# Complete path to file current_dir = os.path.dirname(os.path.abspath(__file__)) data_file = os.path.join(current_dir, data_file) data = get_data_from_mat_file(data_file) signal_1 = data[:2**12] signal_2 = data[2**12:] #------------------------------------------------------------------------------- # Setup analysis #------------------------------------------------------------------------------- # Multifractal analysis object mfa = mf.MFA() ### Set parameters. They can also be set in the constructor of mf.MFA() # wavelet to be used (see PyWavelets documentation for more options) mfa.wt_name = 'db3' # value of p for p-leaders, can be numpy.inf # NOTE: instead of defining the value of p, we can set the variable mfa.formalism, # e.g., mfa.formalism = 'wlmf' (corresponding to p = np.inf) or # mfa.formalism = 'wcmf' (which uses wavelet coefficients only, not leaders) mfa.p = 2 # scaling range mfa.j1 = 3 mfa.j2 = 9
# ------------------------------------------------------------------------------
# Run mf_analysis
# ------------------------------------------------------------------------------
for test_filename in test_data_files_full:
print(" ")
print("* Analyzing file ", test_filename)
# Load data
data = get_data_from_mat_file(test_filename)
# Get output filename
output_filename = out_filenames[test_filename]
# Run mf_analysis and save results
mfa = mfanalysis.MFA(verbose=0)
with open(output_filename, 'a') as csvfile:
writer = csv.writer(csvfile, lineterminator='\n')
for test_index in params: # test_index is a string, e.g. '123', and starts from '1'
if int(test_index) % 10 == 0:
print(" -- Test " + test_index, " of ", n_tests)
# Set parameters in MFA object
mfa.q = np.array(params[test_index]['q'])
mfa.j1 = params[test_index]['j1']
mfa.j2 = params[test_index]['j2']
mfa.wtype = params[test_index]['wtype']
mfa.gamint = params[test_index]['gamint']
mfa.wt_name = 'db' + str(
params[test_index]['nb_vanishing_moments'])
