Resolve "TMVA example"

Closes #45 (closed)

examples/TmvaBdt.ipynb

+%% Cell type:code id: tags:
 
+``` python
+import pandas as pd
+import seaborn as sns
+
+from nnfwtbn import Variable, Process, Cut, hist, McStack, DataStack, Stack, TmvaBdt
+from nnfwtbn import toydata
 ```
 
+%% Cell type:code id: tags:
 
+``` python
+df = toydata.get()
 ```
 
+%% Cell type:markdown id: tags:
 
+# Evaluation of TMVA BDT
+The file `tmva_bdt.xml` contains a sample BDT trained on the toy dataset. The input variables are
+ - $\eta^{j_1}$,
+ - $\eta^{j_2}$,
+ - $\tau\;\mathrm{centrality}$ and
+ - $\ell\;\mathrm{centrality}$.
+
+The BDT was trained with regular TMVA in ROOT. The weights stored in the XML file can be read by `nnfwtbn.TmvaBdt` directly.
 
+%% Cell type:code id: tags:
 
+``` python
+bdt = TmvaBdt("tmva_bdt.xml")
+df['bdt_prediction'] = bdt.predict(df)
 ```
 
+%% Cell type:markdown id: tags:
 
+# Plotting
 
+%% Cell type:code id: tags:
 
+``` python
+p_ztt = Process(r"$Z\rightarrow\tau\tau$", range=(0, 0))
+p_sig = Process(r"Signal", range=(1, 1))
 ```
 
+%% Cell type:code id: tags:
 
+``` python
+colors = ["windows blue", "amber", "greyish", "faded green", "dusty purple"]
+colors = sns.xkcd_palette(colors)
+s_ztt = McStack(p_ztt, color=colors[0], histtype='step')
+s_sig = McStack(p_sig, color=colors[1], histtype='step')
 ```
 
+%% Cell type:code id: tags:
 
+``` python
+v_bdt = Variable("BDT Score", "bdt_prediction")
+hist(df, v_bdt, 22, [s_ztt, s_sig], range=(-1.1, 1.1),
+     weight="weight",  numerator=None)
+None
 ```