Clean up of names and cvxpy dependency. Added placeholder folder for …

…figures and sound_samples.
LCAV · Jul 15, 2014 · a594a6d · a594a6d
1 parent 77267ed
commit a594a6d
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Showing 9 changed files with 13 additions and 54 deletions.
diff --git a/beamforming.py b/beamforming.py
@@ -1,5 +1,4 @@
 import numpy as np
-import cvxpy as cp
 from time import sleep
 
 import constants
@@ -36,48 +35,6 @@ def mdot(*args):
     return ret
 
 
-def complex_to_real_matrix(A):
-
-    A_real = np.real(A)
-    A_imag = np.imag(A)
-
-    A_ctr = np.vstack([np.hstack([A_real, -A_imag]),
-                       np.hstack([A_imag, A_real])])
-
-    return A_ctr
-
-
-def real_to_complex_vector(b):
-
-    n = b.shape[0] / 2
-    return b[0:n] + 1j * b[n:]
-
-
-def echo_beamformer_cvx(A_good, A_bad):
-
-    # Expand complex matrices and vectors to real matrices and vectors
-    A_good_ctr_H = complex_to_real_matrix(H(A_good))
-    A_bad_ctr_H = complex_to_real_matrix(H(A_bad))
-
-    M = A_good.shape[0]
-    K = A_good.shape[1]
-
-    h = cp.Variable(2 * M)
-
-    # Objective: minimize(norm(h.H * A_good)^2)
-
-    objective = cp.Minimize(cp.sum_entries(cp.square(A_bad_ctr_H * h)))
-
-    # Constraint: sum(h.H * A_good) = 1 + 0*1j
-    constraints = [cp.sum_entries((A_good_ctr_H * h)[0:K]) == 1,
-                   cp.sum_entries((A_good_ctr_H * h)[K:]) == 0]
-
-    problem = cp.Problem(objective, constraints)
-    problem.solve()
-
-    return np.array(real_to_complex_vector(h.value))
-
-
 def distance(X, Y):
     # Assume X, Y are arrays, *not* matrices
     X = np.array(X)

diff --git a/figure_Measures1.py b/figure_Measures1.py
@@ -194,8 +194,8 @@
 
 plt.legend(beamformer_names, fontsize=7, loc='upper left', frameon=False, labelspacing=0)
 
-plt.savefig('SINR_vs_K.png')
-plt.savefig('SINR_vs_K.pdf')
+plt.savefig('figures/SINR_vs_K.png')
+plt.savefig('figures/SINR_vs_K.pdf')
 
 plt.close()
 
@@ -253,5 +253,5 @@
 
 plt.legend(beamformer_names, fontsize=7, loc='upper left', frameon=False, labelspacing=0)
 
-plt.savefig('UDR_vs_K.png')
-plt.savefig('UDR_vs_K.pdf')
+plt.savefig('figures/UDR_vs_K.png')
+plt.savefig('figures/UDR_vs_K.pdf')
diff --git a/figure_Measures2.py b/figure_Measures2.py
@@ -161,8 +161,8 @@
 
 plt.legend(beamformer_names, fontsize=7, loc='lower right', frameon=False, labelspacing=0)
 
-plt.savefig('SINR_vs_freq.png')
-plt.savefig('SINR_vs_freq.pdf')
+plt.savefig('figures/SINR_vs_freq.png')
+plt.savefig('figures/SINR_vs_freq.pdf')
 
 
 
diff --git a/figure_SumNorm.py b/figure_SumNorm.py
@@ -109,6 +109,6 @@
 plt.ylabel('SNR gain [dB]', fontsize=10)
 plt.tight_layout()
 
-plt.savefig('SNR_gain.png')
-plt.savefig('SNR_gain.pdf')
+plt.savefig('figures/SNR_gain.png')
+plt.savefig('figures/SNR_gain.pdf')
 
diff --git a/fig_beam_scenarios.py → figure_beam_scenarios.py b/fig_beam_scenarios.py → figure_beam_scenarios.py
diff --git a/fig_filter_avg_ir.py → figure_filter_avg_ir.py b/fig_filter_avg_ir.py → figure_filter_avg_ir.py
diff --git a/fig_spectrograms.py → figure_spectrograms.py b/fig_spectrograms.py → figure_spectrograms.py
@@ -163,9 +163,9 @@
 output_maxsinr = output_maxsinr[:n_lim]
 
 # save all files for listening test
-wavfile.write('input_mic.wav', Fs, input_mic)
-wavfile.write('output_mvdr.wav', Fs, output_mvdr)
-wavfile.write('output_maxsinr.wav', Fs, output_maxsinr)
+wavfile.write('output_samples/input_mic.wav', Fs, input_mic)
+wavfile.write('output_samples/output_mvdr.wav', Fs, output_mvdr)
+wavfile.write('output_samples/output_maxsinr.wav', Fs, output_maxsinr)
 
 # compute time-frequency planes
 F0 = stft(input_clean, fft_size, fft_hop, 

diff --git a/figures/README.md b/figures/README.md
@@ -0,0 +1 @@
+A directory to store all generated figures.
diff --git a/output_samples/README.md b/output_samples/README.md
@@ -0,0 +1 @@
+A directory to store all generated output sound samples.