Corrects experiment to also measure for p=2, q=2

bss_scale/algorithms.py

@@ -126,7 +126,7 @@ def minimum_distortion(
     """
 
     # by default we do the regular minimum distortion
-    if p is None or (p == 2.0 and q is None):
+    if p is None or (p == 2.0 and (q is None or p == q)):
         return minimum_distortion_l2(Y, ref), 1
 
     n_frames, n_freq, n_channels = Y.shape

experiment1_config.json

@@ -10,7 +10,7 @@
   "ref_mic": 0,
 
   "minimum_distortion": {
-    "p_list": [0.1, 2.0, 0.1],
+    "p_list": [0.1, 2.0, 20],
     "kwargs": {
       "rtol": 1e-5,
       "max_iter": 100

experiment1_rpt.py

@@ -82,6 +82,6 @@ def one_loop(args):
         gen_args,
         func_init=init,
         base_dir=base_dir,
-        results_dir="data/",
+        results_dir="sim_results/",
         description="Simulation for OverIVA",
     )

process.py

@@ -109,10 +109,11 @@ def process(args, config):
     results.append(t.copy())
 
     # minimum distortion
-    lo, hi, step = config["minimum_distortion"]["p_list"]
+    lo, hi, n_steps = config["minimum_distortion"]["p_list"]
+    p_vals = np.linspace(lo, hi, n_steps)
     kwargs = config["minimum_distortion"]["kwargs"]
-    for p in np.arange(lo, hi + step, step):
-        for q in np.arange(p, hi + step, step):
+    for ip, p in enumerate(p_vals):
+        for q in p_vals[ip:]:
             t["p"], t["q"], t["proj_algo"] = (
                 f"{p:.1f}",
                 f"{q:.1f}",