def process(self, value):
"""Returns minmax (tuple) for a number of samples after the first
level change has occurred, otherwise None"""
if self._level_change_time is not None:
if (get_time() - self._level_change_time) >= self._duration_in_sec:
return tuple(self._minmax)
if value > self._minmax[1]:
self._minmax[1] = value
elif value < self._minmax[0]:
self._minmax[0] = value
elif self._minmax[0] != value: # level change just occurred
self._level_change_time = get_time()
return self.process(value)
return None
def process(self, value):
"""Returns minmax (tuple) for a number of samples after the first
level change has occurred, otherwise None"""
if self._level_change_time is not None:
if (get_time() - self._level_change_time) >= self._duration_in_sec:
return tuple(self._minmax)
if value > self._minmax[1]:
self._minmax[1] = value
elif value < self._minmax[0]:
self._minmax[0] = value
elif self._minmax[0] != value: # level change just occurred
self._level_change_time = get_time()
return self.process(value)
return None
def profile_time(a_degree=4, b_degree=4, c_degree=4):
print(f'Profiling ASGarD\'s compute time for {PDE}...')
# The output sheet describing time data
time_sheet = TimeSheet()
# The function describing the time used for each level for every degree
f = Function(degree=2) # a quadratic function
# a list containing the terms of the function describing time used as a function of degree per level
level_terms = []
# Iterate over level and degrees for the PDE
for level in tqdm(LEVELS, desc=f'Total progress'):
for i, degree in enumerate(tqdm(DEGREES, leave=False, desc=f'Level {level}')):
seconds = []
for _ in range(3):
seconds.append(get_time(level, degree, PDE))
average_seconds = sum(seconds) / len(seconds)
# time as a function of degree per level
f.add_point(i, average_seconds)
time_sheet.add_seconds(level, degree, average_seconds)
# add to the list of the list of terms per level's time function
level_terms.append(f.as_terms())
# clear the current f to reuse for the next level's time function
f.clear()
# Functions describing the a, b, and c terms of the function describing seconds used
a = Function(degree=a_degree)
b = Function(degree=b_degree)
c = Function(degree=c_degree)
# Add the points for the a, b, and c functions
for i, terms in enumerate(level_terms):
a.add_point(i, terms[0])
b.add_point(i, terms[1])
c.add_point(i, terms[2])
return a, b, c, time_sheet
def is_sampling_for_minmax(self):
"""true true if currently sampling for minmax"""
return (self._level_change_time is not None) and \
(get_time() - self._level_change_time) < self._duration_in_sec
#print sort.check_sorted(list,False)
#
print '\ntesting and timing for a large array\n'
list_large = []
for i in range(5000):
list_large.append(random.randint(1, 100))
print 'size:5000, for the slower ones'
timer = timer.Timer(time.clock()) #initialize the timer
print 'bubble sort\n'
list = sort.bubble_sort(list_large[:])
assert sort.check_sorted(list)
timer.get_time(time.clock())
print ''
print 'insertion sort\n'
list = sort.insert_sort(list_large[:])
assert sort.check_sorted(list)
timer.get_time(time.clock())
print ''
print 'insertion sort fast\n'
list = sort.insert_sort_fast(list_large[:])
assert sort.check_sorted(list)
timer.get_time(time.clock())
print ''
print 'heap sort\n'
def is_sampling_for_minmax(self):
"""true true if currently sampling for minmax"""
return (self._level_change_time is not None) and \
(get_time() - self._level_change_time) < self._duration_in_sec
