Learned-key stages, per-scheme plot styles, KM naming

exp_learned.py mirrors every structured result stage for the learned key
family at the same SNRs, frame counts and seeds, so Figs. 2, 3, 4 and 7
and Tables IV and VI can carry both realizations of keyed masking.

replot_security.py gains a style registry: colour identifies the scheme
and line style the role, so a curve learned in one figure reads the same
in the next. Previously OMA was grey in two figures and teal in a third,
and blue meant the eavesdropper in one figure and the permutation key in
another.

data/compare_learned.csv

@@ -0,0 +1,2 @@
+scheme,legit_ser,eve_out,eve_in,jam0_ser
+proposed_learned,0.06358416667,0.9998083333,0.9999833333,0.4046066667

data/kpa_learned.csv

@@ -0,0 +1,43 @@
+snr_db,n_frames,kappa,eve_ser
+0,1,0.2127109103,0.993336
+0,2,0.7559393242,0.666508
+0,3,0.8627683729,0.392272125
+0,4,0.9179756209,0.218212875
+0,5,0.945390512,0.14425925
+0,6,0.9590921029,0.107493
+0,8,0.9725584686,0.086112625
+0,10,0.9778045967,0.07933375
+0,12,0.9831736788,0.07420325
+0,16,0.9879393309,0.070712875
+0,24,0.9925390184,0.067800375
+0,32,0.9945808738,0.06649325
+0,48,0.9965663388,0.065265
+0,64,0.9975094497,0.065024875
+10,1,0.3165432975,0.948993875
+10,2,0.9290210679,0.19776825
+10,3,0.9781143948,0.095876875
+10,4,0.9896475986,0.070495125
+10,5,0.9934410676,0.067297125
+10,6,0.9953705788,0.06628575
+10,8,0.9971551418,0.06520175
+10,10,0.9979188025,0.064684875
+10,12,0.9982561454,0.06454375
+10,16,0.9987509355,0.06426625
+10,24,0.9992754847,0.064091125
+10,32,0.9994516179,0.06386675
+10,48,0.9996520028,0.063819875
+10,64,0.999746412,0.063847125
+20,1,0.742194891,0.513137625
+20,2,0.9947786465,0.06753025
+20,3,0.9986294076,0.06438075
+20,4,0.9992210969,0.064160375
+20,5,0.9994008377,0.064080125
+20,6,0.9995701849,0.063900375
+20,8,0.9997365534,0.063852875
+20,10,0.9998067141,0.063813
+20,12,0.9998438716,0.06370225
+20,16,0.9998808399,0.063670875
+20,24,0.9999239221,0.06380125
+20,32,0.9999452353,0.063820625
+20,48,0.9999649763,0.063811
+20,64,0.9999733046,0.06377525

data/refresh_learned.csv

@@ -0,0 +1,9 @@
+block,legit_ser,eve_ser
+0,0.06381666667,0.9999375
+1,0.06395583333,0.9981941667
+2,0.06397833333,0.999985
+3,0.06386833333,0.9983758333
+4,0.06338666667,0.9999908333
+5,0.06366416667,0.9999133333
+6,0.06398416667,0.9999433333
+7,0.06390583333,0.9809091667

data/refresh_summary.csv

@@ -2,3 +2,4 @@ scheme,legit,eve,entropy_bits
 None (fixed key),0.05300666667,0.9997075,23.76910417
 Fresh orthogonal keys,0.1215548611,0.9996535069,23.76910417
 Invariant,0.05304121528,0.9995528819,364.5801064
+"Invariant, learned keys",0.063800,0.997200,364.5801064

data/sec_compare.csv

@@ -4,3 +4,4 @@ public_mask,0.0529425,0.0529425,0.0529425,0.83882
 perm_key,0.0528525,0.9999925,0.0528525,0.36425
 index_cipher,0.0529425,0.9999847412,0.9999847412,0.83882
 oma_plain,0.08056383667,0.08056383667,0.08056383667,nan
+proposed_learned,0.06358416667,0.9998083333,0.9999833333,0.4046066667

data/sec_jam_learned.csv

@@ -0,0 +1,8 @@
+jsr_db,blind,matched,nojam
+-10,0.117582,0.40832,0.062852
+-5,0.215158,0.657572,0.062852
+0,0.404244,0.851282,0.062852
+5,0.648786,0.94662,0.062852
+10,0.839218,0.982652,0.062852
+15,0.939304,0.994184,0.062852
+20,0.979206,0.99818,0.062852

data/sec_keylen_learned.csv

@@ -0,0 +1,9 @@
+L,d,legit_ser,eve_ser,mask_xcorr,oma
+8,32,0.9297855,0.9998735,0.007307400461,0.6849191155
+12,48,0.416604,0.9997065,0.005153660662,nan
+16,64,0.2762895,0.999912,0.007116591092,0.2747696909
+20,80,0.2076175,0.999383,0.003162040841,0.2289444229
+24,96,0.1829615,0.999894,0.002973971656,0.1961714033
+32,128,0.131901,0.999616,0.005575809628,0.1524639978
+48,192,0.090206,0.9994575,0.005743456539,0.1054308944
+64,256,0.0635265,0.999637,0.006678360514,0.08056383667