From 9707ef3e9876e7fb4cb96cd7e679749ddb136845 Mon Sep 17 00:00:00 2001 From: Manos Date: Thu, 7 Oct 2021 12:32:46 +0200 Subject: [PATCH] code: Corrections and cleaning up --- code/expt/copenhagen.py | 22 ++++----- code/lib/lmdk_bgt.py | 15 +++--- code/lib/lmdk_lib.py | 4 +- code/lib/lmdk_sel.py | 44 ++++++++++++------ rslt/bgt_cmp/Copenhagen-sel-pareto.pdf | Bin 14644 -> 0 bytes rslt/bgt_cmp/Copenhagen-sel.pdf | Bin 14643 -> 0 bytes rslt/bgt_cmp/Copenhagen.pdf | Bin 15649 -> 14644 bytes rslt/bgt_cmp/HUE-001.pdf | Bin 15480 -> 0 bytes rslt/bgt_cmp/HUE-log.pdf | Bin 15353 -> 0 bytes rslt/bgt_cmp/HUE-new.pdf | Bin 16237 -> 0 bytes rslt/bgt_cmp/HUE-sel-pareto.pdf | Bin 15980 -> 0 bytes rslt/bgt_cmp/HUE-sel.pdf | Bin 15981 -> 0 bytes rslt/bgt_cmp/T-drive-sel-pareto.pdf | Bin 15623 -> 0 bytes rslt/bgt_cmp/T-drive-sel.pdf | Bin 15615 -> 0 bytes .../Bimodal landmark distribution.pdf | Bin 14587 -> 0 bytes .../Left-skewed landmark distribution.pdf | Bin 14865 -> 0 bytes .../Right-skewed landmark distribution.pdf | Bin 14863 -> 0 bytes .../Symmetric landmark distribution.pdf | Bin 14852 -> 0 bytes .../Uniform landmark distribution.pdf | Bin 14583 -> 0 bytes .../Bimodal landmark distribution.pdf | Bin 13730 -> 0 bytes .../Left-skewed landmark distribution.pdf | Bin 13725 -> 0 bytes .../Right-skewed landmark distribution.pdf | Bin 13729 -> 0 bytes .../Symmetric landmark distribution.pdf | Bin 13721 -> 0 bytes .../Uniform landmark distribution.pdf | Bin 13729 -> 0 bytes rslt/lmdk_sel_cmp-pareto/lmdk_sel_cmp.pdf | Bin 16076 -> 0 bytes rslt/lmdk_sel_cmp/lmdk_sel_cmp-emd.pdf | Bin 14362 -> 0 bytes rslt/lmdk_sel_cmp/lmdk_sel_cmp-norm.pdf | Bin 14805 -> 0 bytes 27 files changed, 49 insertions(+), 36 deletions(-) delete mode 100644 rslt/bgt_cmp/Copenhagen-sel-pareto.pdf delete mode 100644 rslt/bgt_cmp/Copenhagen-sel.pdf delete mode 100644 rslt/bgt_cmp/HUE-001.pdf delete mode 100644 rslt/bgt_cmp/HUE-log.pdf delete mode 100644 rslt/bgt_cmp/HUE-new.pdf delete mode 100644 rslt/bgt_cmp/HUE-sel-pareto.pdf delete mode 100644 rslt/bgt_cmp/HUE-sel.pdf delete mode 100644 rslt/bgt_cmp/T-drive-sel-pareto.pdf delete mode 100644 rslt/bgt_cmp/T-drive-sel.pdf delete mode 100644 rslt/lmdk_sel-pareto/Bimodal landmark distribution.pdf delete mode 100644 rslt/lmdk_sel-pareto/Left-skewed landmark distribution.pdf delete mode 100644 rslt/lmdk_sel-pareto/Right-skewed landmark distribution.pdf delete mode 100644 rslt/lmdk_sel-pareto/Symmetric landmark distribution.pdf delete mode 100644 rslt/lmdk_sel-pareto/Uniform landmark distribution.pdf delete mode 100644 rslt/lmdk_sel/Bimodal landmark distribution.pdf delete mode 100644 rslt/lmdk_sel/Left-skewed landmark distribution.pdf delete mode 100644 rslt/lmdk_sel/Right-skewed landmark distribution.pdf delete mode 100644 rslt/lmdk_sel/Symmetric landmark distribution.pdf delete mode 100644 rslt/lmdk_sel/Uniform landmark distribution.pdf delete mode 100644 rslt/lmdk_sel_cmp-pareto/lmdk_sel_cmp.pdf delete mode 100644 rslt/lmdk_sel_cmp/lmdk_sel_cmp-emd.pdf delete mode 100644 rslt/lmdk_sel_cmp/lmdk_sel_cmp-norm.pdf diff --git a/code/expt/copenhagen.py b/code/expt/copenhagen.py index adb7610..0da5a07 100644 --- a/code/expt/copenhagen.py +++ b/code/expt/copenhagen.py @@ -27,7 +27,7 @@ def main(args): # The landmarks percentages lmdks_pct = [0, 20, 40, 60, 80, 100] # The privacy budget - epsilon = 1.0 + epsilon = .1 # Number of methods n = 3 @@ -68,32 +68,26 @@ def main(args): # Skip rls_data_s, bgts_s = lmdk_bgt.skip_cont(seq, lmdks, epsilon) # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_s) - mae_s[i] += lmdk_bgt.mae_cont(rls_data_s)/args.iter + mae_s[i] += (lmdk_bgt.mae_cont(rls_data_s)/args.iter)*100 # Uniform rls_data_u, bgts_u = lmdk_bgt.uniform_cont(seq, lmdks, epsilon) # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_u) - mae_u[i] += lmdk_bgt.mae_cont(rls_data_u)/args.iter + mae_u[i] += (lmdk_bgt.mae_cont(rls_data_u)/args.iter)*100 # Adaptive rls_data_a, _, _ = lmdk_bgt.adaptive_cont(seq, lmdks, epsilon, .5, .5) - mae_a[i] += lmdk_bgt.mae_cont(rls_data_a)/args.iter + mae_a[i] += (lmdk_bgt.mae_cont(rls_data_a)/args.iter)*100 # Calculate once if i == 0: # Event rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 0), epsilon) - mae_evt += lmdk_bgt.mae_cont(rls_data_evt)/args.iter + mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100 # User rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 100), epsilon) - mae_usr += lmdk_bgt.mae_cont(rls_data_usr)/args.iter - - mae_u *= 100 - mae_s *= 100 - mae_a *= 100 - mae_evt *= 100 - mae_usr *= 100 - + mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100 + exit() plt.axhline( y = mae_evt, color = '#212121', @@ -172,7 +166,7 @@ if __name__ == '__main__': main(parse_args()) end_time = time.time() print('##############################') - print('Time : %.4fs' % (end_time - start_time)) + print('Time elapsed: %s' % (time.strftime('%H:%M:%S', time.gmtime(end_time - start_time)))) print('##############################') except KeyboardInterrupt: print('Interrupted by user.') diff --git a/code/lib/lmdk_bgt.py b/code/lib/lmdk_bgt.py index 0e6c764..8ff6a7f 100644 --- a/code/lib/lmdk_bgt.py +++ b/code/lib/lmdk_bgt.py @@ -492,7 +492,8 @@ def skip_cont(seq, lmdks, epsilon): lmdks - The landmarks. epsilon - The available privacy budget. Returns: - rls_data - The perturbed data. + rls_data - The new data. + [0: The true answer, 1: The perturbed answer] bgts - The privacy budget allocation. ''' # Event-level budget allocation @@ -501,15 +502,15 @@ def skip_cont(seq, lmdks, epsilon): rls_data = [None]*len(seq) for i, p in enumerate(seq): # Check if current point is a landmark - r = any((lmdks[:]==p).all(1)) + is_landmark = any(np.equal(lmdks, p).all(1)) # Add noise - o = lmdk_lib.randomized_response(r, bgts[i]) - if r: + o = lmdk_lib.randomized_response(is_landmark, bgts[i]) + if is_landmark: if i > 0: # Approximate with previous o = rls_data[i - 1][1] - bgts[i] = 0 - rls_data[i] = [r, o] + bgts[i] = 0 + rls_data[i] = [is_landmark, o] return rls_data, bgts @@ -720,7 +721,7 @@ def uniform_cont(seq, lmdks, epsilon): # Budgets bgts = uniform(seq, lmdks, epsilon) for i, p in enumerate(seq): - r = any((lmdks[:]==p).all(1)) + r = any(np.equal(lmdks, p).all(1)) # [original, perturbed] rls_data[i] = [r, lmdk_lib.randomized_response(r, bgts[i])] return rls_data, bgts diff --git a/code/lib/lmdk_lib.py b/code/lib/lmdk_lib.py index 0d1bf80..3820b6e 100644 --- a/code/lib/lmdk_lib.py +++ b/code/lib/lmdk_lib.py @@ -959,13 +959,13 @@ def find_lmdks_cont(lmdk_data, seq, uid, pct): landmarks percentage. 0: uid, 1: lmdk_pct, 2: contacts seq - The users' data. - 0: tim, 1: uid, 2: cont, 3: rssi + 0: tim, 1: uid, 2: cont, 3: rssi uid - The user's id that we are interested in. pct - The landmarks percentage. Returns: lmdks - The user's landmarks contacts for the given landmarks percentage. - 0: uid_b + 0: tim, 1: uid, 2: cont, 3: rssi ''' # Initialize user's landmarks lmdks = np.empty(0).reshape(0,4) diff --git a/code/lib/lmdk_sel.py b/code/lib/lmdk_sel.py index cdbef0f..eb2071a 100644 --- a/code/lib/lmdk_sel.py +++ b/code/lib/lmdk_sel.py @@ -5,8 +5,8 @@ from lmdk_lib import * import exp_mech import numpy as np import random +import scipy.stats as stats import time -from scipy.spatial.distance import cdist ''' @@ -163,7 +163,7 @@ def get_opts_from_top_h(seq, lmdks): # The options to be returned hist_opts = [] # Keep adding points until the maximum is reached - while np.sum(hist_cur) < max(seq): + while np.sum(hist_cur) < len(seq): # Track the minimum (best) evaluation diff_min = float('inf') # The candidate option @@ -175,8 +175,8 @@ def get_opts_from_top_h(seq, lmdks): hist_tmp = np.copy(hist_cur) hist_tmp[i] += 1 # Find difference from original - # diff_cur = get_norm(hist, hist_tmp) # Euclidean - diff_cur = get_emd(hist, hist_tmp) # Wasserstein + diff_cur = get_norm(hist, hist_tmp) # Euclidean + # diff_cur = get_emd(hist, hist_tmp) # Wasserstein # Remember if it is the best that you've seen if diff_cur < diff_min: diff_min = diff_cur @@ -326,19 +326,37 @@ def find_lmdks(seq, lmdks, epsilon): opts = get_opts_from_top_h(get_seq(1, len(seq)), lmdks_seq) # Landmarks selection budget eps_sel = epsilon/(len(lmdks_seq) + 1) - # Get private landmarks timestamps - lmdks_seq, _ = exp_mech.exponential(hist, opts, exp_mech.score, 1.0, eps_sel) + # Get landmarks histogram with dummy landmarks + hist_new, _ = exp_mech.exponential(hist, opts, exp_mech.score, 1.0, eps_sel) + # Split sequence in parts of size h + pt_idx = [] + for idx in range(1, len(seq), h): + pt_idx.append([idx, idx + h - 1]) + pt_idx[-1][1] = len(seq) + # Get new landmarks indexes + lmdks_seq_new = np.array([], dtype=int) + for i, pt in enumerate(pt_idx): + # Already landmarks + lmdks_seq_pt = lmdks_seq[(lmdks_seq >= pt[0]) & (lmdks_seq <= pt[1])] + # Sample randomly from the rest of the sequence + size = hist_new[i] - len(lmdks_seq_pt) + rglr = np.setdiff1d(np.arange(pt[0], pt[1] + 1), lmdks_seq_pt) + # Add already landmarks + lmdks_seq_new = np.concatenate([lmdks_seq_new, lmdks_seq_pt]) + # Add new landmarks + if size > 0 and len(rglr) > size: + lmdks_seq_new = np.concatenate([lmdks_seq_new, + np.random.choice( + rglr, + size = size, + replace = False + ) + ]) # Get actual landmarks values - lmdks_new = seq[lmdks_seq] + lmdks_new = seq[lmdks_seq_new - 1] return lmdks_new, epsilon - eps_sel def test(): - - A = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]) - B = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) - print(get_norm(A, B)) - exit() - # Start and end points of the sequence # # Nonrandom # start = 1 diff --git a/rslt/bgt_cmp/Copenhagen-sel-pareto.pdf b/rslt/bgt_cmp/Copenhagen-sel-pareto.pdf deleted file mode 100644 index a0d05cc75c2431312afcc6fc94de0dd1a2ef3b72..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 14644 zcmb_@2Rv18_;_e=vm&y}wNi?^+{;Dw$_^Q!TwJ4YjZ0*enT*UN*?W^hL?k;aAtX_h zkd@Jp|2anAl>hJJ^ZWd+&-*#Y^Sbr zT!x5=L17v=3%nx~2|zTVFl|>mJQOB_BjT(H7Ep0<2;SBV94P$91UVO?f))`+#6tx) zCdm_QiBQzWy#|g*#5>qR(cr%jn1%zvR0~gp8US=;F!esHzR;GAO1%Nv6pSAuNfTTE?m^rb zBwPT6K?q~fP(dV00FD(xgDh)+(}`OO)WkayoE%I6je;rzG_avjP|1I&6J%{m|MFJW zfX1LOd22wWvUpR18DIewysZV%5{lR`3&4yc(E*RMfw%<)^mV#NHM1$9uoK@_VH$G~78%{%F4Osgj3=LZhs`f|i79;{O4NQ0DR9~Dd1Q$N52g$6B> zX9y?ipXNgQeyXj|8^JvC$vkZEU{3FJkeuRvX=%n*#q(o(5FhwTRj1!k)SJv7H{+c@ z7=)_6-UO4cQJ~k%aeYp|Z$&Iw+~5+MubxOUolfe*%n$RmdNiCl!LOn^uzPQEd0Eaz znH+FcZ{8=%;&YRat6kJ5d*wB&EWn`i-DPgf0Uw@&gC=P?5RTNDpHeCGN=MDleA{z| zd&buaF)DVKt?Sy!}|kKuGqGrQiH& zl4g6g{ozo0NdUEH!fSG#0olWyfzd@QcyU)LRcixL(jXu)S#cOEo`yFQw07MbZ;J=0s{Dvm4DTC)vi$i6+cNHiG)#9*HlNGQ9(;W| zyObDe+#h?9FKL0B`aWgNtfUi(rex-@iWkKBirD?y%ulUb?|>i)X;0JB`MXjhzCn zSY{D?QH-#VP7J5hrxOusP-!DFeIp;|EXS_c!%f(wa{*jV;(H#s>KmGn;+!ZkPL$Ic zA1AJzdgS~@!H6weMqyQ9Z~rs+v(HS{pP2@dscR!e(;mcBh-n@c z=JPoyOD^ork#2gO@~$Voxdl~L(|J9q^4wVGn)f=^MOvcnJ(gUY=johes~QmFt8G>T zmR)UD5l*Yo<ZG0{J|OOepO{~B|d?Wb9CttA;MrdKJ+ABKt@C6F#WTCh-$S)JFo z+AFebV&kzkNi*KO0k%}foNxlKhidECnZ%An+GCdFIw7JbTvT3p^SYR`e!|aIBoBIj zJmHq_ROxfX%XrqE|A)*ase)o3??zdE7jKKw8yEK%vR3fBRF7lk*z6E$tWS6$eI7D> zmKQ$U#bd_r*hi8D)KlLp%EOgVECsrm5Dj#_b)#DjDZ73>G&!j|t&v!US{0Y5?6FvT z<5B&~S)y;Dessaaop3PvMgf8n%R{9X?8ih;`*G>W3-m0P;=05$pz1H<9&!Uq-%I=^EFI;53~Op07)Mtg*ArS4Vai5A?;HMEMe;~sq`2@6Ih zkx1qyTQR>B7i#u-9t}q8h|dQ3=-%U1&V#U$=4(Tr?Lx0gVXB&6guf&cj61fpP^c?;ZRY{4Aw@^VL05bR9`W5nfRdR zkJMKkMKeM{r6M+0^zjC2Kg62XN`uqev4j<|w+hV;t*O~>(|h{I-3Epmt(MJ92#!~S z4mo>AB$@fuQ%_o<0!TB1+{Hz z?kjSj3QD)q-$QaSXL*lNv_&xrCl)YU({*5YyjzVppzX1@k}hcNp00Okv%9(uW4U)i z(129D>7W!#(ggR16)`)td%e}K$;bF~Nv&e`-anOKWWs5BFC(kMv(44km*REQ*k!)w zo(5%K^Ha=`;q(yOGaA!9`~3Lm9Md$=WhDHUVLwfOm1B$@MOiwBMp45zsgc1dEC=z% zmv09}#E(YyoL`jpf>DsyzFRvT?MNs2qTFa7>ZD%|V(v;sJ5JhxVNAJ&!md3v;c>i5 z!N}hG^dBGX|2(#eSRqj(1d~=9Un~#nb@0)n}HCO7WZN0c|_#Rgu z=`3+|ts_tNoQa-&uy*_7!cW&~&ppVXWaAwy|7QaIKRtMezgE3!m{h0?2c^vN{bxtA zd}Zj~i9OA!`1Hn0lsX>PMmpAP%!|91Y^o-Pc}ez|F~OQEbiP}DW*_5ToRO?y2zEr% z-!!L4Ek*$4q04qvr}%`v#^c0>{Yp=--_bn0 zWVCy4T+DDAD1x{hy)xf!^Ymw+{V9ptedk8s>-AH&7A<$%EQpI3Tq=|c=k}lEsEf+4f|ZY6f&SI)Ee2Fl&43$Ri*JNO`1@v zh{$9*xuDYU)_T^Y(#Fpw_mzDCk?NJXILctGz4{~P*Tw)3r~SvfMOrWJA(rV5;R;2A zFUHf0LG>9qjc!s|WZz_>Fk}A}ZNSV~cTuS~EPkRh@#P_Yvy08MGc>cFzr;w~uKyI{ zxVci%ZEnJMzd#diuIzkI)Sh!iLAt3DZdo$L>t6`FbN3lt6RSrQPD)aA1^cj><_x+p zM8h=2IyfwZxKb{0WG13_a20r%7Cf|Or*E|VJ+rg0F zo^v;bL<(WH8B+Be)|O0)a&npB=k*(1=teiTy(dT4$~Ycj!b}u=sc*f~QKfwG{C(2t z;wQ8Cn4}Ir-PEH^VwWk{Asww($vOf9>S8e#18R2ErIhvB49=OS_Ia|Nw&19#*9pCA zq>BnxP8qJ{mZJ()>AG=2xUSE?mtHZOe3G4SkPxNtH873NrZxDjR>x^U|ZE8dbmHj6VRZ5-E|3uAgTiydD0{`jRU`!!cIq-{ale!oP3 zgW0%h#AU90=2iE*X9yn}ARe#9@Apvz2Lu{+WLCKAZMle zfr1VWC_|o7?~p)p13P!Pd@cK_2aBr*MrSV{+(EhE=6-j|MQl^99H89il9ZDl8NSz$ zihOjr?IU-qZEY~@fsZz)7#&Pk_1xK*zHl*tR^@8zw0lz#iHAhfRZJ>YqHdlXcL?d^ zg1KLa3^;bC0JlJUH&?GoT$AxuaUYO8zCu*0x20>p5*B@vlVKnSANfG| zv|ehip@C&28?-xay1Q3-QtAcS-cxH$HEyX8U;n(cCWFb{a- z7~tGAToHbPoYg*$@G?^9O=BUCMZtBR=|G2MC0Y76N%=qg<(sA7OVz1I9V~wPG||;pEe^RchjCq+(38NqBrkcgHo(u zPL851v$4)nYGzY3Pd@76$gkn|$7aqwQ9GD;NU7G0hC>t6hU8@((v;T7aKyNf8su^f z6%8|t^gFIScVm9}$~@Wdm-;d?^WCP(B)mQAsxKXGyjAFt zZ>|^ZkuYCmid7aeWsmNlPkma2k?>GKcqK%amL)YB6a;bbJFt+NWX2b{?<;j_JcAzER8^B-f2zK6Q5t3e~LausPT}+tqGb zSdhqzI2omTw3F9KNiMq)9ky@6{mMfQjar=mt>YRi0!Iv*TSr3OCe@yQcxid@g9~3& zGePy*-JrK;kFU6nGo6TwS5JD+d%t7h<4JRj$06<19}n_h^eKN1F}~-4Y!Z4KSP(v) z_=<*C#kBp}DeIpkXK!4IlIx)~S-oA}$q-nr%yZ%VlNGC|3T0he^F!0~qq!;SK}BBL zWn|_@gnxRTyLys>CulskfIHKiw=H<^t@cDp7wr&700S<=1QG}?+E)5S*y<{~(4KlRS(=Z*3ml4x2vuQ$glW2#IO7^jC) z@$Qy6Wz9!@huo0m`5;nz&QGCB8)>5S>P&Jp zzJ74QTZQUzNKc5*N4+1@#oZ&gWrt-6!?DvdFphfRPdiAs+pP`auiRShwiGoff|6{; zLoT87`B~PtWYTOcYlXu5N@Lm-FS@DGGTE>fBI1j7lHWffEC1$#~iXJkmRvY5&KV?dvsZoPg-OrO0x|$ z(bbt^1FIH!(=zyz?-$61YT#}=NVD5rlF;^GfI=cQ;Tmw%0XqMT49K{A2Dnj^td0## zmKL~4Lf10leO6iz+RS!0hpm88poqkHEJL1ALyr6oiEJ^6o)ycUIXENsUv^Nt-MC

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