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CAN_Reverse_Engineering
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delim_whitespace preferred over delimiter argument

This commit is contained in:
Will Freeman 2020-04-22 15:02:10 -05:00
parent f0fdcd631e
commit 48e8ccec7d
1 changed files with 14 additions and 7 deletions
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21
Pipeline/PreProcessor.py
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@ -42,12 +42,15 @@ class PreProcessor:
self.data = read_csv(filename,
header=None,
names=['time', 'id', 'dlc', 'b0', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'b7'],
names=['time', 'id', 'dlc', 'b0', 'b1',
'b2', 'b3', 'b4', 'b5', 'b6', 'b7'],
skiprows=7,
delimiter='\t',
delim_whitespace=True,
converters=convert_dict,
index_col=0)
print(self.data)
a_timer.set_can_csv_to_df()
# sanity check output of the original data
@ -95,11 +98,13 @@ class PreProcessor:
continue
elif arb_id == 2024:
# This is the J1979 responses (ID 0x7DF & 0x8 = 0x7E8 = 2024)
j1979_data = self.data.loc[self.data['id'] == arb_id].copy()
j1979_data = self.data.loc[self.data['id'] == arb_id].copy(
)
j1979_data.drop('dlc', axis=1, inplace=True)
j1979_data.drop('id', axis=1, inplace=True)
a_timer.start_nested_function_time()
j1979_dictionary = self.generate_j1979_dictionary(j1979_data)
j1979_dictionary = self.generate_j1979_dictionary(
j1979_data)
a_timer.set_j1979_creation()
elif arb_id > 0:
a_timer.start_iteration_time()
@ -110,7 +115,7 @@ class PreProcessor:
# Check if the Arbitration ID always used the same DLC. If not, ignore it.
# We can effectively ignore this Arb ID by not adding it to the Arb ID dictionary.
if this_id.original_data['dlc'].nunique() is not 1:
if this_id.original_data['dlc'].nunique() != 1:
continue
this_id.dlc = this_id.original_data['dlc'].iloc[0]
this_id.original_data.drop('dlc', axis=1, inplace=True)
@ -121,14 +126,16 @@ class PreProcessor:
# not actually on the bus.
if this_id.dlc < 8:
for i in range(this_id.dlc, 8):
this_id.original_data.drop('b' + str(i), axis=1, inplace=True)
this_id.original_data.drop(
'b' + str(i), axis=1, inplace=True)
# Check if there are duplicate index values and correct them.
if not this_id.original_data.index.is_unique:
correction_mask = this_id.original_data.index.duplicated()
this_id.original_data = this_id.original_data[~correction_mask]
this_id.generate_binary_matrix_and_tang(a_timer, normalize_strategy)
this_id.generate_binary_matrix_and_tang(
a_timer, normalize_strategy)
this_id.analyze_transmission_frequency(time_convert=time_conversion,
ci_accuracy=freq_analysis_accuracy,
synchronous_threshold=freq_synchronous_threshold)