Reorganize numeric noise detection logic (bad9e0e1) · Commits · Giacomo Mulas / NP_TMcode

src/scripts/pycompare.py

+55 −32

Original line number	Diff line number	Diff line
		@@ -230,7 +230,7 @@ def compare_lines(f_line, c_line, config, line_num=0, num_len=4, log_file=None):
		if (len(severities) > 0):
		if (severities[-1] == 0):
		log_line = (
		log_line + c_groups[-1] + c_line[c_ends[-1]:len(c_line) - 2]
		log_line + c_groups[-1] + c_line[c_ends[-1]:len(c_line) - 1]
		)
		elif (severities[-1] == 1):
		log_line = (
		@@ -291,50 +291,73 @@ def compare_lines(f_line, c_line, config, line_num=0, num_len=4, log_file=None):
		# \returns result: `array(int)` An array of severity codes ordered as the
		# input numeric values.
		def mismatch_severities(str_f_values, str_c_values, config):
		result = []
		if len(str_f_values) == len(str_c_values):
		result = [0 for ri in range(len(str_f_values))]
		f_values = []
		c_values = []
		# Convert numeric strings to numbers
		for i in range(len(str_f_values)):
		if (str_f_values[i] != str_c_values[i]):
		# Add the exponent marker if it is missing
		temp_str_value = str_f_values[i][1:]
		split_temp = temp_str_value.split('-')
		if len(split_temp) > 1:
		if (split_temp[0][-1] != 'E'):
		str_f_values[i] = str_f_values[i][0] + split_temp[0] + "E-" + split_temp[1]
		f_values.append(float(str_f_values[i]))
		temp_str_value = str_c_values[i][1:]
		split_temp = temp_str_value.split('-')
		if len(split_temp) > 1:
		if (split_temp[0][-1] != 'E'):
		str_c_values[i] = str_c_values[i][0] + split_temp[0] + "E-" + split_temp[1]
		c_values.append(float(str_c_values[i]))
		# End of missing exponent marker correction
		f_values = [float(str_f_values[j]) for j in range(len(str_f_values))]
		c_values = [float(str_c_values[j]) for j in range(len(str_c_values))]
		if (len(f_values) != len(c_values)): return []
		f_log_values = [0.0 for j in range(len(f_values))]
		c_log_values = [0.0 for j in range(len(c_values))]
		# End string to number conversion
		# Evaluate the maximum scale
		max_f_log = -1.0e12
		max_c_log = -1.0e12
		min_f_log = 1.0e12
		min_c_log = 1.0e12
		for j in range(len(f_values)) :
		if f_values[j] < 0.0: f_values[j] *= -1.0
		if c_values[j] < 0.0: c_values[j] *= -1.0
		f_log_values[j] = log10(f_values[j]) if f_values[j] > 0.0 else -999
		c_log_values[j] = log10(c_values[j]) if c_values[j] > 0.0 else -999
		if (f_log_values[j] > max_f_log): max_f_log = f_log_values[j]
		if (c_log_values[j] > max_c_log): max_c_log = c_log_values[j]
		if (f_log_values[j] < min_f_log): min_f_log = f_log_values[j]
		if (c_log_values[j] < min_c_log): min_c_log = c_log_values[j]
		if (c_log_values[i] < max_c_log - 5.0 and f_log_values[i] < max_f_log - 5.0):
		result[i] = 1
		else:
		warning_scale = 10.0**(int(max_f_log - f_log_values[i]))
		difference = c_values[i] - f_values[i]
		fractional = 1.0
		for si in range(len(f_values)):
		if (f_values[i] != 0):
		sign = 1.0 if f_values[i] > 0.0 else -1.0
		log_f_value = log10(sign * f_values[i])
		if (log_f_value > max_f_log): max_f_log = log_f_value
		if (c_values[i] != 0):
		sign = 1.0 if c_values[i] > 0.0 else -1.0
		log_c_value = log10(sign * c_values[i])
		if (log_c_value > max_c_log): max_c_log = log_c_value
		if (max_f_log == -1.0e12): max_f_log = 0.0
		if (max_c_log == -1.0e12): max_c_log = 0.0
		# End of maximum scale evaluation
		# Compare the numbers
		for i in range(len(f_values)):
		if (f_values[i] != c_values[i]):
		if (f_values[i] != 0.0):
		fractional = difference / f_values[i]
		sign = 1.0 if f_values[i] > 0.0 else -1.0
		log_f_value = log10(sign * f_values[i])
		if (log_f_value > max_f_log - 5.0):
		scale = 10.0**(log_f_value - max_f_log)
		fractional = scale * (f_values[i] - c_values[i]) / f_values[i]
		if (fractional < 0.0): fractional *= -1.0
		if (fractional < warning_scale * config['warning_threshold']): result[i] = 2
		else: result[i] = 3
		if (fractional <= config['warning_threshold']):
		result[i] = 2
		else:
		result[i] = 3
		else:
		result[i] = 1
		else: # f_values[i] == 0 and c_values[i] != 0
		sign = 1.0 if c_values[i] > 0.0 else -1.0
		log_c_value = log10(sign * c_values[i])
		if (log_c_value > max_c_log - 5.0):
		scale = 10.0**(log_c_value - max_c_log)
		fractional = scale * (c_values[i] - f_values[i]) / c_values[i]
		if (fractional < 0.0): fractional *= -1.0
		if (fractional <= config['warning_threshold']):
		result[i] = 2
		else:
		result[i] = 3
		else:
		result[i] = 1
		# End number comparison
		return result

		## \brief Parse the command line arguments.