def test_check_filter_properties():
filter_coefs = design_fir_filter(FS, 'bandpass', (8, 12))
# Check valid / passing filter
passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass', (8, 12))
assert passes is True
# Check failing filter - insufficient attenuation
with warnings.catch_warnings(record=True) as warn:
filter_coefs = design_fir_filter(FS, 'bandstop', (8, 12))
passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass',
(8, 12))
assert passes is False
assert len(warn) == 1
assert "filter attenuation" in str(warn[-1].message)
# Check failing filter - transition bandwidth
with warnings.catch_warnings(record=True) as warn:
filter_coefs = design_fir_filter(FS, 'bandpass', (20, 21))
passes = check_filter_properties(filter_coefs, 1, FS, 'bandpass',
(8, 12))
assert passes is False
assert len(warn) == 1
assert "Transition bandwidth" in str(warn[-1].message)
# Check failing filter - insufficient attenuation on part of stopband
with warnings.catch_warnings(record=True) as w:
filter_coefs = design_fir_filter(FS, 'bandpass', (5, 40), n_cycles=1)
check_filter_properties(filter_coefs, 1, FS, 'bandpass', (5, 40))
assert len(w) == 1
assert "stopband" in str(w[-1].message)
def test_compute_frequency_response():
filter_coefs = design_fir_filter(FS, 'bandpass', (8, 12))
f_db, db = compute_frequency_response(filter_coefs, 1, FS)
with raises(ValueError):
f_db, db = compute_frequency_response(filter_coefs, None, FS)
def test_plot_impulse_response():
coefs = design_fir_filter(FS, 'bandpass', (8, 12), 3)
plot_impulse_response(FS, coefs,
save_fig=True, file_path=TEST_PLOTS_PATH,
file_name='test_plot_impulse_response.png')
def test_plot_impulse_response():
fs = 1000
coefs = design_fir_filter(2000, fs, 'bandpass', (8, 12), 3)
plot_impulse_response(fs, coefs)
assert True
def test_plot_frequency_response():
coefs = design_fir_filter(2000, 1000, 'bandpass', (8, 12), 3)
f_db, db = compute_frequency_response(coefs, a_vals=1, fs=1000)
plot_frequency_response(f_db, db)
assert True
def test_plot_frequency_response():
coefs = design_fir_filter(FS, 'bandpass', (8, 12), 3)
f_db, db = compute_frequency_response(coefs, a_vals=1, fs=FS)
plot_frequency_response(f_db, db,
save_fig=True, file_path=TEST_PLOTS_PATH,
file_name='test_plot_frequency_response.png')
def test_plot_filter_properties():
fs = 1000
coefs = design_fir_filter(2000, fs, 'bandpass', (8, 12), 3)
f_db, db = compute_frequency_response(coefs, a_vals=1, fs=1000)
plot_filter_properties(f_db, db, fs, coefs)
assert True
def test_compute_transition_band():
filter_coefs = design_fir_filter(FS, 'bandpass', (8, 12))
f_db, db = compute_frequency_response(filter_coefs, 1, FS)
trans_band = compute_transition_band(f_db, db)
def test_compute_frequency_response():
filter_coefs = design_fir_filter(FS, 'bandpass', (8, 12))
f_db, db = compute_frequency_response(filter_coefs, 1, FS)
def test_check_filter_properties():
filter_coefs = design_fir_filter(1000, 500, 'bandpass', (8, 12))
check_filter_properties(filter_coefs, 1, 500, 'bandpass', (8, 12))
assert True
def test_plot_impulse_response():
coefs = design_fir_filter(FS, 'bandpass', (8, 12), 3)
plot_impulse_response(FS, coefs)
def test_plot_frequency_response():
coefs = design_fir_filter(FS, 'bandpass', (8, 12), 3)
f_db, db = compute_frequency_response(coefs, a_vals=1, fs=FS)
plot_frequency_response(f_db, db)
def test_compute_transition_band():
filter_coefs = design_fir_filter(1000, 500, 'bandpass', (8, 12))
f_db, db = compute_frequency_response(filter_coefs, 1, 500)
trans_band = compute_transition_band(f_db, db)
assert True
# # We also need to specify the filter length, which can be defined either in seconds, or as a # number of cycles (defined as the low cutoff frequency). The default filter length is 3 cycles. # You may need to update this value to customize the filter length, as this impacts the # frequency response. # ################################################################################################### # Define filter settings pass_type = 'bandpass' f_range = (8, 13) n_cycles = 3 # Design the filter coefficients for a specified filter filter_coefs = design_fir_filter(fs, pass_type, f_range, n_cycles=n_cycles) ################################################################################################### # # Now that we have our filter coefficients, we can evaluate our filter. # # Next, we can calculate the frequency response, :math:`b_k`, for our alpha bandpass filter. # ################################################################################################### # Compute the frequency response of the filter f_db, db = compute_frequency_response(filter_coefs, 1, fs) # Plot the filter properties plot_filter_properties(f_db, db, fs, filter_coefs)
