@@ -140,6 +140,25 @@ def test_label_shift():
140140 assert ax .yaxis .get_label ().get_horizontalalignment () == "center"
141141
142142
143+ @check_figures_equal (extensions = ["png" ])
144+ def test_acorr (fig_test , fig_ref ):
145+ np .random .seed (19680801 )
146+ Nx = 512
147+ x = np .random .normal (0 , 1 , Nx ).cumsum ()
148+ maxlags = Nx - 1
149+
150+ ax_test = fig_test .subplots ()
151+ ax_test .acorr (x , maxlags = maxlags )
152+
153+ ax_ref = fig_ref .subplots ()
154+ # Normalized autocorrelation
155+ norm_auto_corr = np .correlate (x , x , mode = "full" )/ np .dot (x , x )
156+ lags = np .arange (- maxlags , maxlags + 1 )
157+ norm_auto_corr = norm_auto_corr [Nx - 1 - maxlags :Nx + maxlags ]
158+ ax_ref .vlines (lags , [0 ], norm_auto_corr )
159+ ax_ref .axhline (y = 0 , xmin = 0 , xmax = 1 )
160+
161+
143162@check_figures_equal (extensions = ["png" ])
144163def test_spy (fig_test , fig_ref ):
145164 np .random .seed (19680801 )
@@ -4706,6 +4725,253 @@ def test_subplot_key_hash():
47064725 assert ax .get_subplotspec ().get_geometry () == (5 , 1 , 0 , 0 )
47074726
47084727
4728+ @pytest .mark .filterwarnings (
4729+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4730+ @image_comparison (
4731+ ["specgram_freqs.png" , "specgram_freqs_linear.png" ,
4732+ "specgram_noise.png" , "specgram_noise_linear.png" ],
4733+ remove_text = True , tol = 0.07 , style = "default" )
4734+ def test_specgram ():
4735+ """Test axes.specgram in default (psd) mode."""
4736+
4737+ # use former defaults to match existing baseline image
4738+ matplotlib .rcParams ['image.interpolation' ] = 'nearest'
4739+
4740+ n = 1000
4741+ Fs = 10.
4742+
4743+ fstims = [[Fs / 4 , Fs / 5 , Fs / 11 ], [Fs / 4.7 , Fs / 5.6 , Fs / 11.9 ]]
4744+ NFFT_freqs = int (10 * Fs / np .min (fstims ))
4745+ x = np .arange (0 , n , 1 / Fs )
4746+ y_freqs = np .concatenate (
4747+ np .sin (2 * np .pi * np .multiply .outer (fstims , x )).sum (axis = 1 ))
4748+
4749+ NFFT_noise = int (10 * Fs / 11 )
4750+ np .random .seed (0 )
4751+ y_noise = np .concatenate ([np .random .standard_normal (n ), np .random .rand (n )])
4752+
4753+ all_sides = ["default" , "onesided" , "twosided" ]
4754+ for y , NFFT in [(y_freqs , NFFT_freqs ), (y_noise , NFFT_noise )]:
4755+ noverlap = NFFT // 2
4756+ pad_to = int (2 ** np .ceil (np .log2 (NFFT )))
4757+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4758+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4759+ pad_to = pad_to , sides = sides )
4760+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4761+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4762+ pad_to = pad_to , sides = sides ,
4763+ scale = "linear" , norm = matplotlib .colors .LogNorm ())
4764+
4765+ @pytest .mark .filterwarnings (
4766+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4767+ @image_comparison (
4768+ ["specgram_magnitude_freqs.png" , "specgram_magnitude_freqs_linear.png" ,
4769+ "specgram_magnitude_noise.png" , "specgram_magnitude_noise_linear.png" ],
4770+ remove_text = True , tol = 0.07 , style = "default" )
4771+ def test_specgram_magnitude ():
4772+ """Test axes.specgram in magnitude mode."""
4773+
4774+ # use former defaults to match existing baseline image
4775+ matplotlib .rcParams ['image.interpolation' ] = 'nearest'
4776+
4777+ n = 1000
4778+ Fs = 10.
4779+
4780+ fstims = [[Fs / 4 , Fs / 5 , Fs / 11 ], [Fs / 4.7 , Fs / 5.6 , Fs / 11.9 ]]
4781+ NFFT_freqs = int (100 * Fs / np .min (fstims ))
4782+ x = np .arange (0 , n , 1 / Fs )
4783+ y = np .sin (2 * np .pi * np .multiply .outer (fstims , x )).sum (axis = 1 )
4784+ y [:, - 1 ] = 1
4785+ y_freqs = np .hstack (y )
4786+
4787+ NFFT_noise = int (10 * Fs / 11 )
4788+ np .random .seed (0 )
4789+ y_noise = np .concatenate ([np .random .standard_normal (n ), np .random .rand (n )])
4790+
4791+ all_sides = ["default" , "onesided" , "twosided" ]
4792+ for y , NFFT in [(y_freqs , NFFT_freqs ), (y_noise , NFFT_noise )]:
4793+ noverlap = NFFT // 2
4794+ pad_to = int (2 ** np .ceil (np .log2 (NFFT )))
4795+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4796+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4797+ pad_to = pad_to , sides = sides , mode = "magnitude" )
4798+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4799+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4800+ pad_to = pad_to , sides = sides , mode = "magnitude" ,
4801+ scale = "linear" , norm = matplotlib .colors .LogNorm ())
4802+
4803+
4804+ @pytest .mark .filterwarnings (
4805+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4806+ @image_comparison (
4807+ ["specgram_angle_freqs.png" , "specgram_phase_freqs.png" ,
4808+ "specgram_angle_noise.png" , "specgram_phase_noise.png" ],
4809+ remove_text = True , tol = 0.07 , style = "default" )
4810+ def test_specgram_angle ():
4811+ """Test axes.specgram in angle and phase modes."""
4812+
4813+ # use former defaults to match existing baseline image
4814+ matplotlib .rcParams ['image.interpolation' ] = 'nearest'
4815+
4816+ n = 1000
4817+ Fs = 10.
4818+
4819+ fstims = [[Fs / 4 , Fs / 5 , Fs / 11 ], [Fs / 4.7 , Fs / 5.6 , Fs / 11.9 ]]
4820+ NFFT_freqs = int (10 * Fs / np .min (fstims ))
4821+ x = np .arange (0 , n , 1 / Fs )
4822+ y = np .sin (2 * np .pi * np .multiply .outer (fstims , x )).sum (axis = 1 )
4823+ y [:, - 1 ] = 1
4824+ y_freqs = np .hstack (y )
4825+
4826+ NFFT_noise = int (10 * Fs / 11 )
4827+ np .random .seed (0 )
4828+ y_noise = np .concatenate ([np .random .standard_normal (n ), np .random .rand (n )])
4829+
4830+ all_sides = ["default" , "onesided" , "twosided" ]
4831+ for y , NFFT in [(y_freqs , NFFT_freqs ), (y_noise , NFFT_noise )]:
4832+ noverlap = NFFT // 2
4833+ pad_to = int (2 ** np .ceil (np .log2 (NFFT )))
4834+ for mode in ["angle" , "phase" ]:
4835+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4836+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4837+ pad_to = pad_to , sides = sides , mode = mode )
4838+ with pytest .raises (ValueError ):
4839+ ax .specgram (y , NFFT = NFFT , Fs = Fs , noverlap = noverlap ,
4840+ pad_to = pad_to , sides = sides , mode = mode ,
4841+ scale = "dB" )
4842+
4843+
4844+ @pytest .mark .filterwarnings (
4845+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4846+ def test_specgram_fs_none ():
4847+ """Test axes.specgram when Fs is None, should not throw error."""
4848+ spec , freqs , t , im = plt .specgram (np .ones (300 ), Fs = None , scale = 'linear' )
4849+ xmin , xmax , freq0 , freq1 = im .get_extent ()
4850+ assert xmin == 32 and xmax == 96
4851+
4852+
4853+ @pytest .mark .filterwarnings (
4854+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4855+ @check_figures_equal (extensions = ["png" ])
4856+ def test_specgram_origin_rcparam (fig_test , fig_ref ):
4857+ """Test specgram ignores image.origin rcParam and uses origin 'upper'."""
4858+ t = np .arange (500 )
4859+ signal = np .sin (t )
4860+
4861+ plt .rcParams ["image.origin" ] = 'upper'
4862+
4863+ # Reference: First graph using default origin in imshow (upper),
4864+ fig_ref .subplots ().specgram (signal )
4865+
4866+ # Try to overwrite the setting trying to flip the specgram
4867+ plt .rcParams ["image.origin" ] = 'lower'
4868+
4869+ # Test: origin='lower' should be ignored
4870+ fig_test .subplots ().specgram (signal )
4871+
4872+
4873+ @pytest .mark .filterwarnings (
4874+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4875+ def test_specgram_origin_kwarg ():
4876+ """Ensure passing origin as a kwarg raises a TypeError."""
4877+ t = np .arange (500 )
4878+ signal = np .sin (t )
4879+
4880+ with pytest .raises (TypeError ):
4881+ plt .specgram (signal , origin = 'lower' )
4882+
4883+ @pytest .mark .filterwarnings (
4884+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4885+ @image_comparison (
4886+ ["psd_freqs.png" , "csd_freqs.png" , "psd_noise.png" , "csd_noise.png" ],
4887+ remove_text = True , tol = 0.002 )
4888+ def test_psd_csd ():
4889+ n = 10000
4890+ Fs = 100.
4891+
4892+ fstims = [[Fs / 4 , Fs / 5 , Fs / 11 ], [Fs / 4.7 , Fs / 5.6 , Fs / 11.9 ]]
4893+ NFFT_freqs = int (1000 * Fs / np .min (fstims ))
4894+ x = np .arange (0 , n , 1 / Fs )
4895+ ys_freqs = np .sin (2 * np .pi * np .multiply .outer (fstims , x )).sum (axis = 1 )
4896+
4897+ NFFT_noise = int (1000 * Fs / 11 )
4898+ np .random .seed (0 )
4899+ ys_noise = [np .random .standard_normal (n ), np .random .rand (n )]
4900+
4901+ all_kwargs = [{"sides" : "default" },
4902+ {"sides" : "onesided" , "return_line" : False },
4903+ {"sides" : "twosided" , "return_line" : True }]
4904+ for ys , NFFT in [(ys_freqs , NFFT_freqs ), (ys_noise , NFFT_noise )]:
4905+ noverlap = NFFT // 2
4906+ pad_to = int (2 ** np .ceil (np .log2 (NFFT )))
4907+ for ax , kwargs in zip (plt .figure ().subplots (3 ), all_kwargs ):
4908+ ret = ax .psd (np .concatenate (ys ), NFFT = NFFT , Fs = Fs ,
4909+ noverlap = noverlap , pad_to = pad_to , ** kwargs )
4910+ assert len (ret ) == 2 + kwargs .get ("return_line" , False )
4911+ ax .set (xlabel = "" , ylabel = "" )
4912+ for ax , kwargs in zip (plt .figure ().subplots (3 ), all_kwargs ):
4913+ ret = ax .csd (* ys , NFFT = NFFT , Fs = Fs ,
4914+ noverlap = noverlap , pad_to = pad_to , ** kwargs )
4915+ assert len (ret ) == 2 + kwargs .get ("return_line" , False )
4916+ ax .set (xlabel = "" , ylabel = "" )
4917+
4918+
4919+ @pytest .mark .filterwarnings (
4920+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4921+ @image_comparison (
4922+ ["magnitude_spectrum_freqs_linear.png" ,
4923+ "magnitude_spectrum_freqs_dB.png" ,
4924+ "angle_spectrum_freqs.png" ,
4925+ "phase_spectrum_freqs.png" ,
4926+ "magnitude_spectrum_noise_linear.png" ,
4927+ "magnitude_spectrum_noise_dB.png" ,
4928+ "angle_spectrum_noise.png" ,
4929+ "phase_spectrum_noise.png" ],
4930+ remove_text = True )
4931+ def test_spectrum ():
4932+ n = 10000
4933+ Fs = 100.
4934+
4935+ fstims1 = [Fs / 4 , Fs / 5 , Fs / 11 ]
4936+ NFFT = int (1000 * Fs / min (fstims1 ))
4937+ pad_to = int (2 ** np .ceil (np .log2 (NFFT )))
4938+
4939+ x = np .arange (0 , n , 1 / Fs )
4940+ y_freqs = ((np .sin (2 * np .pi * np .outer (x , fstims1 )) * 10 ** np .arange (3 ))
4941+ .sum (axis = 1 ))
4942+ np .random .seed (0 )
4943+ y_noise = np .hstack ([np .random .standard_normal (n ), np .random .rand (n )]) - .5
4944+
4945+ all_sides = ["default" , "onesided" , "twosided" ]
4946+ kwargs = {"Fs" : Fs , "pad_to" : pad_to }
4947+ for y in [y_freqs , y_noise ]:
4948+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4949+ spec , freqs , line = ax .magnitude_spectrum (y , sides = sides , ** kwargs )
4950+ ax .set (xlabel = "" , ylabel = "" )
4951+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4952+ spec , freqs , line = ax .magnitude_spectrum (y , sides = sides , ** kwargs ,
4953+ scale = "dB" )
4954+ ax .set (xlabel = "" , ylabel = "" )
4955+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4956+ spec , freqs , line = ax .angle_spectrum (y , sides = sides , ** kwargs )
4957+ ax .set (xlabel = "" , ylabel = "" )
4958+ for ax , sides in zip (plt .figure ().subplots (3 ), all_sides ):
4959+ spec , freqs , line = ax .phase_spectrum (y , sides = sides , ** kwargs )
4960+ ax .set (xlabel = "" , ylabel = "" )
4961+
4962+
4963+ @pytest .mark .filterwarnings (
4964+ 'ignore::matplotlib._api.deprecation.MatplotlibDeprecationWarning' )
4965+ def test_psd_csd_edge_cases ():
4966+ # Inverted yaxis or fully zero inputs used to throw exceptions.
4967+ axs = plt .figure ().subplots (2 )
4968+ for ax in axs :
4969+ ax .yaxis .set (inverted = True )
4970+ with np .errstate (divide = "ignore" ):
4971+ axs [0 ].psd (np .zeros (5 ))
4972+ axs [1 ].csd (np .zeros (5 ), np .zeros (5 ))
4973+
4974+
47094975@check_figures_equal (extensions = ['png' ])
47104976def test_twin_remove (fig_test , fig_ref ):
47114977 ax_test = fig_test .add_subplot ()
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