def generate_and_save_all_datasets():
for operator in config.operators_list():
for operand_digits in config.operand_digits_list():
op_dataset, carry_datasets = generate_datasets(
operand_digits, operator)
save_op_dataset(op_dataset, operand_digits, operator)
save_carry_datasets(carry_datasets, operand_digits, operator)
for operand_digits in config.operand_digits_list():
random_datasets = generate_random_datasets(operand_digits)
save_random_datasets(random_datasets, operand_digits)
def test_import_random_sampled_carry_datasets(n_samples=10):
'''
"To test the function `import_random_sampled_carry_datasets`"
'''
is_all_correct = True
for operand_digits in config.operand_digits_list():
for operator in config.operators_list():
carry_datasets = import_random_sampled_carry_datasets(
operand_digits, operator, n_samples)
for n_carries in carry_datasets.keys():
n_operations = carry_datasets[n_carries]['input'].shape[0]
for i_operation in range(n_operations):
operand1 = carry_datasets[n_carries]['input'][
i_operation, :operand_digits]
operand2 = carry_datasets[n_carries]['input'][
i_operation, operand_digits:]
result = carry_datasets[n_carries]['output'][
i_operation, :]
result_by_computing = operate_two_numbers(
operand1, operand2,
operator)[0] # Get the first element
is_equal = np.array_equal(result, result_by_computing)
if not is_equal:
print(operand1)
print(operand2)
print(result)
print(result_by_computing)
print('================')
is_all_correct = is_all_correct and is_equal
return is_all_correct
def test_func_add_two_numbers():
is_all_correct = True
for operand_digits in config.operand_digits_list():
# varying part
result_digits = get_result_digits(operand_digits, 'add')
for dec_op1 in range(2**operand_digits):
for dec_op2 in range(2**operand_digits):
# varying part
bin_result = get_str_bin(dec_op1 + dec_op2)
np_bin_result = get_np_bin(bin_result, result_digits)
np_bin_op1 = get_np_bin(get_str_bin(dec_op1), operand_digits)
np_bin_op2 = get_np_bin(get_str_bin(dec_op2), operand_digits)
np_bin_result_algo, _ = add_two_numbers(np_bin_op1, np_bin_op2)
is_equal = np.array_equal(np_bin_result, np_bin_result_algo)
is_all_correct = is_all_correct and is_equal
return is_all_correct
def test_multiply_symmetric_carries():
'''
Purpose : To test whether the number of carries while multipication is same for a * b and b * a.
Result : The number of carries is always same for a * b and b * a.
'''
is_all_symmetric = True
for operand_digits in config.operand_digits_list():
for int_dec_operand1 in range(2**operand_digits):
for int_dec_operand2 in range(2**operand_digits):
operand1 = get_np_bin(get_str_bin(int_dec_operand1),
operand_digits)
operand2 = get_np_bin(get_str_bin(int_dec_operand2),
operand_digits)
result1, _ = multiply_two_numbers(operand1, operand2)
result2, _ = multiply_two_numbers(operand2, operand1)
is_equal = np.array_equal(result1, result2)
is_all_symmetric = is_all_symmetric and is_equal
return is_all_symmetric
def plot_carry_dataset_statistics(mode='save', file_format='svg'):
df_carry_ds_stat = pd.read_csv(get_carry_ds_stat_path())
df_carry_ds_stat = df_carry_ds_stat[[
'operator', 'operand digits', 'carries', 'carry percentage'
]]
for operand_digits in config.operand_digits_list():
plt.title(
'Percentage of operations by required carries ({}-digit operand)'.
format(operand_digits))
plt.xlabel('Carries')
plt.ylabel('Percentage (%)')
plt.grid(axis='y')
plt.yticks(np.arange(0, 101, step=10))
plt.ylim(0, 101)
for operator in config.operators_list():
if operator == 'modulo':
break
if operator == 'divide':
operator_label = 'divide/modulo'
else:
operator_label = operator
df = df_carry_ds_stat.loc[
(df_carry_ds_stat['operator'] == operator)
& (df_carry_ds_stat['operand digits'] == operand_digits)]
df = df[['carries', 'carry percentage']]
plt.plot(df['carries'],
df['carry percentage'],
':o',
label=operator_label)
#plt.bar(df['carries'], df['carry percentage'], label=operator)
plt.legend()
if mode == 'show':
plt.show()
if mode == 'save':
create_dir(config.dir_plot_fig())
plot_fig_path = '{}/carry_dataset_statistics_{}-digit_operand.{}'.format(
config.dir_plot_fig(), operand_digits, file_format)
plt.savefig(plot_fig_path)
print('{} saved!'.format(plot_fig_path))
plt.clf()
def test_func_multiply_two_numbers():
is_all_correct = True
for operand_digits in config.operand_digits_list():
# varying part
result_digits = get_result_digits(operand_digits, 'multiply')
for int_dec_operand1 in range(2**operand_digits):
for int_dec_operand2 in range(2**operand_digits):
# varying part
bin_result = get_str_bin(int_dec_operand1 * int_dec_operand2)
np_result = get_np_bin(bin_result, result_digits)
np_operand1 = get_np_bin(get_str_bin(int_dec_operand1),
operand_digits)
np_operand2 = get_np_bin(get_str_bin(int_dec_operand2),
operand_digits)
np_bin_result_algo, _ = multiply_two_numbers(
np_operand1, np_operand2)
is_equal = np.array_equal(np_result, np_bin_result_algo)
is_all_correct = is_all_correct and is_equal
return is_all_correct
def test_func_subtract_two_numbers():
is_all_correct = True
for operand_digits in config.operand_digits_list():
# varying part
result_digits = get_result_digits(operand_digits, 'subtract')
for int_dec_operand1 in range(2**operand_digits):
for int_dec_operand2 in range(2**operand_digits):
if int_dec_operand1 >= int_dec_operand2: # Only these cases are dealth with.
# varying part
bin_result = get_str_bin(int_dec_operand1 -
int_dec_operand2)
np_result = get_np_bin(bin_result, result_digits)
np_operand1 = get_np_bin(get_str_bin(int_dec_operand1),
operand_digits)
np_operand2 = get_np_bin(get_str_bin(int_dec_operand2),
operand_digits)
np_bin_result_algo, _ = subtract_two_numbers(
np_operand1, np_operand2)
is_equal = np.array_equal(np_result, np_bin_result_algo)
is_all_correct = is_all_correct and is_equal
return is_all_correct
def write_carry_dataset_statistics():
carry_dataset_info_list = list()
csv_file_path = get_carry_ds_stat_path()
create_dir(config.dir_data())
for operator in config.operators_list():
for operand_digits in config.operand_digits_list():
carry_datasets = generate_datasets(operand_digits, operator)
carry_dataset_info_list = carry_dataset_info_list + get_carry_dataset_info_list(
carry_datasets, operator)
with open(csv_file_path, mode='w') as csv_file:
fieldnames = [
'operator', 'operand digits', 'input dimension',
'output dimension', 'total operations', 'carries',
'carry operations', 'carry percentage'
]
writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
writer.writeheader()
for carry_dataset_info in carry_dataset_info_list:
writer.writerow(carry_dataset_info)
print('{} saved!'.format(csv_file_path))
