def testIsPositive(self): # - - - - - - - - - - - - - - - - - - - - - - - -
"""Test 'check_is_positive' function."""
assert (auxiliary.check_is_positive('TestArgument',1.) == None)
assert (auxiliary.check_is_positive('TestArgument',0.001) == None)
assert (auxiliary.check_is_positive('TestArgument',0.0000001) == None)
assert (auxiliary.check_is_positive('TestArgument',1) == None)
assert (auxiliary.check_is_positive('TestArgument',1.474) == None)
assert (auxiliary.check_is_positive('TestArgument',1236967) == None)
assert (auxiliary.check_is_positive('TestArgument',17676.474) == None)
def testIsPositive(self): # - - - - - - - - - - - - - - - - - - - - - - - -
"""Test 'check_is_positive' function."""
assert (auxiliary.check_is_positive('TestArgument',1.) == None)
assert (auxiliary.check_is_positive('TestArgument',0.001) == None)
assert (auxiliary.check_is_positive('TestArgument',0.0000001) == None)
assert (auxiliary.check_is_positive('TestArgument',1) == None)
assert (auxiliary.check_is_positive('TestArgument',1.474) == None)
assert (auxiliary.check_is_positive('TestArgument',1236967) == None)
assert (auxiliary.check_is_positive('TestArgument',17676.474) == None)
def testIsPositive(
self): # - - - - - - - - - - - - - - - - - - - - - - - -
"""Test 'check_is_positive' function."""
assert auxiliary.check_is_positive("TestArgument", 1.0)
assert auxiliary.check_is_positive("TestArgument", 0.001)
assert auxiliary.check_is_positive("TestArgument", 0.0000001)
assert auxiliary.check_is_positive("TestArgument", 1)
assert auxiliary.check_is_positive("TestArgument", 1.474)
assert auxiliary.check_is_positive("TestArgument", 1236967)
assert auxiliary.check_is_positive("TestArgument", 17676.474)
def GenerateHistogram(w_vec_dict, bin_width, file_name=None, match_sets=None):
"""Print and/or save a histogram of the weight vectors stored in the given
dictionary, and according to the match sets (if given).
The histogram is rotated 90 degrees clockwise, i.e. up to down instead of
left to right.
This function sums up the number of weight vectors with a matching weight
in a given bin (according to the given bin width).
If given, the match sets must be a tuple containing three sets, the first
being a set with matches, the second with non-matches, and the third with
possible matches, as generated by classifiers in the classification.py
Febrl module.
For each bin, the number of weight vectors in this bin is printed as well,
and if the match sets are given the number of matches, non-matches and
possible matches in this bin.
If a file name is given, the output will be written into this text file.
This function returns a list of containing the histogram as text strings.
"""
MAX_HISTO_WIDTH = 80 # maximum width in characters
auxiliary.check_is_dictionary('w_vec_dict', w_vec_dict)
auxiliary.check_is_number('bin_width', bin_width)
auxiliary.check_is_positive('bin_width', bin_width)
if (file_name != None):
auxiliary.check_is_string('file_name', file_name)
if (match_sets != None):
auxiliary.check_is_tuple('match_sets', match_sets)
if (len(match_sets) != 3):
logging.exception('Match sets must be a tuple containing three sets.')
raise Exception
auxiliary.check_is_set('match_sets[0]', match_sets[0])
auxiliary.check_is_set('match_sets[1]', match_sets[1])
auxiliary.check_is_set('match_sets[2]', match_sets[2])
if (len(w_vec_dict) != (len(match_sets[0]) + len(match_sets[1]) + \
len(match_sets[2]))):
logging.exception('Lengths of weight vector dictionary differs from' + \
'summed lengths of match sets.')
raise Exception
# Check if weight vector dictionary is empty, if so return empty list
#
if (w_vec_dict == {}):
logging.warn('Empty weight vector dictionary given for histogram ' + \
'generation')
return []
# Get a random vector dictionary element to get dimensionality of vectors
#
(rec_id_tuple, w_vec) = w_vec_dict.popitem()
v_dim = len(w_vec)
w_vec_dict[rec_id_tuple] = w_vec # Put back in
histo_dict = {} # A combined histogram dictionary
if (match_sets != None): # Also matches, non-matches and possible matches
match_histo_dict = {}
non_match_histo_dict = {}
poss_match_histo_dict = {}
max_bin_w_count = -1 # Maximal count for one binned weight entry
# Loop over weight vectors - - - - - - - - - - - - - - - - - - - - - - - - -
#
for (rec_id_tuple, w_vec) in w_vec_dict.iteritems():
w_sum = sum(w_vec) # Sum all weight vector elements
binned_w = w_sum - (w_sum % bin_width)
binned_w_count = histo_dict.get(binned_w,0) + 1 # Increase count by one
histo_dict[binned_w] = binned_w_count
if (binned_w_count > max_bin_w_count): # Check if this is new maximum count
max_bin_w_count = binned_w_count
if (match_sets != None):
if (rec_id_tuple in match_sets[0]):
binned_w_count = match_histo_dict.get(binned_w,0) + 1
match_histo_dict[binned_w] = binned_w_count
elif (rec_id_tuple in match_sets[1]):
binned_w_count = non_match_histo_dict.get(binned_w,0) + 1
non_match_histo_dict[binned_w] = binned_w_count
else: # A possible match
binned_w_count = poss_match_histo_dict.get(binned_w,0) + 1
poss_match_histo_dict[binned_w] = binned_w_count
# Sort histogram according to X axis values - - - - - - - - - - - - - - - - -
#
x_vals = histo_dict.keys()
x_vals.sort()
assert sum(histo_dict.values()) == len(w_vec_dict)
if (match_sets == None): # Can use 68 characters for histogram
scale_factor_y = float(MAX_HISTO_WIDTH-19) / max_bin_w_count
elif (len(poss_match_histo_dict) == 0): # No possible matches
scale_factor_y = float(MAX_HISTO_WIDTH-30) / max_bin_w_count
else: # All three set non-empty
scale_factor_y = float(MAX_HISTO_WIDTH-41) / max_bin_w_count
# Generate the histogram as a list of strings - - - - - - - - - - - - - - - -
#
histo_list = []
histo_list.append('Weight histogram:')
histo_list.append('-----------------')
if (match_sets == None):
histo_list.append(' Counts | w_sum |')
histo_list.append('-------------------')
elif (len(poss_match_histo_dict) == 0): # No possible matches
histo_list.append(' Counts |')
histo_list.append(' Match | Non-Match| w_sum |')
histo_list.append('------------------------------')
else:
histo_list.append(' Counts |')
histo_list.append(' Match | Non-Match|Poss-Match| w_sum |')
histo_list.append('-----------------------------------------')
for x_val in x_vals:
this_count = histo_dict[x_val]
if (match_sets == None):
line_str = '%9d | %5.2f |' % (this_count, x_val)
elif (len(poss_match_histo_dict) == 0): # No possible matches
this_match_count = match_histo_dict.get(x_val, 0)
this_non_match_count = non_match_histo_dict.get(x_val, 0)
line_str = '%9d |%9d | %5.2f |' % (this_match_count,
this_non_match_count, x_val)
else:
this_match_count = match_histo_dict.get(x_val, 0)
this_non_match_count = non_match_histo_dict.get(x_val, 0)
this_poss_match_count = poss_match_histo_dict.get(x_val, 0)
line_str = '%9d |%9d |%9d | %5.2f |' % (this_match_count,
this_non_match_count,
this_poss_match_count, x_val)
line_str += '*'*int(this_count*scale_factor_y)
histo_list.append(line_str)
histo_list.append('')
# If a file name is given open it for writing - - - - - - - - - - - - - - - -
#
if (file_name != None):
try:
f = open(file_name, 'w')
except:
logging.exception('Cannot open file "%s" for writing' % (str(file_name)))
raise IOError
for line in histo_list:
f.write(line + os.linesep)
f.close()
logging.info('Histogram written to file: %s' % (file_name))
if (match_sets != None):
print match_histo_dict.items()
print non_match_histo_dict.items()
return histo_list
def GenerateHistogram(w_vec_dict, bin_width, file_name=None, match_sets=None):
"""Print and/or save a histogram of the weight vectors stored in the given
dictionary, and according to the match sets (if given).
The histogram is rotated 90 degrees clockwise, i.e. up to down instead of
left to right.
This function sums up the number of weight vectors with a matching weight
in a given bin (according to the given bin width).
If given, the match sets must be a tuple containing three sets, the first
being a set with matches, the second with non-matches, and the third with
possible matches, as generated by classifiers in the classification.py
Febrl module.
For each bin, the number of weight vectors in this bin is printed as well,
and if the match sets are given the number of matches, non-matches and
possible matches in this bin.
If a file name is given, the output will be written into this text file.
This function returns a list of containing the histogram as text strings.
"""
MAX_HISTO_WIDTH = 80 # maximum width in characters
auxiliary.check_is_dictionary('w_vec_dict', w_vec_dict)
auxiliary.check_is_number('bin_width', bin_width)
auxiliary.check_is_positive('bin_width', bin_width)
if (file_name != None):
auxiliary.check_is_string('file_name', file_name)
if (match_sets != None):
auxiliary.check_is_tuple('match_sets', match_sets)
if (len(match_sets) != 3):
logging.exception(
'Match sets must be a tuple containing three sets.')
raise Exception
auxiliary.check_is_set('match_sets[0]', match_sets[0])
auxiliary.check_is_set('match_sets[1]', match_sets[1])
auxiliary.check_is_set('match_sets[2]', match_sets[2])
if (len(w_vec_dict) != (len(match_sets[0]) + len(match_sets[1]) + \
len(match_sets[2]))):
logging.exception('Lengths of weight vector dictionary differs from' + \
'summed lengths of match sets.')
raise Exception
# Check if weight vector dictionary is empty, if so return empty list
#
if (w_vec_dict == {}):
logging.warn('Empty weight vector dictionary given for histogram ' + \
'generation')
return []
# Get a random vector dictionary element to get dimensionality of vectors
#
(rec_id_tuple, w_vec) = w_vec_dict.popitem()
v_dim = len(w_vec)
w_vec_dict[rec_id_tuple] = w_vec # Put back in
histo_dict = {} # A combined histogram dictionary
if (match_sets != None): # Also matches, non-matches and possible matches
match_histo_dict = {}
non_match_histo_dict = {}
poss_match_histo_dict = {}
max_bin_w_count = -1 # Maximal count for one binned weight entry
# Loop over weight vectors - - - - - - - - - - - - - - - - - - - - - - - - -
#
for (rec_id_tuple, w_vec) in w_vec_dict.iteritems():
w_sum = sum(w_vec) # Sum all weight vector elements
binned_w = w_sum - (w_sum % bin_width)
binned_w_count = histo_dict.get(binned_w,
0) + 1 # Increase count by one
histo_dict[binned_w] = binned_w_count
if (binned_w_count >
max_bin_w_count): # Check if this is new maximum count
max_bin_w_count = binned_w_count
if (match_sets != None):
if (rec_id_tuple in match_sets[0]):
binned_w_count = match_histo_dict.get(binned_w, 0) + 1
match_histo_dict[binned_w] = binned_w_count
elif (rec_id_tuple in match_sets[1]):
binned_w_count = non_match_histo_dict.get(binned_w, 0) + 1
non_match_histo_dict[binned_w] = binned_w_count
else: # A possible match
binned_w_count = poss_match_histo_dict.get(binned_w, 0) + 1
poss_match_histo_dict[binned_w] = binned_w_count
# Sort histogram according to X axis values - - - - - - - - - - - - - - - - -
#
x_vals = histo_dict.keys()
x_vals.sort()
assert sum(histo_dict.values()) == len(w_vec_dict)
if (match_sets == None): # Can use 68 characters for histogram
scale_factor_y = float(MAX_HISTO_WIDTH - 19) / max_bin_w_count
elif (len(poss_match_histo_dict) == 0): # No possible matches
scale_factor_y = float(MAX_HISTO_WIDTH - 30) / max_bin_w_count
else: # All three set non-empty
scale_factor_y = float(MAX_HISTO_WIDTH - 41) / max_bin_w_count
# Generate the histogram as a list of strings - - - - - - - - - - - - - - - -
#
histo_list = []
histo_list.append('Weight histogram:')
histo_list.append('-----------------')
if (match_sets == None):
histo_list.append(' Counts | w_sum |')
histo_list.append('-------------------')
elif (len(poss_match_histo_dict) == 0): # No possible matches
histo_list.append(' Counts |')
histo_list.append(' Match | Non-Match| w_sum |')
histo_list.append('------------------------------')
else:
histo_list.append(' Counts |')
histo_list.append(' Match | Non-Match|Poss-Match| w_sum |')
histo_list.append('-----------------------------------------')
for x_val in x_vals:
this_count = histo_dict[x_val]
if (match_sets == None):
line_str = '%9d | %5.2f |' % (this_count, x_val)
elif (len(poss_match_histo_dict) == 0): # No possible matches
this_match_count = match_histo_dict.get(x_val, 0)
this_non_match_count = non_match_histo_dict.get(x_val, 0)
line_str = '%9d |%9d | %5.2f |' % (this_match_count,
this_non_match_count, x_val)
else:
this_match_count = match_histo_dict.get(x_val, 0)
this_non_match_count = non_match_histo_dict.get(x_val, 0)
this_poss_match_count = poss_match_histo_dict.get(x_val, 0)
line_str = '%9d |%9d |%9d | %5.2f |' % (
this_match_count, this_non_match_count, this_poss_match_count,
x_val)
line_str += '*' * int(this_count * scale_factor_y)
histo_list.append(line_str)
histo_list.append('')
# If a file name is given open it for writing - - - - - - - - - - - - - - - -
#
if (file_name != None):
try:
f = open(file_name, 'w')
except:
logging.exception('Cannot open file "%s" for writing' %
(str(file_name)))
raise IOError
for line in histo_list:
f.write(line + os.linesep)
f.close()
logging.info('Histogram written to file: %s' % (file_name))
if (match_sets != None):
print match_histo_dict.items()
print non_match_histo_dict.items()
return histo_list