def compare_pca_results():
original = CSVReader(pca_mask_folder, "results-original.csv")
results = CSVReader(pca_mask_folder, "results-mask.csv")
csv_writer = CSVWriter(pca_mask_folder, "results-merge.csv")
assert (original.total_lines == results.total_lines)
while original.continue_reading:
original_line = original.read_line()
results_line = results.read_line()
coder_name = original_line[3]
if coder_name in ["Coder", "CoderBase"]:
# assert(original_line == results_line)
csv_writer.write_row(parse_line(original_line))
else:
if len(original_line[4]) > 0: # algorithm params line
original_line, results_line = write_params_line(
csv_writer, original_line, results_line)
original_line = parse_line(original_line)
results_line = parse_mask_line(results_line)
# if original_line == results_line:
# continue
csv_writer.write_row(['O'] + original_line[1:] + ['O'])
csv_writer.write_row(['M'] + results_line[1:] + ['M'])
diff = []
for i in range(7, len(original_line)):
original_value, results_value = original_line[i], results_line[
i]
if i % 2 == 0:
# floats (percentages)
# diff_value = results_value + ' - ' + original_value
diff_value = float(results_value) - float(original_value)
diff_value = diff_scenarios(diff_value)
else:
# integers (bits)
if original_value == results_value:
diff_value = '==='
else:
diff_value = c_int(results_value) - c_int(
original_value)
diff_value = '+++' + str(
diff_value) if diff_value > 0 else '---' + str(
diff_value)
diff.append(diff_value)
diff_line = original_line[:7] + diff
csv_writer.write_row(diff_line)
original.close()
results.close()
csv_writer.close()
def read_data(input_path, input_filename, column_index):
data = []
data = np.array(data)
csv_file = CSVReader(input_path, input_filename)
csv_file.goto_row(3)
column_name = csv_file.read_line()[column_index]
csv_file.goto_first_data_row()
while csv_file.continue_reading:
value = csv_file.read_line()[column_index]
data = np.append(data, float(value))
return [column_name, data]
def filter_dataset(original_path,
original_filename,
csv_writer,
algorithms_array,
print_header=False):
csv_reader = CSVReader(original_path, original_filename)
matching_algorithm = False
while csv_reader.continue_reading:
line = csv_reader.read_line()
filename, algorithm_name = line[1], line[3]
if len(algorithm_name) > 0:
if matching_algorithm and algorithm_name not in algorithms_array:
matching_algorithm = False
elif not matching_algorithm and algorithm_name in algorithms_array:
matching_algorithm = True
if line[0] == "Dataset":
if print_header:
csv_writer.write_row(line)
elif len(filename) > 0 or matching_algorithm:
csv_writer.write_row(line)
csv_reader.close()
def compare():
test_files_path = OSUtils.cpp_project_path() + "/test_files"
csv_reader_1 = CSVReader(OSUtils.datasets_csv_path() + "[1]irkis/",
"vwc_1202.dat.csv")
csv_reader_2 = CSVReader(test_files_path,
"vwc_1202.dat.csv-CoderSF-Decode.csv")
while csv_reader_1.continue_reading:
assert (
csv_reader_1.current_line_count == csv_reader_2.current_line_count)
current_line_count = csv_reader_1.current_line_count
line_1 = csv_reader_1.read_line()
line_2 = csv_reader_2.read_line()
compare_lines(line_1, line_2, current_line_count)
print "COMPARE SUCCESS!!"
csv_reader_1.close()
csv_reader_2.close()
class GzipResultsReader(object):
def __init__(self, path, filename):
self.input = CSVReader(path, filename)
def gzip_and_base_bits(self, dataset_name, filename, column_name):
self.input.goto_row(0)
self.__find_match(0, dataset_name)
self.__find_match(1, filename) # filename can be 'Global'
self.__find_match(2, column_name)
gzip_bits, base_bits = int(self.line[4]), int(float(self.line[5]))
return gzip_bits, base_bits
def __find_match(self, col_index, value):
# print col_index, value
while self.input.continue_reading:
line = self.input.read_line()
if line[col_index] == value:
self.line = line
return
raise KeyError('Reached EOF')
class ResultsReader(object):
def __init__(self, mode, mask_mode):
if mask_mode in ["NM", "M"]:
input_path, input_filename = ResultsPaths.get_path_and_filename(
mode, mask_mode)
else:
input_path, input_filename = mode, mask_mode
self.input_file = CSVReader(input_path, input_filename)
def read_line_no_count(self):
return self.input_file.read_line()
def __read_line(self):
self.line_count += 1
self.line = self.input_file.read_line()
return self.line
def __goto_file_start(self):
self.input_file.goto_row(0)
self.line = None
self.line_count = 0
def full_results(self):
self.__goto_file_start()
self.__read_line() # headers line
lines_array = []
while self.continue_reading():
self.__read_line()
lines_array.append(self.line)
return lines_array
def dataset_results(self,
dataset_name,
change_index=CSVConstants.INDEX_DATASET):
self.find_dataset(dataset_name)
return ResultsReader.add_until_change(self, change_index)
def filename_results(self,
dataset_name,
filename,
change_index=CSVConstants.INDEX_FILENAME):
self.find_filename_in_dataset(dataset_name, filename)
return ResultsReader.add_until_change(self, change_index)
def find_dataset(self, dataset_name):
self.__goto_file_start()
self.__find_next_line(CSVConstants.INDEX_DATASET, dataset_name, False)
def find_filename(self, filename):
self.__goto_file_start()
self.__find_next_line(CSVConstants.INDEX_FILENAME, filename, False)
def find_threshold(self, threshold):
# self.__goto_file_start()
self.__find_next_line(CSVConstants.INDEX_THRESHOLD, threshold, True)
def find_filename_in_dataset(self, dataset_name, filename):
self.find_dataset(dataset_name)
self.__find_next_line(CSVConstants.INDEX_FILENAME, filename, False)
def continue_reading(self):
return self.input_file.continue_reading
def __find_next_line(self, index, value, is_integer):
if self.line_count > 0 and ResultsReader.matching_line(
self.line, index, value, is_integer):
return True
while self.input_file.continue_reading:
self.__read_line()
if ResultsReader.matching_line(self.line, index, value,
is_integer):
return True
raise Exception("ERROR: __find_next_line")
@staticmethod
def matching_line(line, index, value, is_integer):
value_in_index = line[index]
if len(value_in_index) == 0:
return False
value_to_compare = int(
value_in_index) if is_integer else value_in_index
return value == value_to_compare
@staticmethod
def copy_until_change(results_reader, output_file, line_index):
first_line = True
while results_reader.continue_reading() and (first_line or len(
results_reader.line[line_index]) == 0):
output_file.write_row(results_reader.line)
results_reader.__read_line()
first_line = False
if not results_reader.continue_reading():
output_file.write_row(results_reader.line)
@staticmethod
def add_until_change(results_reader, line_index):
lines_array = []
first_line = True
while results_reader.continue_reading() and (first_line or len(
results_reader.line[line_index]) == 0):
lines_array.append(results_reader.line)
results_reader.__read_line()
first_line = False
if not results_reader.continue_reading():
lines_array.append(results_reader.line)
return lines_array
@staticmethod
def set_percentages(line, line_total):
assert (len(line) == len(line_total))
for index in range(len(line)):
if CSVConstants.is_percentage_index(index):
total, value = line_total[index - 1], line[index - 1]
percentage = MathUtils.calculate_percent(total, value)
line[index] = percentage
return line
@staticmethod
def convert_lines(lines):
return [ResultsReader.convert_line(line) for line in lines]
@staticmethod
def convert_line(line):
new_line = []
# 0 1 2 3 4 5 6
# Dataset, Filename, #rows, Coder, %, Error Threshold, Window Param
#
new_line.append(line[CSVConstants.INDEX_DATASET])
new_line.append(line[CSVConstants.INDEX_FILENAME])
no_rows = line[CSVConstants.INDEX_NO_ROWS]
new_line.append(
MathUtils.str_to_int(no_rows) if isinstance(no_rows, int) else '')
new_line.append(line[CSVConstants.INDEX_ALGORITHM]) # Coder
threshold = line[CSVConstants.INDEX_THRESHOLD]
new_line.append(int(threshold) if len(threshold) > 0 else None) # %
new_line.append('') # Error Threshold
window = line[CSVConstants.INDEX_WINDOW]
new_line.append(
int(window) if len(window) > 0 else None) # Window Param
# 7 8 9 10 11 12
# Size (B), CR (%), Delta - Size (data), Delta - Size (mask), Delta - Size (total), Delta - CR (%), ...
#
for index in range(CSVConstants.INDEX_TOTAL_SIZE, len(line)):
if CSVConstants.is_percentage_index(index):
value = line[index]
if value.count('.') > 1: # e.g. "1.145.49"
value = value.replace('.', '',
1) # "1.145.49" => "1145.49"
new_line.append(float(value))
else:
new_line.append(MathUtils.str_to_int(line[index]))
return new_line
import sys
sys.path.append('.')
from file_utils.csv_utils.csv_writer import CSVWriter
from file_utils.csv_utils.csv_reader import CSVReader
path = "/Users/pablocerve/Documents/FING/Proyecto/pc-tesis/dataset_parser/scripts/informe/results/3.1/06.2020/2-complete"
file = "results-mm3.csv"
new_file = "results-mm3-p.csv"
reader = CSVReader(path, file)
writer = CSVWriter(path, new_file)
while reader.continue_reading:
line = reader.read_line()
if "0" in line[4]:
line[4] = int(float(line[4]) * 100)
writer.write_row(line)
writer.close()
reader.close()
class CSVCompare:
def __init__(self, file1_path, file1_filename, file2_path, file2_filename):
self.file1 = CSVReader(file1_path, file1_filename)
self.file2 = CSVReader(file2_path, file2_filename)
self.file1_first_data_row = CSVReader.first_data_row(file1_path, file1_filename)
self.file2_first_data_row = CSVReader.first_data_row(file2_path, file2_filename)
assert(self.file1_first_data_row == self.file2_first_data_row)
#
# error_thresholds is an array with the the maximum difference between the original and the compressed values
# in a near-lossless compression schema.
# If error_thresholds is None then we consider a lossless compression schema.
#
# if abort is True then the comparison stops as soon as an error is found.
#
# Returns True iff there is no error.
#
def compare(self, error_thresholds=None, abort=True):
self.error_thresholds = self._check_error_thresholds(error_thresholds)
self.abort = abort
same_file = self._check_same_file()
self._print_result(same_file)
return same_file
####################################################################################################################
@classmethod
def _check_error_thresholds(cls, error_thresholds):
if error_thresholds is not None:
for error in error_thresholds:
assert(error == PandasTools.NO_DATA or (isinstance(error, int) and error >= 0))
return error_thresholds
def _get_threshold(self, col_index):
if self.error_thresholds is None:
return 0
error_thresholds_len = len(self.error_thresholds)
assert(col_index < error_thresholds_len)
return self.error_thresholds[col_index]
# else: # GAMPS coder
# data_columns_group_count = len(self.error_thresholds) - 1
# if data_columns_group_count == 1:
# index = 1
# else:
# index = col_index % data_columns_group_count
# index = data_columns_group_count if index == 0 else index
# return self.error_thresholds[index]
def _print_result(self, same_file):
if same_file:
print("SAME FILES!")
else:
print("DIFFERENT FILES!")
if self.error_thresholds is None:
print("Compared with all thresholds = 0.")
else:
print("Compared with thresholds = ", self.error_thresholds)
def _check_same_file(self):
same_file = True
continue_while = True
self.row_count = 0
while continue_while and self.file1.continue_reading and self.file2.continue_reading:
row1, row2 = self.file1.read_line(), self.file2.read_line()
if self.row_count < self.file1_first_data_row + 1:
same_file = self._compare_header_rows(row1, row2)
continue_while = same_file # if there is a mismatch in the header rows, exit the while
else:
same_row = self._compare_data_rows(row1, row2)
if not same_row:
same_file = False
# if there is a mismatch in the data rows, exit or not depending on the self.abort flag
if self.abort:
continue_while = False
self.row_count += 1
if self._only_one_file_ends():
same_file = False
return same_file
@classmethod
def _compare_header_rows(cls, row1, row2):
if row1 == row2:
return True
# the non-data rows must match exactly
print("Difference in the header rows")
print(row1)
print(row2)
return False
#
# Returns False iff:
# - the length of the rows does not match.
# OR
# - the error_threshold constraint does not hold.
#
def _compare_data_rows(self, row1, row2):
if len(row1) != len(row2):
print("len(row1) = %s != %s = len(row2)" % (len(row1), len(row2)))
return False
same_row = True
for col_index in range(len(row1)):
value1, value2 = row1[col_index], row2[col_index]
same_row_value = self._compare_values(value1, value2, col_index)
if not same_row_value:
same_row = False
self._print_idx_error(col_index, value1, value2)
return same_row
def _compare_values(self, value1, value2, col_index):
same_row_value = True
if value1 == PandasTools.NO_DATA or value2 == PandasTools.NO_DATA: # both values must be PandasTools.NO_DATA
if value1 != PandasTools.NO_DATA or value2 != PandasTools.NO_DATA:
same_row_value = False
else:
error = self._get_threshold(col_index)
# print(value1, value2)
assert(isinstance(error, int) and error >= 0)
if error == 0: # compare strings instead of int
if value1 != value2:
same_row_value = False
else:
# compare ints
abs_diff = abs(int(value1) - int(value2))
if abs_diff > error:
print('abs_diff', abs_diff, 'error_threshold', error)
same_row_value = False
return same_row_value
def _print_idx_error(self, col_index, value1, value2):
print("row_count = %s, col_index = %s, value1 = '%s', value2 = '%s'" % (self.row_count, col_index, value1, value2))
#
# Returns true iff one file has more rows than the other.
#
def _only_one_file_ends(self):
if not self.file1.continue_reading and self.file2.continue_reading:
print("file1 is shorter than file2")
return True
elif self.file1.continue_reading and not self.file2.continue_reading:
print("file2 is shorter than file1")
return True
return False