From 4370211b107d7859a2f9766f3ca3c42de5266a6e Mon Sep 17 00:00:00 2001
From: Nikolai <osterei33@gmx.de>
Date: Thu, 9 Aug 2018 09:25:26 +0200
Subject: [PATCH] trying to implement 2D ratio hist
---
plotting.py | 29 +++++++++++++++++++++++++++++
scripts/plot_NN_2D.py | 29 +++++++++++++++++++++++++++--
2 files changed, 56 insertions(+), 2 deletions(-)
diff --git a/plotting.py b/plotting.py
index db24def..c4f9000 100644
--- a/plotting.py
+++ b/plotting.py
@@ -250,6 +250,35 @@ def plot_hist_2D_events(plotname, valsx, valsy, nbinsx, xmin, xmax, nbinsy, ymin
plot_hist_2D(plotname, xedges, yedges, hist, varx_label, vary_label, log)
+def plot_hist_2D_events_ratio(plotname,
+ valsx1, valsy1,
+ valsx2, valsy2,
+ nbinsx, xmin, xmax, nbinsy, ymin, ymax,
+ weights1=None,
+ weights2=None,
+ varx_label=None, vary_label=None, log=False):
+
+ xedges = np.linspace(xmin, xmax, nbinsx)
+ yedges = np.linspace(ymin, ymax, nbinsy)
+
+ hist1, xedges, yedges = np.histogram2d(valsx1, valsy1, bins=(xedges, yedges), weights=weights1)
+ hist2, xedges, yedges = np.histogram2d(valsx2, valsy2, bins=(xedges, yedges), weights=weights2)
+
+ hist1 = hist1.T
+ hist2 = hist2.T
+
+ hist1 /= hist1.sum()
+ hist2 /= hist2.sum()
+
+ hist2[hist2==0] = np.nan
+
+ hist = hist1/hist2
+
+ print(hist)
+
+ plot_hist_2D(plotname, xedges, yedges, hist, varx_label, vary_label, log)
+
+
def plot_cond_avg_actmax_2D(plotname, model, layer, neuron, ranges,
varx_index, vary_index,
nbinsx, xmin, xmax, nbinsy, ymin, ymax,
diff --git a/scripts/plot_NN_2D.py b/scripts/plot_NN_2D.py
index ba54b1e..996c29e 100755
--- a/scripts/plot_NN_2D.py
+++ b/scripts/plot_NN_2D.py
@@ -13,6 +13,7 @@ from KerasROOTClassification.plotting import (
plot_NN_vs_var_2D,
plot_profile_2D,
plot_hist_2D_events,
+ plot_hist_2D_events_ratio,
plot_cond_avg_actmax_2D
)
from KerasROOTClassification.utils import get_single_neuron_function, get_max_activation_events
@@ -23,7 +24,7 @@ parser.add_argument("output_filename")
parser.add_argument("varx")
parser.add_argument("vary")
parser.add_argument("-m", "--mode",
- choices=["mean_sig", "mean_bkg", "profile_sig", "profile_bkg", "hist_sig", "hist_bkg", "hist_actmax", "cond_actmax"],
+ choices=["mean_sig", "mean_bkg", "profile_sig", "profile_bkg", "hist_sig", "hist_bkg", "hist_ratio", "hist_actmax", "cond_actmax"],
default="mean_sig")
parser.add_argument("-l", "--layer", type=int, help="Layer index (takes last layer by default)")
parser.add_argument("-n", "--neuron", type=int, default=0, help="Neuron index (takes first neuron by default)")
@@ -134,7 +135,7 @@ elif args.mode.startswith("profile"):
**opt_kwargs
)
-elif args.mode.startswith("hist"):
+elif args.mode.startswith("hist") and not args.mode == "hist_ratio":
if not args.mode == "hist_actmax":
if args.mode == "hist_sig":
@@ -171,6 +172,30 @@ elif args.mode.startswith("hist"):
log=args.log,
)
+elif args.mode == "hist_ratio":
+ valsx1 = c.x_test[c.y_test==1][:,varx_index]
+ valsx2 = c.x_test[c.y_test==0][:,varx_index]
+ if not plot_vs_activation:
+ valsy1 = c.x_test[c.y_test==1][:,vary_index]
+ valsy2 = c.x_test[c.y_test==0][:,vary_index]
+ else:
+ valsy1 = c.scores_test[c.y_test==1].reshape(-1)
+ valsy2 = c.scores_test[c.y_test==0].reshape(-1)
+ weights1 = c.w_test[c.y_test==1]
+ weights2 = c.w_test[c.y_test==0]
+
+ plot_hist_2D_events_ratio(
+ args.output_filename,
+ valsx1, valsy1,
+ valsx2, valsy2,
+ xmin=varx_range[0], xmax=varx_range[1], nbinsx=varx_range[2],
+ ymin=vary_range[0], ymax=vary_range[1], nbinsy=vary_range[2],
+ weights1=weights1,
+ weights2=weights2,
+ varx_label=varx_label, vary_label=vary_label,
+ log=args.log,
+ )
+
elif args.mode.startswith("cond_actmax"):
x_test_scaled = c.scaler.transform(c.x_test)
--
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