Update xp1

experiments/SIAM/xp_1_balls/xp_a_accuracy_sol.py

 # -*- coding: utf-8 -*-
 import time, argparse, sys
-from pathlib import Path
 
 import numpy as np
 
@@ -14,8 +13,7 @@ from src.utils import get_lambda_max, gamma_sequence_generator
 from src.dictionaries import generate_dic
 
 # Screening
-from src.screening.singletest import GapSphereSingleTest
-from src.screening.gap_ptest import GAP_Ptest
+from src.screening.gap_test_all import GapTestAll
 
 # XP import
 from experiments.SIAM.slopepb import SlopePb
@@ -26,7 +24,7 @@ parser=argparse.ArgumentParser()
 parser.add_argument('--erase', help='erase existing results', action="store_true")
 parser.add_argument('--continue', help='save figure', action="store_true", dest="cont")
 parser.add_argument('--id', help='setup id', type=str,
-    default="1a")
+    default=1)
 args=parser.parse_args()
 
 
@@ -35,10 +33,7 @@ args=parser.parse_args()
 # -------------------------
 
 setup = Setup(args.id)
-folder = "results/"
-Path(folder).mkdir(parents=True, exist_ok=True)
-
-out_file_name = folder + f"/xp_setup{args.id}.npz"
+out_file_name = f"results/xp_setup{args.id}.npz"
 
 mat_seed = np.random.randint(
    0, 2**32-1,
@@ -131,19 +126,21 @@ for i_dic in range(setup.nb_dic):
                params.max_it = 1e7
                params.gap_stopping = xpparams.stopping_gap
                params.time_stopping = np.inf
-               params.screening1 = GapSphereSingleTest()
-               params.screening2 = GAP_Ptest(vec_gammas)
-               params.screening_it_div = 2.
+               params.screening1 = GapTestAll(vec_gammas)
+               params.eval_gap   = True
+               params.eval_gap_it = setup.eval_gap_it
                params.accelerated = True
                params.verbose = False
                
                out_slope = slope_gp(vecy, matA, ratio * lbd_max, vec_gammas, params)
 
-               gap = slopePb.eval_gap(out_slope["sol"], out_slope["dualsol"])
+               dv  = vecy - matA @  out_slope["sol"]
+               dv = slopePb.make_dual_scaling(dv)
+               gap = slopePb.eval_gap(out_slope["sol"], dv)
 
                if gap <= gap_old:
                   mat_pvopt[i_dic, i_seq, i_ratio, rep, :] = out_slope["sol"]
-                  mat_dvopt[i_dic, i_seq, i_ratio, rep, :] = out_slope["dualsol"]
+                  mat_dvopt[i_dic, i_seq, i_ratio, rep, :] = dv
 
                   # Save
                   np.savez(out_file_name,

experiments/SIAM/xp_1_balls/xp_b_screening.py

 # -*- coding: utf-8 -*-
 import argparse
-from pathlib import Path
 
 import numpy as np
 
@@ -10,10 +9,9 @@ from src.dictionaries import generate_dic
 from src.utils import get_lambda_max, gamma_sequence_generator
 
 # Screening
-from src.screening.gap_rqtest import GAP_RQtest
-from src.screening.kappa_test import Kappa_test
-from src.screening.singletest import GapSphereSingleTest
-from src.screening.gap_ptest import GAP_Ptest
+from src.screening.gap_test_p_1 import GapTestPequalOne
+from src.screening.gap_test_p_q import GapTestPequalQ
+from src.screening.gap_test_all import GapTestAll
 
 # XP import
 from experiments.SIAM.slopepb import SlopePb
@@ -103,14 +101,12 @@ for i_dic in range(setup.nb_dic):
 
             # ---- 3c. Testing sphere ---- 
             list_tests = [
-               # GAP_RQtest(vec_gammas, 1 + np.arange(setup.n)),
-               Kappa_test(vec_gammas, np.arange(setup.n, dtype=float)),
-               GapSphereSingleTest(),
-               GAP_Ptest(vec_gammas),
+               GapTestPequalOne(vec_gammas, np.arange(setup.n, dtype=np.double)),
+               GapTestPequalQ(),
+               GapTestAll(vec_gammas),
             ]
             assert(len(list_tests) == NB_TEST)
 
-
             for i_offset, offset in enumerate(xpparams.vec_offsets):
                for i_test, test in enumerate(list_tests):
                   out = test.apply_test(np.abs(Atu), gap, ratio * lbd_max, vec_gammas, offset_radius=offset)

experiments/SIAM/xp_1_balls/xp_c_viz_fig1.py

 # -*- coding: utf-8 -*-
-from decimal import Decimal
-import json, argparse
-from pathlib import Path
+import argparse
 
 import numpy as np
 
 # XP import
 from experiments.SIAM.slopepb import SlopePb
 from experiments.SIAM.setup import Setup
-from experiments.SIAM.xp_1_balls import xpparams
-from experiments.SIAM.xp_1_balls.process_data import process
+
+import xpparams
+from process_data import process
 
 
 parser=argparse.ArgumentParser()
 parser.add_argument('--noshow', help='do not display figures', action="store_true")
 parser.add_argument('--save', help='save figure', action="store_true")
-# parser.add_argument('--id', help='setup id', type=str, default=1)
+parser.add_argument('--id', help='setup id', type=str, default="SIAM")
+parser.add_argument('--i_seq', type=int, default=0)
 args=parser.parse_args()
 
 import matplotlib
@@ -52,7 +52,7 @@ font_text = font_manager.FontProperties(
 
 font_ttt = font_manager.FontProperties(
    # fname='../fonts/ectt1000.ttf',
-   fname='../fonts/cmuntt.ttf',
+   fname='../fonts/computer-modern/cmuntt.ttf',
    weight='bold',
    style='normal',
    size=fs
@@ -63,14 +63,15 @@ font_ttt = font_manager.FontProperties(
 #        Load Results
 # -------------------------
 
-# OSCAR
-setup_oscar = Setup("1a")
+
+setup_oscar = Setup(args.id)
 dic_process_oscar = process(setup_oscar)
 
 mat_pc_detected_oscar = dic_process_oscar["mat_pc_detected"]
 list_tests_oscar      = dic_process_oscar["list_tests"]
 
 
+
 # -------------------------
 #        Plot Results
 # -------------------------
@@ -81,63 +82,58 @@ i_lbd = 1
 fs=22
 fs_ylabels = 20
 list_colors  = ["tab:blue", "tab:orange", "tab:green"]
-list_legends = ["$r_q=q\\;\\forall q$", "best performance", "$r_q=1\\;\\forall q$"]
+list_legends = ["$p_q=q\\;\\forall q$", "all", "$p_q=1\\;\\forall q$"]
 # "best $r_q \\;\\forall q$ "
 
 print("printing xp_0_ball parameters with")
-print(" - OSCAR sequence")
 print(f"- {setup_oscar.list_dic[i_dic]} dictionary")
 print(f"- lbd / lbd_max = {setup_oscar.list_ratio_lbd[i_lbd]}")
 
-for i_seq in range(2):
 
-   f, ax = plt.subplots(1, 1, figsize=(.7*16, .6*9), sharex=True, sharey=True)
+f, ax = plt.subplots(1, 1, figsize=(.7*16, .6*9), sharex=True, sharey=True)
 
-   # ax.set_title(f"OSCAR-{i_seq+1}", fontsize=fs+2)
-   ax.set_xlabel(
-      r"$R$", 
-      fontsize=fs+2,
-      fontproperties=font_math,
-   )
-   ax.set_ylabel(
-      "% of zero entries detected",
-      fontsize=fs+2,
-      fontproperties=font_text
+# ax.set_title(f"OSCAR-{i_seq+1}", fontsize=fs+2)
+ax.set_xlabel(
+   r"$R$", 
+   fontsize=fs+2,
+   fontproperties=font_math,
+)
+ax.set_ylabel(
+   "% of zero entries detected",
+   fontsize=fs+2,
+   fontproperties=font_text
+)
+
+for tick in ax.xaxis.get_major_ticks():
+   tick.label.set_fontproperties(font_math)
+   tick.label.set_fontsize(20)
+
+for tick in ax.yaxis.get_major_ticks():
+   tick.label.set_fontproperties(font_math)
+   tick.label.set_fontsize(20)
+
+for i_test in [2, 0, 1]:
+   ax.plot(
+      xpparams.vec_offsets, 
+      100 * mat_pc_detected_oscar[i_test, :, i_dic, args.i_seq, i_lbd],
+      label = list_legends[i_test],
+      linewidth=4.,
+      alpha=.9,
+      color=list_colors[i_test]
    )
 
-   for tick in ax.xaxis.get_major_ticks():
-      tick.label.set_fontproperties(font_math)
-      tick.label.set_fontsize(20)
-
-   for tick in ax.yaxis.get_major_ticks():
-      tick.label.set_fontproperties(font_math)
-      tick.label.set_fontsize(20)
-
-   for i_test in [2, 0, 1]:
-      ax.plot(
-         xpparams.vec_offsets, 
-         100 * mat_pc_detected_oscar[i_test, :, i_dic, i_seq, i_lbd],
-         label = list_legends[i_test],
-         linewidth=4.,
-         alpha=.9,
-         color=list_colors[i_test]
-      )
-
-   if i_seq == 0:
-      ax.legend(
-         fontsize=fs-2,
-         prop=font_math
-      )
-
-   ax.set_xscale("log")
-   ax.set_xlim([1e-6, 1e0])
-   ax.set_ylim([-2, 102])
-
-   if args.save:
-      Path("figs/").mkdir(parents=True, exist_ok=True)      
-
-      filename = f"figs/xp_illustration_screening{i_seq}.eps"
-      plt.savefig(filename, bbox_inches='tight')
+ax.legend(
+   fontsize=fs-2,
+   prop=font_math
+)
+
+ax.set_xscale("log")
+ax.set_xlim([1e-6, 1e0])
+ax.set_ylim([-2, 102])
+
+if args.save:
+   filename = f"figs/xp_illustration_screening{args.i_seq}.eps"
+   plt.savefig(filename, bbox_inches='tight')
 
 if not args.noshow:
    plt.show()
\ No newline at end of file

experiments/SIAM/xp_1_balls/xp_c_viz_fig2.py

 # -*- coding: utf-8 -*-
-from decimal import Decimal
-import json, argparse
-from pathlib import Path
+import argparse
 
 import numpy as np
 
 # XP import
 from experiments.SIAM.slopepb import SlopePb
 from experiments.SIAM.setup import Setup
-from experiments.SIAM.xp_1_balls import xpparams
-from experiments.SIAM.xp_1_balls.process_data import process
+
+import xpparams
+from process_data import process
 
 
 parser=argparse.ArgumentParser()
 parser.add_argument('--noshow', help='do not display figures', action="store_true")
 parser.add_argument('--save', help='save figure', action="store_true")
-# parser.add_argument('--id', help='setup id', type=str, default=1)
+parser.add_argument('--id', help='setup id', type=str, default="SIAM")
 args=parser.parse_args()
 
 import matplotlib
@@ -26,14 +25,15 @@ else:
 import matplotlib.pyplot as plt
 from matplotlib.legend_handler import HandlerBase
 import matplotlib.font_manager as font_manager
-
+# print(matplotlib.get_backend())
+# matplotlib.rc('pdf', fonttype=42)
 
 # -------------------------
 #        Load Results
 # -------------------------
 
 # OSCAR
-setup_oscar = Setup("1a")
+setup_oscar = Setup(args.id)
 dic_process_oscar = process(setup_oscar)
 
 mat_pc_detected_oscar = dic_process_oscar["mat_pc_detected"]
@@ -153,7 +153,7 @@ f.tight_layout()
 
 
 for i_seq in range(3):
-   ax[i_seq].set_xlabel("$R$", fontproperties=font_math, fontsize=fs_ylabels+6)
+   ax[i_seq].set_xlabel("$R_0$", fontproperties=font_math, fontsize=fs_ylabels+6)
 
    # ax[1, i_seq].xaxis.set_major_locator(plt.MaxNLocator(6))
 
@@ -165,7 +165,11 @@ for i_seq in range(3):
       tick.label.set_fontproperties(font_math)
       tick.label.set_fontsize(22)
 
+
+# plt.show()
+# exit()
+
 if args.save:
    filename = f"figs/xp0_{setup_oscar.list_dic[i_dic]}.eps"
    # plt.rcParams['pdf.fonttype'] = 42
-   plt.savefig(filename, bbox_inches='tight')
\ No newline at end of file
+   plt.savefig(filename, bbox_inches='tight')