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Fixing fitter and cleaning prefix directory addition (#833)
* Fixing fitter and cleaning prefix directory addition * fix * copyright fix * fix pylint * fix --------- Co-authored-by: Luigi Dello Stritto <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -25,10 +25,11 @@ def __init__(self, datap, case, typean, period): | |
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| # The only thing here is to dump the database in the data analysis directory | ||
| for mcordata in ("mc", "data"): | ||
| prefix_dir_res = datap["mlapplication"][mcordata].get("prefix_dir_res", "") | ||
| results_dir = prefix_dir_res + datap["analysis"][typean][mcordata]["results"][period] \ | ||
| dp = datap["analysis"][typean][mcordata] | ||
| prefix_dir_res = dp.get("prefix_dir_res", "") | ||
| results_dir = prefix_dir_res + dp["results"][period] \ | ||
| if period is not None \ | ||
| else prefix_dir_res + datap["analysis"][typean][mcordata]["resultsallp"] | ||
| else prefix_dir_res + dp["resultsallp"] | ||
| if not exists(results_dir): | ||
| # create otput directories in case they do not exist | ||
| makedirs(results_dir) | ||
|
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||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -20,7 +20,7 @@ | |
| # pylint: disable=unused-wildcard-import, wildcard-import | ||
| #from array import array | ||
| #import itertools | ||
| # pylint: disable=import-error, no-name-in-module, unused-import | ||
| # pylint: disable=import-error, no-name-in-module, unused-import, consider-using-f-string | ||
| # from root_numpy import hist2array, array2hist | ||
| from ROOT import TFile, TH1F, TH2F, TCanvas, TPad, TF1, TH1D | ||
| from ROOT import gStyle, TLegend, TLine, TText, TPaveText, TArrow | ||
|
|
@@ -54,10 +54,15 @@ def __init__(self, datap, case, typean, period): | |
| self.lpt_probcutfin = datap["mlapplication"]["probcutoptimal"] | ||
| self.triggerbit = datap["analysis"][self.typean].get("triggerbit", "") | ||
|
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| self.d_resultsallpmc = datap["analysis"][typean]["mc"]["results"][period] \ | ||
| if period is not None else datap["analysis"][typean]["mc"]["resultsallp"] | ||
| self.d_resultsallpdata = datap["analysis"][typean]["data"]["results"][period] \ | ||
| if period is not None else datap["analysis"][typean]["data"]["resultsallp"] | ||
| dp = datap["analysis"][self.typean] | ||
| self.d_prefix_mc = dp["mc"].get("prefix_dir_res") | ||
| self.d_prefix_data = dp["data"].get("prefix_dir_res") | ||
| self.d_resultsallpmc = self.d_prefix_mc + dp["mc"]["results"][period] \ | ||
| if period is not None \ | ||
| else self.d_prefix_mc + dp["mc"]["resultsallp"] | ||
| self.d_resultsallpdata = + dp["data"]["results"][period] \ | ||
| if period is not None \ | ||
| else self.d_prefix_data + dp["data"]["resultsallp"] | ||
|
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| n_filemass_name = datap["files_names"]["histofilename"] | ||
| self.n_filemass = os.path.join(self.d_resultsallpdata, n_filemass_name) | ||
|
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||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -24,7 +24,7 @@ | |
| from math import sqrt | ||
| from ctypes import c_double | ||
|
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| # pylint: disable=import-error, no-name-in-module, unused-import | ||
| # pylint: disable=import-error, no-name-in-module, unused-import, f-string-without-interpolation | ||
| from ROOT import AliHFInvMassFitter, AliVertexingHFUtils, AliHFInvMassMultiTrialFit | ||
| from ROOT import TFile, TH1F, TH1D, TF1, TPaveText, TLine, TLegend, TLatex | ||
| from ROOT import kBlue, kRed, kGreen, kMagenta, kOrange, kPink, kCyan, kYellow, kBlack | ||
|
|
@@ -497,6 +497,10 @@ def draw_kernel(self, root_pad, root_objects=[], **draw_args): # pylint: disable | |
| signif = c_double() | ||
| signif_err = c_double() | ||
| self.kernel.Significance(n_sigma_signal, signif, signif_err) | ||
| bkg = bkg.value | ||
| bkg_err = bkg_err.value | ||
| signif = signif.value | ||
| signif_err = signif_err.value | ||
| sig_o_bkg = sig / bkg if bkg > 0. else -1. | ||
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| root_objects.append(self.add_pave_helper_(0.15, 0.7, 0.48, 0.89, "NDC")) | ||
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@@ -1399,7 +1403,7 @@ def fill_pad(pad, ylims, histos, ref_line=None): | |
| pad.cd() | ||
| pad.SetLeftMargin(0.13) | ||
| pad.SetRightMargin(0.06) | ||
| lim_delta = (ylims[1] - ylims[0]) | ||
| lim_delta = ylims[1] - ylims[0] | ||
| lim_min = ylims[0] - 0.1 * lim_delta | ||
| lim_max = ylims[1] + 0.1 * lim_delta | ||
| for h in histos: | ||
|
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||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -20,7 +20,7 @@ | |
| from array import array | ||
| from ctypes import c_double | ||
|
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| #pylint: disable=too-many-lines, too-few-public-methods | ||
| #pylint: disable=too-many-lines, too-few-public-methods, consider-using-f-string, too-many-statements | ||
| from ROOT import TFile, TH1F, TF1, TCanvas, gStyle #pylint: disable=import-error, no-name-in-module | ||
|
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| from machine_learning_hep.logger import get_logger | ||
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@@ -29,7 +29,7 @@ | |
| from machine_learning_hep.fitting.utils import save_fit, load_fit | ||
| from machine_learning_hep.fitting.fitters import FitAliHF, FitROOTGauss, FitSystAliHF | ||
|
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| class MLFitParsFactory: # pylint: disable=too-many-instance-attributes, too-many-statements | ||
| class MLFitParsFactory: # pylint: disable=too-many-instance-attributes | ||
| """ | ||
| Managing MLHEP specific fit parameters and is used to collect and retrieve all information | ||
| required to initialise a (systematic) fit | ||
|
|
@@ -670,17 +670,20 @@ def __call__(self, x_var, par): | |
| return 0 | ||
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| if fbkg[ibin1] == "kLin": | ||
| fit_func = TF1("fit_func", FitBkg(), fitlim[0], fitlim[1], 2) | ||
| bkgFunc = FitBkg() | ||
| fit_func = TF1("fit_func", bkgFunc, fitlim[0], fitlim[1], 2) | ||
| hmass.Fit(fit_func, '', '', fitlim[0], fitlim[1]) | ||
| pars = fit_func.GetParameters() | ||
| bkg_func = TF1("fbkg", "pol1", fitlim[0], fitlim[1]) | ||
| elif fbkg[ibin1] == "Pol2": | ||
| fit_func = TF1("fit_func", FitBkg(), fitlim[0], fitlim[1], 3) | ||
| hmass.Fit(fit_func, '', '', fitlim[0], fitlim[1]) | ||
| bkgFunc = FitBkg() | ||
| fit_func = TF1("fit_func", bkgFunc, fitlim[0], fitlim[1], 3) | ||
| hmass.Fit("fit_func", '', '', fitlim[0], fitlim[1]) | ||
| pars = fit_func.GetParameters() | ||
| bkg_func = TF1("fbkg", "pol2", fitlim[0], fitlim[1]) | ||
| elif fbkg[ibin1] == "kExpo": | ||
| fit_func = TF1("fit_func", FitBkg(), fitlim[0], fitlim[1], 2) | ||
| bkgFunc = FitBkg() | ||
| fit_func = TF1("fit_func", bkgFunc, fitlim[0], fitlim[1], 2) | ||
| hmass.Fit(fit_func, '', '', fitlim[0], fitlim[1]) | ||
| pars = fit_func.GetParameters() | ||
| bkg_func = TF1("fbkg", "expo", fitlim[0], fitlim[1]) | ||
|
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||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -51,20 +51,16 @@ def __init__(self, case, proc_class, datap, typean, run_param, mcordata): | |
| self.dlper_pklsk = [] | ||
| self.dlper_pklml = [] | ||
| self.d_prefix = datap["multi"][self.mcordata].get("prefix_dir", "") | ||
| self.d_prefix_res = datap["mlapplication"][self.mcordata].get("prefix_dir_res", "") | ||
| for s in datap["multi"][self.mcordata]["unmerged_tree_dir"]: | ||
| self.dlper_root.append(self.d_prefix + s) | ||
| for s in datap["multi"][self.mcordata]["pkl"]: | ||
| self.dlper_pkl.append(self.d_prefix + s) | ||
| for s in datap["multi"][self.mcordata]["pkl_skimmed"]: | ||
| self.dlper_pklsk.append(self.d_prefix + s) | ||
| for s in datap["multi"][self.mcordata]["pkl_skimmed_merge_for_ml"]: | ||
| self.dlper_pklml.append(self.d_prefix + s) | ||
| self.d_pklml_mergedallp = self.d_prefix + \ | ||
| datap["multi"][self.mcordata]["pkl_skimmed_merge_for_ml_all"] | ||
| self.d_pklevt_mergedallp = self.d_prefix + \ | ||
| datap["multi"][self.mcordata]["pkl_evtcounter_all"] | ||
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| self.d_prefix_app = datap["mlapplication"][self.mcordata].get("prefix_dir_app", "") | ||
| self.d_prefix_res = datap["analysis"][self.typean][self.mcordata].get("prefix_dir_res", "") | ||
|
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| dp = datap["multi"][self.mcordata] | ||
| self.dlper_root = [self.d_prefix + p for p in dp["unmerged_tree_dir"]] | ||
| self.dlper_pkl = [self.d_prefix + p for p in dp["pkl"]] | ||
| self.dlper_pklsk = [self.d_prefix + p for p in dp["pkl_skimmed"]] | ||
| self.dlper_pklml = [self.d_prefix + p for p in dp["pkl_skimmed_merge_for_ml"]] | ||
| self.d_pklml_mergedallp = self.d_prefix + dp["pkl_skimmed_merge_for_ml_all"] | ||
| self.d_pklevt_mergedallp = self.d_prefix + dp["pkl_evtcounter_all"] | ||
| self.dlper_mcreweights = datap["multi"][self.mcordata]["mcreweights"] | ||
|
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| #namefiles pkl | ||
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@@ -101,18 +97,14 @@ def __init__(self, case, proc_class, datap, typean, run_param, mcordata): | |
| self.lper_evtorig = \ | ||
| [os.path.join(direc, self.n_evtorig) for direc in self.dlper_pkl] | ||
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| self.dlper_reco_modapp = [] | ||
| self.dlper_reco_modappmerged = [] | ||
| self.d_results = [] | ||
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| for s in datap["mlapplication"][self.mcordata]["pkl_skimmed_dec"]: | ||
| self.dlper_reco_modapp.append(self.d_prefix_res + s) | ||
| for s in datap["mlapplication"][self.mcordata]["pkl_skimmed_decmerged"]: | ||
| self.dlper_reco_modappmerged.append(self.d_prefix_res + s) | ||
| for s in datap["analysis"][self.typean][self.mcordata]["results"]: | ||
| self.d_results.append(self.d_prefix_res + s) | ||
| self.d_resultsallp = \ | ||
| self.d_prefix_res + datap["analysis"][self.typean][self.mcordata]["resultsallp"] | ||
| dp = datap["mlapplication"][self.mcordata] | ||
| self.dlper_reco_modapp = [self.d_prefix_app + p for p in dp["pkl_skimmed_dec"]] | ||
| self.dlper_reco_modappmerged = [self.d_prefix_app + p for p in dp["pkl_skimmed_decmerged"]] | ||
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| dp = datap["analysis"][self.typean][self.mcordata] | ||
| self.d_results = [self.d_prefix_res + p for p in dp["results"]] | ||
| self.d_resultsallp = self.d_prefix_res + dp["resultsallp"] | ||
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| self.lpt_probcutpre = datap["mlapplication"]["probcutpresel"] | ||
| self.lpt_probcut = datap["mlapplication"]["probcutoptimal"] | ||
| self.f_evt_mergedallp = os.path.join(self.d_pklevt_mergedallp, self.n_evt) | ||
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||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| ############################################################################# | ||
| ## © Copyright CERN 2018. All rights not expressly granted are reserved. ## | ||
| ## © Copyright CERN 2023. All rights not expressly granted are reserved. ## | ||
| ## Author: [email protected] ## | ||
| ## This program is free software: you can redistribute it and/or modify it ## | ||
| ## under the terms of the GNU General Public License as published by the ## | ||
|
|
@@ -133,7 +133,7 @@ def process_histomass_single(self, index): | |
| h_invmass = TH1F("hmass" + suffix, "", self.p_num_bins, | ||
| self.p_mass_fit_lim[0], self.p_mass_fit_lim[1]) | ||
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| fill_hist(h_invmass, df[self.v_invmass].to_numpy()) | ||
| fill_hist(h_invmass, df[self.v_invmass]) | ||
| myfile.cd() | ||
| h_invmass.Write() | ||
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@@ -149,9 +149,9 @@ def process_histomass_single(self, index): | |
| self.p_mass_fit_lim[0], self.p_mass_fit_lim[1]) | ||
| h_invmass_refl = TH1F("hmass_refl" + suffix, "", self.p_num_bins, | ||
| self.p_mass_fit_lim[0], self.p_mass_fit_lim[1]) | ||
| fill_hist(h_invmass_sig, df_sig[self.v_invmass].to_numpy()) | ||
| fill_hist(h_invmass_bkg, df_bkg[self.v_invmass].to_numpy()) | ||
| fill_hist(h_invmass_refl, df_refl[self.v_invmass].to_numpy()) | ||
| fill_hist(h_invmass_sig, df_sig[self.v_invmass]) | ||
| fill_hist(h_invmass_bkg, df_bkg[self.v_invmass]) | ||
| fill_hist(h_invmass_refl, df_refl[self.v_invmass]) | ||
| myfile.cd() | ||
| h_invmass_sig.Write() | ||
| h_invmass_bkg.Write() | ||
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