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Commit bcbebe3d authored by Elvira Clement's avatar Elvira Clement
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Update xp1

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# -*- 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,
......
# -*- 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)
......
# -*- 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
# -*- 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')
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