diff --git a/experiments/SIAM/xp_0_balls/make_fig_paper.sh b/experiments/SIAM/xp_0_balls/make_fig_paper.sh
deleted file mode 100755
index 02554698e3ce2952dc11b52195654208a26351f2..0000000000000000000000000000000000000000
--- a/experiments/SIAM/xp_0_balls/make_fig_paper.sh
+++ /dev/null
@@ -1,3 +0,0 @@
-python xp_a_accuracy_sol.py --id SIAM
-python xp_b_screening.py --id SIAM
-python xp_c_viz_paper.py --id SIAM
\ No newline at end of file
diff --git a/experiments/SIAM/xp_0_balls/process_data.py b/experiments/SIAM/xp_0_balls/process_data.py
deleted file mode 100644
index d8a4f63bcd5db7e8f43f704e9275d0e1713c2dd9..0000000000000000000000000000000000000000
--- a/experiments/SIAM/xp_0_balls/process_data.py
+++ /dev/null
@@ -1,56 +0,0 @@
-# -*- coding: utf-8 -*-
-import numpy as np
-
-from xps.SIAM.setup import Setup
-from xps.SIAM.xp_1_balls import xpparams
-
-
-def process(setup, log=True):
-
- # ---- load ----
- solutions_filename = f"results/xp_setup{setup.setup_id}.npz"
- solutions = np.load(solutions_filename, allow_pickle=True)
-
- screenings_filename = f"results/xp_setup{setup.setup_id}_screening.npz"
- screenings = np.load(screenings_filename, allow_pickle=True)
-
- # mat_results_gap[1, i_dic, i_seq, rep, i_ratio]
- mat_pvopt = solutions["mat_pvopt"]
-
- mat_nb_zero_detected = screenings['mat_nb_zero_detected']
- nb_test = mat_nb_zero_detected.shape[0]
- list_tests = screenings["list_test"]
-
- # ---- log ----
- if log:
- print("Experiment info")
- # print(f"- run with version {solutions["version"]}")
- print(f"- setup{setup.setup_id}")
- print("")
-
- # ---- processing ----
- mat_pc_detected =np.zeros(
- (nb_test, xpparams.nb_point, setup.nb_dic, setup.nb_sequence, setup.nb_ratio_lbd, setup.n_rep)
- )
-
- for i_dic in range(setup.nb_dic):
- for i_seq in range(setup.nb_sequence):
- for i_ratio in range(setup.nb_ratio_lbd):
- for rep in range(setup.n_rep):
-
- nb_0 = np.sum(mat_pvopt[i_dic, i_seq, i_ratio, rep, :] == 0)
- if nb_0 > 0:
- mat_detected = mat_nb_zero_detected[:, :, i_dic, i_seq, i_ratio, rep]
- mat_pc_detected[:, :, i_dic, i_seq, i_ratio, rep] = mat_detected / float(nb_0)
-
-
- # ---- return ----
- return {
- "mat_pc_detected": np.mean(mat_pc_detected, axis=5),
- "list_tests": list_tests,
- }
-
- # {
- # "results_mat_nb": results_mat_nb,
- # "results_mat_nbz": results_mat_nbz,
- # }
\ No newline at end of file
diff --git a/experiments/SIAM/xp_0_balls/xp_a_accuracy_sol.py b/experiments/SIAM/xp_0_balls/xp_a_accuracy_sol.py
deleted file mode 100755
index 795f54c63ff5a06c82c943601181c990126022c4..0000000000000000000000000000000000000000
--- a/experiments/SIAM/xp_0_balls/xp_a_accuracy_sol.py
+++ /dev/null
@@ -1,153 +0,0 @@
-# -*- coding: utf-8 -*-
-import time, argparse, sys
-
-import numpy as np
-
-# Algorithm import
-from src import __version__
-from src.solver.parameters import SlopeParameters, EnumLipchitzOptions
-from src.solver.slope import primal_func, dual_func, slope_gp
-
-# Generative models
-from src.utils import get_lambda_max, gamma_sequence_generator
-from src.dictionaries import generate_dic
-
-# Screening
-from src.screening.gap_test_all import GapTestAll
-
-# XP import
-from experiments.SIAM.slopepb import SlopePb
-from experiments.SIAM.setup import Setup
-from experiments.SIAM.xp_1_balls import xpparams
-
-parser=argparse.ArgumentParser()
-parser.add_argument('--erase', help='erase existing results', action="store_true")
-parser.add_argument('--id', help='setup id', type=str)
-args=parser.parse_args()
-
-
-# -------------------------
-# Load Setup
-# -------------------------
-
-setup = Setup(args.id)
-out_file_name = f"results/xp_setup{args.id}.npz"
-
-mat_seed = np.random.randint(
- 0, 2**32-1,
- size=(setup.nb_dic, setup.nb_sequence, setup.n_rep),
-)
-
-mat_pvopt = np.zeros(
- (setup.nb_dic, setup.nb_sequence, setup.nb_ratio_lbd, setup.n_rep, setup.n)
-)
-
-mat_dvopt = np.zeros(
- (setup.nb_dic, setup.nb_sequence, setup.nb_ratio_lbd, setup.n_rep, setup.m)
-)
-
-
-try:
- if args.erase:
- raise FileNotFoundError
-
- # Try to load existing results
- load_results = np.load(out_file_name, allow_pickle=True)
- mat_seed = load_results["mat_seed"]
- mat_pvopt = load_results["mat_pvopt"]
- mat_dvopt = load_results["mat_dvopt"]
-
-except FileNotFoundError:
- pass
-
-
-# -------------------------
-# Xp
-# -------------------------
-
-# For each trial
-# 1. Compute high accuracy solution
-# 2. Create ideal safe ball
-# 3. increase radius
-
-nb_xp = setup.nb_dic * setup.n_rep * setup.nb_sequence * setup.nb_ratio_lbd
-i_xp = 0
-for i_dic in range(setup.nb_dic):
- for i_seq, seq in enumerate(setup.list_sequence):
- for rep in range(setup.n_rep):
-
- np.random.seed(mat_seed[i_dic, i_seq, rep])
-
- # ---- 1. Gen data ----
- matA = generate_dic(
- setup.list_dic[i_dic],
- setup.m,
- setup.n,
- setup.normalize
- )
-
- lip = np.linalg.norm(matA, ord=2)**2
- vecy = np.random.randn(setup.m)
- vecy /= np.linalg.norm(vecy, 2)
-
-
- # ---- 2. Compute parameters ----
- vec_gammas = gamma_sequence_generator(
- setup.m,
- setup.n,
- setup.list_sequence[i_seq][0],
- setup.list_sequence[i_seq][1:]
- )
-
- lbd_max = get_lambda_max(vecy, matA, vec_gammas)
-
-
- # ---- 3. XP ----
- for i_ratio, ratio in enumerate(setup.list_ratio_lbd):
- i_xp += 1
-
- slopePb = SlopePb(matA, vecy, vec_gammas, ratio, lbdmax=lbd_max)
- vecx_hat = mat_pvopt[i_dic, i_seq, i_ratio, rep, :]
- vecu_hat = mat_dvopt[i_dic, i_seq, i_ratio, rep, :]
-
- gap = slopePb.eval_gap(vecx_hat, vecu_hat)
- print(f"xp {i_xp} / {nb_xp} --- (gap={gap})")
-
- if (gap > xpparams.stopping_gap):
- gap_old = gap
-
- # ---- 3a. Find solution ----
- params = SlopeParameters()
- params.vecx_init = np.copy(vecx_hat)
- params.lipchitz_constant = lip
- params.lipchitz_update = EnumLipchitzOptions.EXACT
- params.max_it = 1e7
- params.gap_stopping = xpparams.stopping_gap
- params.time_stopping = np.inf
- params.screening1 = GapTestAll(vec_gammas)
- params.eval_gap = True
- params.eval_gap_it = setup.eval_gap_it
- params.accelerated = False
- params.verbose = False
-
- out_slope = slope_gp(vecy, matA, ratio * lbd_max, vec_gammas, params)
-
- 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, :] = dv
-
- # Save
- np.savez(out_file_name,
- mat_seed=mat_seed,
- mat_pvopt=mat_pvopt,
- mat_dvopt=mat_dvopt,
- version = __version__,
- allow_pickle=True
- )
-
- # if i_xp ==3:
- # exit()
\ No newline at end of file
diff --git a/experiments/SIAM/xp_0_balls/xp_b_screening.py b/experiments/SIAM/xp_0_balls/xp_b_screening.py
deleted file mode 100644
index d9b65cda52ceb40369447f0aeec104e71512f500..0000000000000000000000000000000000000000
--- a/experiments/SIAM/xp_0_balls/xp_b_screening.py
+++ /dev/null
@@ -1,122 +0,0 @@
-# -*- coding: utf-8 -*-
-import argparse
-
-import numpy as np
-
-# Algorithm import
-from src import __version__
-from src.dictionaries import generate_dic
-from src.utils import get_lambda_max, gamma_sequence_generator
-
-# Screening
-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
-from experiments.SIAM.setup import Setup
-from experiments.SIAM.xp_1_balls import xpparams
-
-
-parser=argparse.ArgumentParser()
-parser.add_argument('--id', help='setup id', type=str, default=1)
-args=parser.parse_args()
-
-# -------------------------
-# Load Setup
-# -------------------------
-
-setup = Setup(args.id)
-solutions_filename = f"results/xp_setup{args.id}.npz"
-
-try:
- # Try to load existing results
- load_results = np.load(solutions_filename, allow_pickle=True)
- mat_seed = load_results["mat_seed"]
- mat_pvopt = load_results["mat_pvopt"]
- mat_dvopt = load_results["mat_dvopt"]
-
-except FileNotFoundError:
- print("No result found")
- sys.exit(1)
-
-
-# -------------------------
-# Screening Xp
-# -------------------------
-
-# percentage of detected zero
-mat_nb_zero_detected = np.full(
- (3, xpparams.nb_point, setup.nb_dic, setup.nb_sequence, setup.nb_ratio_lbd, setup.n_rep),
- np.nan,
- dtype=int
-)
-screening_filename = f"results/xp_setup{args.id}_screening.npz"
-
-i_xp = 0
-nb_xp = setup.nb_dic * setup.n_rep * setup.nb_sequence * setup.nb_ratio_lbd
-for i_dic in range(setup.nb_dic):
- for i_seq, seq in enumerate(setup.list_sequence):
- for rep in range(setup.n_rep):
-
- np.random.seed(mat_seed[i_dic, i_seq, rep])
-
- # ---- 1. Gen data ----
- matA = generate_dic(
- setup.list_dic[i_dic],
- setup.m,
- setup.n,
- setup.normalize
- )
-
- vecy = np.random.randn(setup.m)
- vecy /= np.linalg.norm(vecy)
-
-
- # ---- 2. Compute parameters ----
- vec_gammas = gamma_sequence_generator(
- setup.m,
- setup.n,
- setup.list_sequence[i_seq][0],
- setup.list_sequence[i_seq][1:]
- )
-
- lbd_max = get_lambda_max(vecy, matA, vec_gammas)
-
- # ---- 3. XP ----
- for i_ratio, ratio in enumerate(setup.list_ratio_lbd):
- i_xp += 1
- print(f"xp {i_xp} / {nb_xp}")
-
- slopePb = SlopePb(matA, vecy, vec_gammas, ratio, lbdmax=lbd_max)
- vecx_hat = mat_pvopt[i_dic, i_seq, i_ratio, rep, :]
- vecu_hat = mat_dvopt[i_dic, i_seq, i_ratio, rep, :]
- gap = slopePb.eval_gap(vecx_hat, vecu_hat)
- Atu = matA.T @ vecu_hat
-
- # ---- 3b. Build thin safe ball ----
- rgap = np.sqrt(2 * gap)
-
- # ---- 3c. Testing sphere ----
- list_tests = [
- GapTestPequalQ(),
- GapTestAll(vec_gammas),
- GapTestPequalOne(vec_gammas, np.arange(setup.n, dtype=np.double)),
- ]
-
-
- 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)
- mat_nb_zero_detected[i_test, i_offset, i_dic, i_seq, i_ratio, rep] = np.sum(out)
-
-
- # Save
- np.savez(
- screening_filename,
- mat_nb_zero_detected=mat_nb_zero_detected,
- list_test = [test.get_name() for test in list_tests],
- version = __version__,
- allow_pickle=True
- )
\ No newline at end of file
diff --git a/experiments/SIAM/xp_0_balls/xp_c_viz_paper.py b/experiments/SIAM/xp_0_balls/xp_c_viz_paper.py
deleted file mode 100644
index 8ecde14a22a13d95982d5beb4790ef894fe2cd31..0000000000000000000000000000000000000000
--- a/experiments/SIAM/xp_0_balls/xp_c_viz_paper.py
+++ /dev/null
@@ -1,139 +0,0 @@
-# -*- coding: utf-8 -*-
-from decimal import Decimal
-import json, argparse
-
-import numpy as np
-
-# XP import
-from xps.SIAM.slopepb import SlopePb
-from xps.SIAM.setup import Setup
-from xps.SIAM.xp_1_balls import xpparams
-from xps.SIAM.xp_1_balls.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="SIAM")
-parser.add_argument('--i_seq', type=int, default=0)
-args=parser.parse_args()
-
-import matplotlib
-if args.noshow:
- matplotlib.use('PS')
-else:
- matplotlib.use("TkAgg")
-
-import matplotlib.pyplot as plt
-from matplotlib.legend_handler import HandlerBase
-import matplotlib.font_manager as font_manager
-
-# -------------------------
-# Font stuff
-# -------------------------
-
-fs = 20
-
-font_math = font_manager.FontProperties(
- fname='../fonts/cmunrm.ttf',
- # weight='normal',
- # style='normal',
- math_fontfamily="cm",
- size=fs+2
-)
-
-font_text = font_manager.FontProperties(
- fname='../fonts/cmunrm.ttf',
- # weight='normal',
- # style='normal',
- math_fontfamily="cm",
- size=fs+2
-)
-
-font_ttt = font_manager.FontProperties(
- # fname='../fonts/ectt1000.ttf',
- fname='../fonts/computer-modern/cmuntt.ttf',
- weight='bold',
- style='normal',
- size=fs
-)
-
-
-# -------------------------
-# Load Results
-# -------------------------
-
-
-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
-# -------------------------
-
-i_dic = 2
-i_lbd = 1
-
-fs=22
-fs_ylabels = 20
-list_colors = ["tab:blue", "tab:orange", "tab:green"]
-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(f"- {setup_oscar.list_dic[i_dic]} dictionary")
-print(f"- lbd / lbd_max = {setup_oscar.list_ratio_lbd[i_lbd]}")
-
-
-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
-)
-
-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]
- )
-
-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
diff --git a/experiments/SIAM/xp_1_balls/launcher.sh b/experiments/SIAM/xp_1_balls/launcher.sh
index 31fa66dcf699cf03d476027d3c8b87069e47d2d3..4242a301059084f7d0d9bb90cf6712aad01ac08c 100755
--- a/experiments/SIAM/xp_1_balls/launcher.sh
+++ b/experiments/SIAM/xp_1_balls/launcher.sh
@@ -1,4 +1,4 @@
-python xp_a_accuracy_sol.py --id 1a
-python xp_b_screening.py --id 1a
-python xp_c_viz_fig1.py --noshow --save
-python xp_c_viz_fig2.py --noshow --save
\ No newline at end of file
+python xp_a_accuracy_sol.py --id SIAM
+python xp_b_screening.py --id SIAM
+python xp_c_viz_fig1.py --id SIAM --save
+python xp_c_viz_fig2.py --id SIAM --save
\ No newline at end of file
diff --git a/experiments/SIAM/xp_1_balls/xp_a_accuracy_sol.py b/experiments/SIAM/xp_1_balls/xp_a_accuracy_sol.py
index 9a6acb08e18ed2e7dcbfedf912cf6ef16152bdcf..aba672152b0748d34dac1801371003b7df92667d 100755
--- a/experiments/SIAM/xp_1_balls/xp_a_accuracy_sol.py
+++ b/experiments/SIAM/xp_1_balls/xp_a_accuracy_sol.py
@@ -1,5 +1,6 @@
# -*- coding: utf-8 -*-
import time, argparse, sys
+from pathlib import Path
import numpy as np
@@ -33,6 +34,7 @@ args=parser.parse_args()
# -------------------------
setup = Setup(args.id)
+Path("results").mkdir(parents=True, exist_ok=True)
out_file_name = f"results/xp_setup{args.id}.npz"
mat_seed = np.random.randint(
diff --git a/experiments/SIAM/xp_1_balls/xp_c_viz_fig1.py b/experiments/SIAM/xp_1_balls/xp_c_viz_fig1.py
index 00c45b70f8001c45e0c3c6e61dd54a54f11c4ccf..bb124daf3745c1e20aa64a44b957f701c06570d9 100644
--- a/experiments/SIAM/xp_1_balls/xp_c_viz_fig1.py
+++ b/experiments/SIAM/xp_1_balls/xp_c_viz_fig1.py
@@ -1,5 +1,6 @@
# -*- coding: utf-8 -*-
import argparse
+from pathlib import Path
import numpy as np
@@ -132,7 +133,10 @@ ax.set_xlim([1e-6, 1e0])
ax.set_ylim([-2, 102])
if args.save:
- filename = f"figs/xp_illustration_screening{args.i_seq}.eps"
+ folderfig = "figs"
+ Path(folderfig).mkdir(parents=True, exist_ok=True)
+
+ filename = folderfig + f"/xp_illustration_screening{args.i_seq}.eps"
plt.savefig(filename, bbox_inches='tight')
if not args.noshow:
diff --git a/experiments/SIAM/xp_1_balls/xp_c_viz_fig2.py b/experiments/SIAM/xp_1_balls/xp_c_viz_fig2.py
index 1048707222072ac1ba54d7c53d376077006195e4..dfcf0c1475082a9f9b7e8123bb899ea5df4630dd 100644
--- a/experiments/SIAM/xp_1_balls/xp_c_viz_fig2.py
+++ b/experiments/SIAM/xp_1_balls/xp_c_viz_fig2.py
@@ -1,5 +1,6 @@
# -*- coding: utf-8 -*-
import argparse
+from pathlib import Path
import numpy as np
@@ -170,6 +171,9 @@ for i_seq in range(3):
# exit()
if args.save:
- filename = f"figs/xp0_{setup_oscar.list_dic[i_dic]}.eps"
+ folderfig = "figs"
+ Path(folderfig).mkdir(parents=True, exist_ok=True)
+
+ filename = folderfig + f"/xp0_{setup_oscar.list_dic[i_dic]}.eps"
# plt.rcParams['pdf.fonttype'] = 42
plt.savefig(filename, bbox_inches='tight')