(model, training_data)
try:
measure_val = float(measure_val)
except:
raise TypeError('Measure should be a scalar float or numpy float but got type: {}'.format(type(measure_val)))
complexity_value[mid] = measure_val
time_left_over = time_budget - time.time() + start
if time_left_over <= 0:
time_exceeded = True
if verbose:
print(complexity_value)
if time_exceeded:
vprint(verbose, "[+] Time exceeded: time limit is {} but program has run for {}".format(time_budget, time.time() - start))
else:
# ========= Creating a model ==========
vprint(verbose, "======== Creating model ==========")
training_data = D.load_training_data()
complexity_value = {}
for mid in D.model_ids:
if time_exceeded:
complexity_value[mid] = 'EXCEEDED'
continue
tf.keras.backend.clear_session()
model = D.load_model(mid)
if should_pass_submission_dir:
measure_val = complexity(model,
training_data,
program_dir=submission_dir)
else:
measure_val = complexity(model, training_data)
try:
measure_val = float(measure_val)
except:
print('Incorrect measure data type!')
raise TypeError(
'Measure should be a scalar float or numpy float but got type: {}'
.format(type(measure_val)))
complexity_value[mid] = measure_val
time_left_over = time_budget - time.time() + start
if time_left_over <= 0:
def complexity(self, data):
self.complexity = complexity.complexity(data)