KiF+SSKrSSKJrJrJrJrJrJrJrJ r J r J r J r SSK Jr SSKrSSKrSSKrSSKJr SSKJr SSKJr SSKJr SSKJrJr SS KJr SS K J!r!J"r"J#r# SS KJ$r$ S r%S r&Sr'S0S\ \$\RP\\$\\RP4S\)S\\)S\*S\\\*S\\\*S\\\*S\\S\\S\\+S\\\44Sjjr,S1S\ \$\RP\\$\\RP4S\)S\\)S\*S\\\*S\\\*S\\\*S\)S\-S\.S\-S\-S \)S!\.S"\.S#\.S\\S$\\S\\+S\\\44(S%jjr/S2S\RPS\)S\)S&\\*S'\\*S(\*S)\-S"\.S*\)S\-SS4S+jjr0S3S\RPS\)S\)S&\\*S'\\*S(\\*S)\-S"\.S*\)SS4S,jjr1S4S-\)S\)S\)S)\-S(\*SS4 S.jjr2S4S-\)S\)S\)S)\-S(\*SS4 S/jjr3g)5N) AnyCallableDictListLiteralOptionalTupleTypeVarUnioncastget_args)warn)cm)pyplot)Axes) Normalize)Figure FigureBase) Rectangle)binom gaussian_kdeiqr)TensorcSSKJn UR"SSSSS9upV[S5HnXgnUR USS2U4R 5R 5R5SSS 9 UR USS2U4R 5R 5R5SS S 9 URX'5 M USRSS /5 UR"5 UR"US S 9 g) Nr )F)nrowsncolsfigsizesharexstepValid)histtypelabelFulltight bbox_inches) matplotlib.pyplotrsubplotsrangehistdetachcpunumpy set_titlelegend tight_layoutsavefig) thetapriorslabelsfignamepltfigaxesxaxs S/global/cfs/cdirs/lsst/www/DESC_TD_PUBLIC/users/bastienc/kestrel/dustbi_plotting.pyplot_surviving_priorsr@"s# 2QNIC 2Y W ad ""$((*002V7S q!t ##%))+113fFS VY   GNNGV$%KKW-ct[R"SS9n[R"5nURXSSS9 URXSSSS 9 UR S 5 UR S 5 UR S S 5 URS S 5 URSS9 [R"USS9 X44$)Nrrr!blueTARP)colorr&black--ideal)rG linestyler&zCredibility Level $\alpha$zExpected Coverage Probabilitygg?F)frameonr(r)) r:figuregcaplot set_xlabel set_ylabelset_xlimset_ylimr3r5)ecpalphasavenamer;r>s r? plot_tarprW8s **V $CwwyBGGEfFG3GGE4wGGMM/0MM23KKSKKSIIeIKKg. 7NrAcJSSKJn UR"SS9nUR"5nURSnURSnUR "USSS9 UR "US SS S 9 UR "S 5 UR"S 5 UR"SSSS9 URSS/RS5 URSS/RS5 URSS/RS5 URSSSSS9 UR"USS9 g)NrrCrD training_lossvalidation_losstrain)r&lw validationrI)r&r]lsEpochLossF linecolor)rL labelcolorfontsizebottomleftdimgreytoprightboth)axiswhichcolors labelsizer(r))r+rrMrN_summaryrOxlabelylabelr3spines set_color set_visibleset_lw tick_paramsr5) inferencerVr:r;r> train_losses val_lossess r? plot_lossr}Gs# **V $CwwyB%%o6L##$56JHH\Q0HHZ|d;JJwJJvJJurBIIx !++I6IIug++E2IIx !((+NNfY"NMKKg.rAranksnum_posterior_samplesnum_bins plot_typeparameter_labels ranks_labelsrpr;r>r!returnc .[UUUUUUU4UUU S.U D6$)aPlot simulation-based calibration ranks as empirical CDFs or histograms. Additional options can be passed via the kwargs argument, see _sbc_rank_plot. Args: ranks: Tensor of ranks to be plotted shape (num_sbc_runs, num_parameters), or list of Tensors when comparing several sets of ranks, e.g., set of ranks obtained from different methods. num_bins: number of bins used for binning the ranks, default is num_sbc_runs / 20. plot_type: type of SBC plot, histograms ("hist") or empirical cdfs ("cdf"). parameter_labels: list of labels for each parameter dimension. ranks_labels: list of labels for each set of ranks. colors: list of colors for each parameter dimension, or each set of ranks. Returns: fig, ax: figure and axis objects. )r;r>r!)_sbc_rank_plot) r~rrrrrrpr;r>r!kwargss r? sbc_rank_plotrcsAB         rA num_repeats line_alphashow_uniform_regionuniform_region_alphaxlim_offset_factornum_colsparams_in_subplots show_ylabelsharey legend_kwargsc[U[[R45(aU/nO[U[5(deUn[ U5HWunn[U[[R45(de[U[5(dMDUR 5UU'MY SS/nUU;dS5eUc [SSS9nUSRunn[U5nUS :dUS:XaS n UH'nURUSR:XaM"S 5e [[R"UU - 55nUcU (a US -US -4OSnUc![U5Vs/sH nSUS -3PM nnUc![U5Vs/sH nSUS -3PM nnUcUS-n[U[5(deU (GaUbUc;[R"U[UU 5UUS9unn[R "U5nO8UR"U:dS5eUR$S :aURSOS nUceSunn[ U5GHun n[U5GHn!US :XaU!OU!U -nU!U -n[R&"US :XaUUOUUU45 US:XaM[)USS2U!4UUUU UcSU 3OUU SUU!3U!S:HUS9 U S:XaU (a[+UUUU S9 MMMUS:Xa][-USS2U!4UUUU UcSOUU SUU!3UUU S9 [/UUUU S9 U!S:Xa UU b[R0"S!0UD6 MMM[3SUSU35e GM US - nUS :a/UU :a)UUU4R5S5 US - nUS :aUU :aM)UU4$UbUc[R"S S US9unn[R&"U5 USn[U5H.n![)USS2U!4UUUU!UcSU!3OUU!S U!US - :HUS9 M0 U (a [+UUUU S9 [R0"S!0UD6 UU4$s snfs snf)"agPlot simulation-based calibration ranks as empirical CDFs or histograms. Args: ranks: Tensor of ranks to be plotted shape (num_sbc_runs, num_parameters), or list of Tensors when comparing several sets of ranks, e.g., set of ranks obtained from different methods. num_bins: number of bins used for binning the ranks, default is num_sbc_runs / 20. plot_type: type of SBC plot, histograms ("hist") or empirical cdfs ("cdf"). parameter_labels: list of labels for each parameter dimension. ranks_labels: list of labels for each set of ranks. colors: list of colors for each parameter dimension, or each set of ranks. num_repeats: number of repeats for each empirical CDF step (resolution). line_alpha: alpha for cdf lines or histograms. show_uniform_region: whether to plot the region showing the cdfs expected under uniformity. uniform_region_alpha: alpha for region showing the cdfs expected under uniformity. xlim_offset_factor: factor for empty space left and right of the histogram. num_cols: number of subplot columns, e.g., when plotting ranks of many parameters. params_in_subplots: whether to show each parameter in a separate subplot, or all in one. show_ylabel: whether to show ylabels and ticks. sharey: whether to share the y-labels, ticks, and limits across subplots. fig: figure object to plot in. ax: axis object, must contain as many sublpots as parameters or len(ranks). figsize: dimensions of figure object, default (8, 5) or (len(ranks) * 4, 5). Returns: fig, ax: figure and axis objects. r.cdfz?plot type {plot_type} not implemented, use one in {plot_types}.Nbest皙?)loc handlelengthrrTz+all ranks in list must have the same shape.)rzdim z rank set )r!rz6There must be at least as many subplots as parameters.)rrCzposterior ranks ) ranks_labelrGrsrrU)rU firebrickzposterior rank )rrGrsrrUrz plot_type z not defined, use one in offrDposterior rank) isinstancernpndarrayr enumerater1dictshapelenintceilr-r:r,min atleast_1dsizendimsca_plot_ranks_as_cdf*_plot_cdf_region_expected_under_uniformity_plot_ranks_as_hist+_plot_hist_region_expected_under_uniformityr3 ValueErrorrn)"r~rrrrrrprrrrrrrrrr;rr>r! ranks_listidxrank plot_types num_sbc_runsnum_parameters num_ranksrankinum_rowsicol_idxrow_idxiijjs" r?rrsp%&"**-..W %&&&& z* T$ 45555 dF # #*.**,JsO+ %J  "I "c: #-a=#6#6 L.JI1} V+!{{jm111 9 1 277>H456H8J>A%x!|4PV49.4IJ4Iqd1q5'N4IJ5:95EF5E)AE7+5E F2% h $ $$ $ ;"*llNH- GC r"B77n, H ,')ggkrxx{qH~~":.IBN+ (A "2=.x1}7 "Wg=M:NO%&ae  #$0$4*0."hfRj!12B22F1GH$&!G( Qw#6B($'"6 $7w&('ae  -$0$4-3^k!01A"1E0FG$/(+= @$ -2 Qw<#3#? 3]3$@w%$YK/H Uc,/l 1 lw1 w % %e , qLGlw1B 7N7 ;"*ll1a9GC  1 'B ae ,R0"(."hfRj'>A#56  (  6*   #]# 7NeKFs 'Q QrrsrGrU num_ticksc [X)-5n [R"UUUUUS9 U(a[R"S5 O[R"/5 [R "U *X*-5 [R "[R"SX(55 [R"UcS5 gU5 g)aPlot ranks as histograms on the current axis. Args: ranks: SBC ranks in shape (num_sbc_runs, ) num_bins: number of bins for the histogram, recommendation is num_sbc_runs / 20. num_posteriors_samples: number of posterior samples used for ranking. ranks_label: label for the ranks, e.g., when comparing ranks of different methods. xlabel: label for the current parameter. color: histogram color, default from Talts et al. alpha: histogram transparency. show_ylabel: whether to show y-label "counts". show_legend: whether to show the legend, e.g., when comparing multiple ranks. num_ticks: number of ticks on the x-axis. xlim_offset_factor: factor for empty space left and right of the histogram. legend_kwargs: kwargs for the legend. )binsr&rGrUcountsrNr) rr:r.rtyticksxlimxticksrlinspacers) r~rrrrsrGrUrrr xlim_offsets r?rrcs:+@AKHH   8 2HHk\0>?JJr{{13?@JJ6>>v>rAc [R"XSS9tpU R5n [R"[R "SXU-5[R "XR5- U5UUUS9 U(aC[R"[R "SSS55 [R"S5 O-[R"[R "SSS5/5 [R"SS5 [R"SU5 [R"[R "SX55 [R"UcS 5 gU5 g) aPlot ranks as empirical CDFs on the current axis. Args: ranks: SBC ranks in shape (num_sbc_runs, ) num_bins: number of bins for the histogram, recommendation is num_sbc_runs / 20. num_repeats: number of repeats of each CDF step, i.e., resolution of the eCDF. ranks_label: label for the ranks, e.g., when comparing ranks of different methods. xlabel: label for the current parameter color: line color for the cdf. alpha: line transparency. show_ylabel: whether to show y-label "counts". show_legend: whether to show the legend, e.g., when comparing multiple ranks. num_ticks: number of ticks on the x-axis. legend_kwargs: kwargs for the legend. F)rdensityr)r&rGrUrr\z empirical CDFNr)r histogramcumsumr:rOrrepeatmaxrrtylimrrrs) r~rrrrsrGrUrrr._histcss r?rrs:||E%@HD [[]FHH Axx!78 &::<'5  2;;q!Q'( ?# 2;;q!Q',HHQNHHQJJr{{1h23JJ6>>v>rArc [USU- S9RS5[R"U5-nUR 5UR 5- nUS==S-ss'UVs/sHn[XS9RS5PM nnUVs/sHn[XS9RS5PM n n[ R"[R"SXU-5[R"U[R"U5- U5[R"U [R"U 5- U5UUS S 9 g s snfs snf) zLPlot region of empirical cdfs expected under uniformity on the current axis.rpg?g& .>{Gzt?ףp= ?rexpected under uniformityr=y1y2rGrUr&N) rppfronesrsumr: fill_betweenrrr) rrrrUrGuni_bins uni_bins_cdfrloweruppers r?rrs \Q\266s;bggh>OOH??$x||~5L:F G,QU< % ) )% 0,E G:F G,QU< % ) )% 0,E G ++a#9 : 99URVVE]*K 8 99URVVE]*K 8)  H Gs &"D<"Ec ,[USUS-- S9RS5n[USUS-- S9RS5n[R"[R "SX!5[R "XQ5[R "Xa5UUSS9 g) z8Plot region of empirical cdfs expected under uniformity.rrrrrrrN)rrr:rrrr)rrrrUrGrrs r?rrs ,!x!|"4 5 9 9% @E ,!x!|"4 5 9 9% @E ++a. 9 99U % 99U %) rA)NrNNNNNN)NrNNN2rTg333333?皙?rFFFNNNN)NNrrFr\r)NNNrTr\)g?gray)4copytypingrrrrrrr r r r r warningsr matplotlibmplr1rtorchrrr:matplotlib.axesrmatplotlib.colorsrmatplotlib.figurerrmatplotlib.patchesr scipy.statsrrrrr@rWr}rrstrtuplerfloatboolrrrrrrrAr?rsE      $ '0(00 ., />#,0(,"& #- T&\4 3CC D--sm- - tCy) - 49% - T#Y - & - -e_- 64<-f#,0(,"& $"% #$ $$( #)M T&\4 3CC DMMsmM M tCy) M 49% M T#Y MMMM MMMMM !M" * #M$D>%M(e_)M* 64<+Mh"&  #-? ::-?-?-?# -? 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