From e786b9dbaf84ad6f121dd5b0c05cd029f9e62b11 Mon Sep 17 00:00:00 2001
From: Fize Jacques <jacques.fize@cirad.fr>
Date: Wed, 27 Mar 2019 16:22:55 +0100
Subject: [PATCH] Add new parameter to annotation + debug
---
.gitignore | 3 +-
auto_fill_annotation.py | 91 +-
.../.ipynb_checkpoints/output-checkpoint.png | Bin 23949 -> 0 bytes
.../MatchingAnalysis/MADA_growth_criteria.pdf | Bin 20101 -> 0 bytes
.../Result_AnaysisV2_MADA.ipynb | 999 +++++++-----------
notebooks/MatchingAnalysis/c1.png | Bin 30295 -> 0 bytes
notebooks/MatchingAnalysis/c2.png | Bin 32834 -> 0 bytes
notebooks/MatchingAnalysis/c3.png | Bin 31173 -> 0 bytes
notebooks/MatchingAnalysis/c4.png | Bin 31716 -> 0 bytes
notebooks/MatchingAnalysis/output.png | Bin 31264 -> 0 bytes
notebooks/MatchingAnalysis/sum.png | Bin 23192 -> 0 bytes
run_automatic_annotation.py | 46 +-
run_test.py | 128 +++
strpython/eval/automatic_annotation.py | 18 +-
strpython/helpers/geo_relation_database.py | 18 +-
strpython/helpers/match_cache.py | 4 +-
strpython/helpers/sim_matrix.py | 4 +-
17 files changed, 616 insertions(+), 695 deletions(-)
delete mode 100644 notebooks/MatchingAnalysis/.ipynb_checkpoints/output-checkpoint.png
delete mode 100644 notebooks/MatchingAnalysis/MADA_growth_criteria.pdf
delete mode 100644 notebooks/MatchingAnalysis/c1.png
delete mode 100644 notebooks/MatchingAnalysis/c2.png
delete mode 100644 notebooks/MatchingAnalysis/c3.png
delete mode 100644 notebooks/MatchingAnalysis/c4.png
delete mode 100644 notebooks/MatchingAnalysis/output.png
delete mode 100644 notebooks/MatchingAnalysis/sum.png
create mode 100644 run_test.py
diff --git a/.gitignore b/.gitignore
index fd97257..dd029ad 100644
--- a/.gitignore
+++ b/.gitignore
@@ -28,4 +28,5 @@ __pycache__/
*cache.json
*.gexf
temp_cluster_2/
-agromada*
\ No newline at end of file
+agromada*
+output*
\ No newline at end of file
diff --git a/auto_fill_annotation.py b/auto_fill_annotation.py
index f47d236..8ccf6f9 100644
--- a/auto_fill_annotation.py
+++ b/auto_fill_annotation.py
@@ -4,8 +4,7 @@
import argparse, os
import warnings
-import os, re, glob
-import pandas as pd
+import os, re, glob,json
import networkx as nx
import numpy as np
@@ -19,18 +18,24 @@ from strpython.models.str import STR
from strpython.helpers.sim_matrix import matrix_to_pandas_dataframe, read_bz2_matrix
-def main(dataset, matrix_sim_dir, raw_graph_dir, selected_graphs, threshold, inclusion_fn, adjacency_fn):
+def main(dataset, matrix_sim_dir, raw_graph_dir, selected_graphs, threshold, inclusion_fn, adjacency_fn,min_carac_fn, min_size_G1,min_size_G2,n_car_min_doc1,n_car_min_doc2):
annotater = AnnotationAutomatic(dataset, threshold, inclusion_fn, adjacency_fn)
first_step_output = "output_first_step_{0}_{1}".format(dataset, threshold)
last_step_output = "output_final_{0}_{1}".format(dataset, threshold)
generate_annotation_dataframe(matrix_sim_dir, selected_graphs, first_step_output)
- extract_criteria_4_all(annotater, first_step_output, raw_graph_dir, dataset, threshold)
+ # size_str = extract_criteria_4_all(annotater, first_step_output, raw_graph_dir, dataset, threshold)
if not os.path.exists(last_step_output):
os.makedirs(last_step_output)
- for fn in glob.glob(os.path.join(first_step_output,"*.csv")):
- annotate_eval_sample(annotater, fn, os.path.join(last_step_output, os.path.basename(fn)))
- synthesize(last_step_output,"{0}_{1}.csv".format(dataset,threshold))
+
+ # for fn in tqdm(glob.glob(os.path.join(first_step_output,"*.csv")),desc="Annotate sample"):
+ # annotate_eval_sample(annotater, fn, os.path.join(last_step_output, os.path.basename(fn)),size_str)
+
+ min_carac_dict=None
+ if min_carac_fn != "" and os.path.exists(min_carac_fn):
+ min_carac_dict=json.load(open(min_carac_fn))
+
+ synthesize(last_step_output,"{0}_{1}.csv".format(dataset,threshold),min_size_G1,min_size_G2,min_carac_dict,n_car_min_doc1,n_car_min_doc2)
@@ -47,6 +52,7 @@ def generate_annotation_dataframe(matrix_sim_dir, selected_graphs, output_dir):
-------
"""
+
if not os.path.exists(matrix_sim_dir):
raise FileNotFoundError("Similarity matrix directory not found : {0}".format(matrix_sim_dir))
@@ -55,6 +61,8 @@ def generate_annotation_dataframe(matrix_sim_dir, selected_graphs, output_dir):
type_ = "_".join(os.path.basename(fn).split("_")[1:]).replace(".npy.bz2", "")
print("Proceeding...", measure, type_)
+ if os.path.exists(os.path.join(output_dir, "{0}_{1}.csv".format(measure, type_))):
+ continue
df = matrix_to_pandas_dataframe(np.nan_to_num(read_bz2_matrix(fn)),
selected_graphs,
measure, type_)
@@ -96,30 +104,38 @@ def extract_criteria_4_all(annotater, csv_input_dir, raw_graph_dir, dataset, thr
# Load STRs
strs = {}
+ size_STR={}
+
+ def load(fn):
+ id_ = int(re.findall("\d+", fn)[-1])
+ strs[id_] = STR.from_networkx_graph(nx.read_gexf(fn))
+ size_STR[id_] = len(strs[id_])
+
for file in tqdm(glob.glob(os.path.join(raw_graph_dir, "*.gexf")), desc="Load Graphs"):
id_ = int(re.findall("\d+", file)[-1])
strs[id_] = STR.from_networkx_graph(nx.read_gexf(file))
-
- # Do the annotation for a match between two STR
+ size_STR[id_]= len(strs[id_])
+ #Do the annotation for a match between two STR
def annotate(x):
try:
return annotater.all(strs[int(x.G1)], strs[int(x.G2)], int(x.G1), int(x.G2))
except KeyError as e:
- annotater.matching_cache.add(int(x.G1), int(x.G2), *(0, 0, 0, 0))
- return [0, 0, 0, 0]
+ annotater.matching_cache.add(int(x.G1), int(x.G2), *(0, 0, 0, 0,300000))
+ return [0, 0, 0, 0,300000,0]
# Annotation Time
+ print("Computing Criteria for each match")
matching_dataframe["res"] = matching_dataframe.progress_apply(lambda x: annotate(x), axis=1)
- matching_dataframe.res = matching_dataframe.res.apply(lambda x: list(map(int, x)) if x else [])
- for ix, col in enumerate("c1 c2 c3 c4".split()):
+ matching_dataframe.res = matching_dataframe.res.apply(lambda x: [int(x[0]),int(x[1]),int(x[2]),int(x[3]),float(x[4])] if x else [])
+ for ix, col in enumerate("c1 c2 c3 c4 c5".split()):
matching_dataframe[col] = matching_dataframe.res.apply(lambda x: x[ix] if len(x) > 0 else 0)
del matching_dataframe["res"]
# Writiting output
- matching_dataframe.to_csv(output_file)
+ return size_STR
-def annotate_eval_sample(annotater, csv_file, output_file):
+def annotate_eval_sample(annotater, csv_file, output_file, size_str):
"""
Third Step
Parameters
@@ -141,21 +157,23 @@ def annotate_eval_sample(annotater, csv_file, output_file):
try:
return annotater.all(None, None, x.G1, x.G2)
except Exception as e:
- return [0, 0, 0, 0]
+ return [0, 0, 0, 0,300000]
df["res"] = df.apply(lambda x: foo(x), axis=1)
- df.res = df.res.apply(lambda x: list(map(int, x)) if x else []) # if bool
+ df.res = df.res.apply(lambda x: list(map(float, x)) if x else []) # if bool
df[["c1"]] = df.res.apply(lambda x: x[0] if len(x) > 0 else 0)
df[["c2"]] = df.res.apply(lambda x: x[1] if len(x) > 0 else 0)
df[["c3"]] = df.res.apply(lambda x: x[2] if len(x) > 0 else 0)
df[["c4"]] = df.res.apply(lambda x: x[3] if len(x) > 0 else 0)
-
+ df[["c5"]] = df.res.apply(lambda x: x[4] if len(x) > 0 else 300000)
+ df["size_G1"] =df.apply(lambda x: size_str[x.G1] if x.G1 in size_str else 0, axis=1)
+ df["size_G2"] = df.apply(lambda x: size_str[x.G2] if x.G2 in size_str else 0, axis=1)
del df["res"]
df.to_csv(output_file)
-def synthesize(last_step_output,output_filename):
+def synthesize(last_step_output,output_filename,min_size_G1=None,min_size_G2=None,min_carac_dict=None,ncar_min_doc1=0,ncar_min_doc2=0):
"""
Fourth Step
Parameters
@@ -168,16 +186,41 @@ def synthesize(last_step_output,output_filename):
"""
fns = glob.glob(os.path.join(last_step_output, "*.csv"))
-
+ if min_size_G1:
+ output_filename= output_filename+"_ming1_{0}".format(min_size_G1)
+ if min_size_G2:
+ output_filename= output_filename+"_ming2_{0}".format(min_size_G2)
+ if min_carac_dict and ncar_min_doc1 > 0:
+ output_filename= output_filename+"_mindoc1len_{0}".format(ncar_min_doc1)
+ if min_carac_dict and ncar_min_doc2 > 0:
+ output_filename= output_filename+"_mindoc2len_{0}".format(ncar_min_doc2)
data = []
- for fn in fns:
+ for fn in tqdm(fns,desc="Synthetise Results"):
df = pd.read_csv(fn)
+ if min_size_G1:
+ df= df[df.size_G1 >= min_size_G1]
+
+ if min_size_G2:
+ df = df[df.size_G2 >= min_size_G2]
+
+ if min_carac_dict and ncar_min_doc1>0:
+ df["len_doc1"]=df.apply(lambda x:min_carac_dict[str(x.G1)],axis=1)
+ df =df[df.len_doc1 >= ncar_min_doc1]
+
+ if min_carac_dict and ncar_min_doc2>0:
+ df["len_doc2"]=df.apply(lambda x:min_carac_dict[str(x.G2)] if str(x.G2) in min_carac_dict else 0,axis=1)
+ df =df[df.len_doc2 >= ncar_min_doc2]
+
+ df = df.replace([np.inf, -np.inf], 300000)
+ df["c5"] = 1 - (df.c5 - df.c5.min()) / (df.c5.max() - df.c5.min())
+ if len(df) <1:
+ continue
mes = np.unique(df.sim_measure)[0]
type_ = np.unique(df.type_str)[0]
- val = df.groupby("G1").mean().mean()["c1 c2 c3 c4".split()].values.tolist()
+ val = df.groupby("G1").mean().mean()["c1 c2 c3 c4 c5".split()].values.tolist()
val.insert(0, type_)
val.insert(0, mes)
data.append(val)
- pd.DataFrame(data, columns="mesure type c1 c2 c3 c4".split())
- res = pd.DataFrame(data, columns="mesure type c1 c2 c3 c4".split())
+
+ res = pd.DataFrame(data, columns="mesure type c1 c2 c3 c4 c5".split())
res.to_csv(output_filename)
\ No newline at end of file
diff --git a/notebooks/MatchingAnalysis/.ipynb_checkpoints/output-checkpoint.png b/notebooks/MatchingAnalysis/.ipynb_checkpoints/output-checkpoint.png
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diff --git a/notebooks/MatchingAnalysis/Result_AnaysisV2_MADA.ipynb b/notebooks/MatchingAnalysis/Result_AnaysisV2_MADA.ipynb
index dcbb6ca..a43373c 100644
--- a/notebooks/MatchingAnalysis/Result_AnaysisV2_MADA.ipynb
+++ b/notebooks/MatchingAnalysis/Result_AnaysisV2_MADA.ipynb
@@ -27,7 +27,7 @@
},
{
"cell_type": "code",
- "execution_count": 113,
+ "execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-09-28T05:03:09.093753Z",
@@ -36,7 +36,7 @@
},
"outputs": [],
"source": [
- "data=pd.read_csv(\"../../agromad_05_mean_nbpoint.csv\",index_col=0)\n",
+ "data=pd.read_csv(\"../../bvlac_2_0.5.csvming1_10\",index_col=0)\n",
"data=data[data.mesure != \"BP\"]\n",
"data[\"mean\"]=np.mean(data[\"c1 c2 c3 c4\".split()].values,axis=1)\n",
"data[\"sum\"]=np.sum(data[\"c1 c2 c3 c4\".split()].values,axis=1)\n",
@@ -47,7 +47,7 @@
},
{
"cell_type": "code",
- "execution_count": 114,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -56,7 +56,7 @@
},
{
"cell_type": "code",
- "execution_count": 115,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
@@ -65,234 +65,19 @@
},
{
"cell_type": "code",
- "execution_count": 116,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
- "data": {
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- " }</style><table id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >mesure</th> <th class=\"col_heading level0 col1\" >type</th> <th class=\"col_heading level0 col2\" >c1</th> <th class=\"col_heading level0 col3\" >c2</th> <th class=\"col_heading level0 col4\" >c3</th> <th class=\"col_heading level0 col5\" >c4</th> <th class=\"col_heading level0 col6\" >mean</th> <th class=\"col_heading level0 col7\" >sum</th> <th class=\"col_heading level0 col8\" >c1_w</th> <th class=\"col_heading level0 col9\" >c2_w</th> <th class=\"col_heading level0 col10\" >c3_w</th> <th class=\"col_heading level0 col11\" >c4_w</th> <th class=\"col_heading level0 col12\" >sum_w</th> </tr></thead><tbody>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >6</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col0\" class=\"data row0 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col1\" class=\"data row0 col1\" >inra_gen_country</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.664</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.246</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.342</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col5\" class=\"data row0 col5\" >0.194</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col6\" class=\"data row0 col6\" >0.3615</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col7\" class=\"data row0 col7\" >1.446</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col8\" class=\"data row0 col8\" >0.0664</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col9\" class=\"data row0 col9\" >0.0984</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col10\" class=\"data row0 col10\" >0.1368</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col11\" class=\"data row0 col11\" >0.0194</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row0_col12\" class=\"data row0 col12\" >0.321</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >3</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col0\" class=\"data row1 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col1\" class=\"data row1 col1\" >inra</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.732</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col3\" class=\"data row1 col3\" >0.23</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col4\" class=\"data row1 col4\" >0.336</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col5\" class=\"data row1 col5\" >0.19</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col6\" class=\"data row1 col6\" >0.372</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col7\" class=\"data row1 col7\" >1.488</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col8\" class=\"data row1 col8\" >0.0732</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col9\" class=\"data row1 col9\" >0.092</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col10\" class=\"data row1 col10\" >0.1344</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col11\" class=\"data row1 col11\" >0.019</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row1_col12\" class=\"data row1 col12\" >0.3186</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row2\" class=\"row_heading level0 row2\" >101</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col0\" class=\"data row2 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col1\" class=\"data row2 col1\" >inra_ext_2</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col2\" class=\"data row2 col2\" >0.724</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col3\" class=\"data row2 col3\" >0.226</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col4\" class=\"data row2 col4\" >0.336</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col5\" class=\"data row2 col5\" >0.19</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col6\" class=\"data row2 col6\" >0.369</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col7\" class=\"data row2 col7\" >1.476</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col8\" class=\"data row2 col8\" >0.0724</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col9\" class=\"data row2 col9\" >0.0904</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col10\" class=\"data row2 col10\" >0.1344</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col11\" class=\"data row2 col11\" >0.019</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row2_col12\" class=\"data row2 col12\" >0.3162</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row3\" class=\"row_heading level0 row3\" >137</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col0\" class=\"data row3 col0\" >MCS</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col1\" class=\"data row3 col1\" >gen_region</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col2\" class=\"data row3 col2\" >0.69</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col3\" class=\"data row3 col3\" >0.228</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col4\" class=\"data row3 col4\" >0.334</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col5\" class=\"data row3 col5\" >0.198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col6\" class=\"data row3 col6\" >0.3625</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col7\" class=\"data row3 col7\" >1.45</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col8\" class=\"data row3 col8\" >0.069</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col9\" class=\"data row3 col9\" >0.0912</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col10\" class=\"data row3 col10\" >0.1336</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col11\" class=\"data row3 col11\" >0.0198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row3_col12\" class=\"data row3 col12\" >0.3136</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row4\" class=\"row_heading level0 row4\" >106</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col0\" class=\"data row4 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col1\" class=\"data row4 col1\" >ext_2</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col2\" class=\"data row4 col2\" >0.744</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col3\" class=\"data row4 col3\" >0.22</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col4\" class=\"data row4 col4\" >0.326</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col5\" class=\"data row4 col5\" >0.198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col6\" class=\"data row4 col6\" >0.372</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col7\" class=\"data row4 col7\" >1.488</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col8\" class=\"data row4 col8\" >0.0744</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col9\" class=\"data row4 col9\" >0.088</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col10\" class=\"data row4 col10\" >0.1304</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col11\" class=\"data row4 col11\" >0.0198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row4_col12\" class=\"data row4 col12\" >0.3126</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row5\" class=\"row_heading level0 row5\" >92</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col0\" class=\"data row5 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col1\" class=\"data row5 col1\" >ext_1</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col2\" class=\"data row5 col2\" >0.736</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col3\" class=\"data row5 col3\" >0.216</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col4\" class=\"data row5 col4\" >0.328</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col5\" class=\"data row5 col5\" >0.198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col6\" class=\"data row5 col6\" >0.3695</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col7\" class=\"data row5 col7\" >1.478</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col8\" class=\"data row5 col8\" >0.0736</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col9\" class=\"data row5 col9\" >0.0864</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col10\" class=\"data row5 col10\" >0.1312</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col11\" class=\"data row5 col11\" >0.0198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row5_col12\" class=\"data row5 col12\" >0.311</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row6\" class=\"row_heading level0 row6\" >73</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col0\" class=\"data row6 col0\" >Jaccard</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col1\" class=\"data row6 col1\" >biotex_bvlac</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col2\" class=\"data row6 col2\" >0.726</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col3\" class=\"data row6 col3\" >0.214</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col4\" class=\"data row6 col4\" >0.334</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col5\" class=\"data row6 col5\" >0.192</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col6\" class=\"data row6 col6\" >0.3665</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col7\" class=\"data row6 col7\" >1.466</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col8\" class=\"data row6 col8\" >0.0726</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col9\" class=\"data row6 col9\" >0.0856</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col10\" class=\"data row6 col10\" >0.1336</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col11\" class=\"data row6 col11\" >0.0192</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row6_col12\" class=\"data row6 col12\" >0.311</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row7\" class=\"row_heading level0 row7\" >51</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col0\" class=\"data row7 col0\" >MCS</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col1\" class=\"data row7 col1\" >ext_2</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col2\" class=\"data row7 col2\" >0.7</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col3\" class=\"data row7 col3\" >0.216</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col4\" class=\"data row7 col4\" >0.332</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col5\" class=\"data row7 col5\" >0.198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col6\" class=\"data row7 col6\" >0.3615</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col7\" class=\"data row7 col7\" >1.446</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col8\" class=\"data row7 col8\" >0.07</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col9\" class=\"data row7 col9\" >0.0864</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col10\" class=\"data row7 col10\" >0.1328</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col11\" class=\"data row7 col11\" >0.0198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row7_col12\" class=\"data row7 col12\" >0.309</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row8\" class=\"row_heading level0 row8\" >67</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col0\" class=\"data row8 col0\" >BOW</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col1\" class=\"data row8 col1\" >str_object</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col2\" class=\"data row8 col2\" >0.732</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col3\" class=\"data row8 col3\" >0.208</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col4\" class=\"data row8 col4\" >0.332</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col5\" class=\"data row8 col5\" >0.198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col6\" class=\"data row8 col6\" >0.3675</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col7\" class=\"data row8 col7\" >1.47</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col8\" class=\"data row8 col8\" >0.0732</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col9\" class=\"data row8 col9\" >0.0832</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col10\" class=\"data row8 col10\" >0.1328</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col11\" class=\"data row8 col11\" >0.0198</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row8_col12\" class=\"data row8 col12\" >0.309</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820level0_row9\" class=\"row_heading level0 row9\" >134</th>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col0\" class=\"data row9 col0\" >VertexEdgeOverlap</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col1\" class=\"data row9 col1\" >inra_ext_2</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col2\" class=\"data row9 col2\" >0.71</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col3\" class=\"data row9 col3\" >0.23</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col4\" class=\"data row9 col4\" >0.316</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col5\" class=\"data row9 col5\" >0.194</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col6\" class=\"data row9 col6\" >0.3625</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col7\" class=\"data row9 col7\" >1.45</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col8\" class=\"data row9 col8\" >0.071</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col9\" class=\"data row9 col9\" >0.092</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col10\" class=\"data row9 col10\" >0.1264</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col11\" class=\"data row9 col11\" >0.0194</td>\n",
- " <td id=\"T_6958a7d0_4af9_11e9_9cd7_6a0002e84820row9_col12\" class=\"data row9 col12\" >0.3088</td>\n",
- " </tr>\n",
- " </tbody></table>"
- ],
- "text/plain": [
- "<pandas.io.formats.style.Styler at 0x13d4df3c8>"
- ]
- },
- "execution_count": 116,
- "metadata": {},
- "output_type": "execute_result"
+ "ename": "NameError",
+ "evalue": "name 'colorize' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-4-d2caa3de5718>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"c5_w\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc5\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;36m0.1\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"sum_w\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"c1_w c2_w c3_w c4_w c5_w\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mcolorize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"sum\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mascending\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"sum_w\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mascending\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"c1_w c2_w c3_w c4_w c5_w sum_w\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m: name 'colorize' is not defined"
+ ]
}
],
"source": [
@@ -300,8 +85,9 @@
"data[\"c2_w\"]=data.c2.apply(lambda x: 0.4*x)\n",
"data[\"c3_w\"]=data.c3.apply(lambda x: 0.4*x)\n",
"data[\"c4_w\"]=data.c4.apply(lambda x: 0.1*x)\n",
- "data[\"sum_w\"]=np.sum(data[\"c1_w c2_w c3_w c4_w\".split()].values,axis=1)\n",
- "colorize(data.sort_values(\"sum\",ascending=False).head(10).sort_values(\"sum_w\",ascending=False),\"c1_w c2_w c3_w c4_w sum_w\".split())"
+ "data[\"c5_w\"]=data.c5.apply(lambda x: 0.1*x)\n",
+ "data[\"sum_w\"]=np.sum(data[\"c1_w c2_w c3_w c4_w c5_w\".split()].values,axis=1)\n",
+ "colorize(data.sort_values(\"sum\",ascending=False).head(10).sort_values(\"sum_w\",ascending=False),\"c1_w c2_w c3_w c4_w c5_w sum_w\".split())"
]
},
{
@@ -802,7 +588,7 @@
},
{
"cell_type": "code",
- "execution_count": 119,
+ "execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2018-09-26T12:55:10.491478Z",
@@ -827,23 +613,7 @@
" i+=1\n",
" return indices,pareto_frontier\n",
"\n",
- "def highlight_max(s):\n",
- " '''\n",
- " highlight the maximum in a Series yellow.\n",
- " '''\n",
- " is_max = s == s.max()\n",
- " return ['background-color: yellow' if v else '' for v in is_max]\n",
- "def highlight_min(s):\n",
- " '''\n",
- " highlight the maximum in a Series yellow.\n",
- " '''\n",
- " is_max = s == s.min()\n",
- " return ['background-color: #d64541;color:white;' if v else '' for v in is_max]\n",
- "\n",
- "def colorize(df,fields):\n",
- " return df.style.apply(highlight_max,subset=fields).apply(highlight_min,subset=fields)\n",
- "\n",
- "to_colorize=\"c1 c2 c3 c4 mean sum\".split()"
+ "to_colorize=\"c1 c2 c3 c4 c5 mean sum\".split()\n"
]
},
{
@@ -857,7 +627,7 @@
},
{
"cell_type": "code",
- "execution_count": 120,
+ "execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-09-26T12:55:10.899176Z",
@@ -869,182 +639,159 @@
"data": {
"text/html": [
"<style type=\"text/css\" >\n",
- " #T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col0 {\n",
+ " #T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col0 {\n",
+ " background-color: yellow;\n",
+ " : ;\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col2 {\n",
" background-color: yellow;\n",
" : ;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col2 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col3 {\n",
" background-color: yellow;\n",
" : ;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col4 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col5 {\n",
" background-color: yellow;\n",
" : ;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col5 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col6 {\n",
" background-color: yellow;\n",
" : ;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col3 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col3 {\n",
" background-color: yellow;\n",
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" background-color: yellow;\n",
" : ;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col0 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col3 {\n",
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+ " color: white;\n",
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" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col1 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col2 {\n",
" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col2 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col3 {\n",
" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col3 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col4 {\n",
" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col4 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col5 {\n",
" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " } #T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col5 {\n",
+ " } #T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col6 {\n",
" : ;\n",
" background-color: #d64541;\n",
" color: white;\n",
- " }</style><table id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >c1</th> <th class=\"col_heading level0 col1\" >c2</th> <th class=\"col_heading level0 col2\" >c3</th> <th class=\"col_heading level0 col3\" >c4</th> <th class=\"col_heading level0 col4\" >mean</th> <th class=\"col_heading level0 col5\" >sum</th> <th class=\"col_heading level0 col6\" >c1_w</th> <th class=\"col_heading level0 col7\" >c2_w</th> <th class=\"col_heading level0 col8\" >c3_w</th> <th class=\"col_heading level0 col9\" >c4_w</th> <th class=\"col_heading level0 col10\" >sum_w</th> </tr> <tr> <th class=\"index_name level0\" >mesure</th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> </tr></thead><tbody>\n",
+ " }</style><table id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >c1</th> <th class=\"col_heading level0 col1\" >c2</th> <th class=\"col_heading level0 col2\" >c3</th> <th class=\"col_heading level0 col3\" >c4</th> <th class=\"col_heading level0 col4\" >c5</th> <th class=\"col_heading level0 col5\" >mean</th> <th class=\"col_heading level0 col6\" >sum</th> </tr> <tr> <th class=\"index_name level0\" >mesure</th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> <th class=\"blank\" ></th> </tr></thead><tbody>\n",
" <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >BOW</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col0\" class=\"data row0 col0\" >0.667391</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col1\" class=\"data row0 col1\" >0.215652</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.324174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.193739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.350239</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col5\" class=\"data row0 col5\" >1.40096</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col6\" class=\"data row0 col6\" >0.667391</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col7\" class=\"data row0 col7\" >0.215652</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col8\" class=\"data row0 col8\" >0.324174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col9\" class=\"data row0 col9\" >0.193739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row0_col10\" class=\"data row0 col10\" >1.40096</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >VertexEdgeOverlap</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col0\" class=\"data row1 col0\" >0.664609</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col1\" class=\"data row1 col1\" >0.212174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.316174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col3\" class=\"data row1 col3\" >0.194435</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col4\" class=\"data row1 col4\" >0.346848</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col5\" class=\"data row1 col5\" >1.38739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col6\" class=\"data row1 col6\" >0.664609</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col7\" class=\"data row1 col7\" >0.212174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col8\" class=\"data row1 col8\" >0.316174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col9\" class=\"data row1 col9\" >0.194435</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row1_col10\" class=\"data row1 col10\" >1.38739</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row2\" class=\"row_heading level0 row2\" >MCS</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col0\" class=\"data row2 col0\" >0.649913</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col1\" class=\"data row2 col1\" >0.215304</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col2\" class=\"data row2 col2\" >0.318174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col3\" class=\"data row2 col3\" >0.194696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col4\" class=\"data row2 col4\" >0.344522</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col5\" class=\"data row2 col5\" >1.37809</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col6\" class=\"data row2 col6\" >0.649913</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col7\" class=\"data row2 col7\" >0.215304</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col8\" class=\"data row2 col8\" >0.318174</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col9\" class=\"data row2 col9\" >0.194696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row2_col10\" class=\"data row2 col10\" >1.37809</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row3\" class=\"row_heading level0 row3\" >Jaccard</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col0\" class=\"data row3 col0\" >0.609043</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col1\" class=\"data row3 col1\" >0.217217</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col2\" class=\"data row3 col2\" >0.303739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col3\" class=\"data row3 col3\" >0.182957</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col4\" class=\"data row3 col4\" >0.328239</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col5\" class=\"data row3 col5\" >1.31296</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col6\" class=\"data row3 col6\" >0.609043</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col7\" class=\"data row3 col7\" >0.217217</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col8\" class=\"data row3 col8\" >0.303739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col9\" class=\"data row3 col9\" >0.182957</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row3_col10\" class=\"data row3 col10\" >1.31296</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row4\" class=\"row_heading level0 row4\" >DeepWalk</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col0\" class=\"data row4 col0\" >0.463217</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col1\" class=\"data row4 col1\" >0.348609</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col2\" class=\"data row4 col2\" >0.127043</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col3\" class=\"data row4 col3\" >0.060087</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col4\" class=\"data row4 col4\" >0.249739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col5\" class=\"data row4 col5\" >0.998957</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col6\" class=\"data row4 col6\" >0.463217</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col7\" class=\"data row4 col7\" >0.348609</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col8\" class=\"data row4 col8\" >0.127043</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col9\" class=\"data row4 col9\" >0.060087</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row4_col10\" class=\"data row4 col10\" >0.998957</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row5\" class=\"row_heading level0 row5\" >WeisfeleirLehmanKernel</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col0\" class=\"data row5 col0\" >0.352435</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col1\" class=\"data row5 col1\" >0.541913</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col2\" class=\"data row5 col2\" >0.0561739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col3\" class=\"data row5 col3\" >0.00417391</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col4\" class=\"data row5 col4\" >0.238674</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col5\" class=\"data row5 col5\" >0.954696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col6\" class=\"data row5 col6\" >0.352435</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col7\" class=\"data row5 col7\" >0.541913</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col8\" class=\"data row5 col8\" >0.0561739</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col9\" class=\"data row5 col9\" >0.00417391</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row5_col10\" class=\"data row5 col10\" >0.954696</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row6\" class=\"row_heading level0 row6\" >GraphEditDistance</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col0\" class=\"data row6 col0\" >0.372727</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col1\" class=\"data row6 col1\" >0.144182</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col2\" class=\"data row6 col2\" >0.150545</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col3\" class=\"data row6 col3\" >0.107091</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col4\" class=\"data row6 col4\" >0.193636</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col5\" class=\"data row6 col5\" >0.774545</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col6\" class=\"data row6 col6\" >0.372727</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col7\" class=\"data row6 col7\" >0.144182</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col8\" class=\"data row6 col8\" >0.150545</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col9\" class=\"data row6 col9\" >0.107091</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row6_col10\" class=\"data row6 col10\" >0.774545</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row7\" class=\"row_heading level0 row7\" >PolyIntersect</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col0\" class=\"data row7 col0\" >0.1696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col1\" class=\"data row7 col1\" >0.1124</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col2\" class=\"data row7 col2\" >0.0596</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col3\" class=\"data row7 col3\" >0.0408</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col4\" class=\"data row7 col4\" >0.0956</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col5\" class=\"data row7 col5\" >0.3824</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col6\" class=\"data row7 col6\" >0.1696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col7\" class=\"data row7 col7\" >0.1124</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col8\" class=\"data row7 col8\" >0.0596</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col9\" class=\"data row7 col9\" >0.0408</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row7_col10\" class=\"data row7 col10\" >0.3824</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820level0_row8\" class=\"row_heading level0 row8\" >Graph2Vec</th>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col0\" class=\"data row8 col0\" >0.0206087</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col1\" class=\"data row8 col1\" >0.0264348</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col2\" class=\"data row8 col2\" >0.00243478</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col3\" class=\"data row8 col3\" >0</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col4\" class=\"data row8 col4\" >0.0123696</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col5\" class=\"data row8 col5\" >0.0494783</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col6\" class=\"data row8 col6\" >0.0206087</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col7\" class=\"data row8 col7\" >0.0264348</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col8\" class=\"data row8 col8\" >0.00243478</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col9\" class=\"data row8 col9\" >0</td>\n",
- " <td id=\"T_6afb48ae_4af9_11e9_8332_6a0002e84820row8_col10\" class=\"data row8 col10\" >0.0494783</td>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >BOW</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col0\" class=\"data row0 col0\" >0.67284</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col1\" class=\"data row0 col1\" >0.245059</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.395483</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.223377</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.683918</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col5\" class=\"data row0 col5\" >0.38419</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row0_col6\" class=\"data row0 col6\" >1.53676</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >VertexEdgeOverlap</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col0\" class=\"data row1 col0\" >0.672501</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col1\" class=\"data row1 col1\" >0.245398</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.38611</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col3\" class=\"data row1 col3\" >0.223377</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col4\" class=\"data row1 col4\" >0.693066</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col5\" class=\"data row1 col5\" >0.381846</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row1_col6\" class=\"data row1 col6\" >1.52739</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row2\" class=\"row_heading level0 row2\" >MCS</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col0\" class=\"data row2 col0\" >0.657256</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col1\" class=\"data row2 col1\" >0.247883</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col2\" class=\"data row2 col2\" >0.388707</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col3\" class=\"data row2 col3\" >0.223377</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col4\" class=\"data row2 col4\" >0.684032</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col5\" class=\"data row2 col5\" >0.379305</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row2_col6\" class=\"data row2 col6\" >1.51722</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row3\" class=\"row_heading level0 row3\" >Jaccard</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col0\" class=\"data row3 col0\" >0.640994</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col1\" class=\"data row3 col1\" >0.240542</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col2\" class=\"data row3 col2\" >0.372671</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col3\" class=\"data row3 col3\" >0.210615</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col4\" class=\"data row3 col4\" >0.660207</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col5\" class=\"data row3 col5\" >0.366206</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row3_col6\" class=\"data row3 col6\" >1.46482</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row4\" class=\"row_heading level0 row4\" >DeepWalk</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col0\" class=\"data row4 col0\" >0.49712</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col1\" class=\"data row4 col1\" >0.389723</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col2\" class=\"data row4 col2\" >0.152005</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col3\" class=\"data row4 col3\" >0.0658385</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col4\" class=\"data row4 col4\" >0.610745</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col5\" class=\"data row4 col5\" >0.276172</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row4_col6\" class=\"data row4 col6\" >1.10469</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row5\" class=\"row_heading level0 row5\" >WeisfeleirLehmanKernel</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col0\" class=\"data row5 col0\" >0.394128</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col1\" class=\"data row5 col1\" >0.493619</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col2\" class=\"data row5 col2\" >0.0725014</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col3\" class=\"data row5 col3\" >0.00496894</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col4\" class=\"data row5 col4\" >0.528249</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col5\" class=\"data row5 col5\" >0.241304</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row5_col6\" class=\"data row5 col6\" >0.965217</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row6\" class=\"row_heading level0 row6\" >GraphEditDistance</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col0\" class=\"data row6 col0\" >0.379693</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col1\" class=\"data row6 col1\" >0.170248</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col2\" class=\"data row6 col2\" >0.186068</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col3\" class=\"data row6 col3\" >0.121842</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col4\" class=\"data row6 col4\" >0.430875</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col5\" class=\"data row6 col5\" >0.214463</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row6_col6\" class=\"data row6 col6\" >0.857851</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row7\" class=\"row_heading level0 row7\" >PolyIntersect</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col0\" class=\"data row7 col0\" >0.189091</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col1\" class=\"data row7 col1\" >0.122597</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col2\" class=\"data row7 col2\" >0.0774026</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col3\" class=\"data row7 col3\" >0.052987</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col4\" class=\"data row7 col4\" >0.227495</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col5\" class=\"data row7 col5\" >0.110519</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row7_col6\" class=\"data row7 col6\" >0.442078</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820level0_row8\" class=\"row_heading level0 row8\" >Graph2Vec</th>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col0\" class=\"data row8 col0\" >0.0246189</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col1\" class=\"data row8 col1\" >0.0280068</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col2\" class=\"data row8 col2\" >0.00316206</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col3\" class=\"data row8 col3\" >0</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col4\" class=\"data row8 col4\" >0.0395227</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col5\" class=\"data row8 col5\" >0.0139469</td>\n",
+ " <td id=\"T_1102a8f4_4c06_11e9_af47_6a0002e84820row8_col6\" class=\"data row8 col6\" >0.0557877</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
- "<pandas.io.formats.style.Styler at 0x13c658668>"
+ "<pandas.io.formats.style.Styler at 0x10ede50f0>"
]
},
- "execution_count": 120,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -1094,7 +841,7 @@
},
{
"cell_type": "code",
- "execution_count": 125,
+ "execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2018-09-26T12:55:10.937714Z",
@@ -1106,342 +853,310 @@
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" color: white;\n",
- " }</style><table id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >mesure</th> <th class=\"col_heading level0 col1\" >type</th> <th class=\"col_heading level0 col2\" >c1</th> <th class=\"col_heading level0 col3\" >c2</th> <th class=\"col_heading level0 col4\" >c3</th> <th class=\"col_heading level0 col5\" >c4</th> <th class=\"col_heading level0 col6\" >mean</th> <th class=\"col_heading level0 col7\" >sum</th> <th class=\"col_heading level0 col8\" >c1_w</th> <th class=\"col_heading level0 col9\" >c2_w</th> <th class=\"col_heading level0 col10\" >c3_w</th> <th class=\"col_heading level0 col11\" >c4_w</th> <th class=\"col_heading level0 col12\" >sum_w</th> </tr></thead><tbody>\n",
+ " }</style><table id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >mesure</th> <th class=\"col_heading level0 col1\" >type</th> <th class=\"col_heading level0 col2\" >c1</th> <th class=\"col_heading level0 col3\" >c2</th> <th class=\"col_heading level0 col4\" >c3</th> <th class=\"col_heading level0 col5\" >c4</th> <th class=\"col_heading level0 col6\" >c5</th> <th class=\"col_heading level0 col7\" >mean</th> <th class=\"col_heading level0 col8\" >sum</th> </tr></thead><tbody>\n",
" <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >51</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col0\" class=\"data row0 col0\" >MCS</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col1\" class=\"data row0 col1\" >ext_2</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.7</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.216</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.332</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col5\" class=\"data row0 col5\" >0.198</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col6\" class=\"data row0 col6\" >0.3615</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col7\" class=\"data row0 col7\" >1.446</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col8\" class=\"data row0 col8\" >0.7</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col9\" class=\"data row0 col9\" >0.216</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col10\" class=\"data row0 col10\" >0.332</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col11\" class=\"data row0 col11\" >0.198</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row0_col12\" class=\"data row0 col12\" >1.446</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >7</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col0\" class=\"data row1 col0\" >BOW</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col1\" class=\"data row1 col1\" >dev_du</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.698</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col3\" class=\"data row1 col3\" >0.196</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col4\" class=\"data row1 col4\" >0.336</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col5\" class=\"data row1 col5\" >0.2</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col6\" class=\"data row1 col6\" >0.3575</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col7\" class=\"data row1 col7\" >1.43</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col8\" class=\"data row1 col8\" >0.698</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col9\" class=\"data row1 col9\" >0.196</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col10\" class=\"data row1 col10\" >0.336</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col11\" class=\"data row1 col11\" >0.2</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row1_col12\" class=\"data row1 col12\" >1.43</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row2\" class=\"row_heading level0 row2\" >29</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col0\" class=\"data row2 col0\" >MCS</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col1\" class=\"data row2 col1\" >biotex_lda_bvlac_ext_1</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col2\" class=\"data row2 col2\" >0.656</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col3\" class=\"data row2 col3\" >0.226</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col4\" class=\"data row2 col4\" >0.306</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col5\" class=\"data row2 col5\" >0.194</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col6\" class=\"data row2 col6\" >0.3455</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col7\" class=\"data row2 col7\" >1.382</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col8\" class=\"data row2 col8\" >0.656</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col9\" class=\"data row2 col9\" >0.226</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col10\" class=\"data row2 col10\" >0.306</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col11\" class=\"data row2 col11\" >0.194</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row2_col12\" class=\"data row2 col12\" >1.382</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row3\" class=\"row_heading level0 row3\" >21</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col0\" class=\"data row3 col0\" >VertexEdgeOverlap</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col1\" class=\"data row3 col1\" >biotex_lda_bvlac_gen_country</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col2\" class=\"data row3 col2\" >0.63</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col3\" class=\"data row3 col3\" >0.224</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col4\" class=\"data row3 col4\" >0.318</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col5\" class=\"data row3 col5\" >0.192</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col6\" class=\"data row3 col6\" >0.341</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col7\" class=\"data row3 col7\" >1.364</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col8\" class=\"data row3 col8\" >0.63</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col9\" class=\"data row3 col9\" >0.224</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col10\" class=\"data row3 col10\" >0.318</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col11\" class=\"data row3 col11\" >0.192</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row3_col12\" class=\"data row3 col12\" >1.364</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row4\" class=\"row_heading level0 row4\" >20</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col0\" class=\"data row4 col0\" >MCS</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col1\" class=\"data row4 col1\" >inra_gen_country</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col2\" class=\"data row4 col2\" >0.628</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col3\" class=\"data row4 col3\" >0.226</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col4\" class=\"data row4 col4\" >0.306</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col5\" class=\"data row4 col5\" >0.192</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col6\" class=\"data row4 col6\" >0.338</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col7\" class=\"data row4 col7\" >1.352</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col8\" class=\"data row4 col8\" >0.628</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col9\" class=\"data row4 col9\" >0.226</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col10\" class=\"data row4 col10\" >0.306</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col11\" class=\"data row4 col11\" >0.192</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row4_col12\" class=\"data row4 col12\" >1.352</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row5\" class=\"row_heading level0 row5\" >8</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col0\" class=\"data row5 col0\" >BOW</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col1\" class=\"data row5 col1\" >biotex_lda_bvlac</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col2\" class=\"data row5 col2\" >0.624</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col3\" class=\"data row5 col3\" >0.232</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col4\" class=\"data row5 col4\" >0.302</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col5\" class=\"data row5 col5\" >0.19</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col6\" class=\"data row5 col6\" >0.337</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col7\" class=\"data row5 col7\" >1.348</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col8\" class=\"data row5 col8\" >0.624</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col9\" class=\"data row5 col9\" >0.232</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col10\" class=\"data row5 col10\" >0.302</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col11\" class=\"data row5 col11\" >0.19</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row5_col12\" class=\"data row5 col12\" >1.348</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row6\" class=\"row_heading level0 row6\" >55</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col0\" class=\"data row6 col0\" >Jaccard</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col1\" class=\"data row6 col1\" >dev_du_ext_2</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col2\" class=\"data row6 col2\" >0.598</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col3\" class=\"data row6 col3\" >0.232</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col4\" class=\"data row6 col4\" >0.32</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col5\" class=\"data row6 col5\" >0.198</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col6\" class=\"data row6 col6\" >0.337</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col7\" class=\"data row6 col7\" >1.348</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col8\" class=\"data row6 col8\" >0.598</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col9\" class=\"data row6 col9\" >0.232</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col10\" class=\"data row6 col10\" >0.32</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col11\" class=\"data row6 col11\" >0.198</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row6_col12\" class=\"data row6 col12\" >1.348</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row7\" class=\"row_heading level0 row7\" >30</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col0\" class=\"data row7 col0\" >WeisfeleirLehmanKernel</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col1\" class=\"data row7 col1\" >biotex_bvlac</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col2\" class=\"data row7 col2\" >0.41</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col3\" class=\"data row7 col3\" >0.574</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col4\" class=\"data row7 col4\" >0.032</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col5\" class=\"data row7 col5\" >0.004</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col6\" class=\"data row7 col6\" >0.255</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col7\" class=\"data row7 col7\" >1.02</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col8\" class=\"data row7 col8\" >0.41</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col9\" class=\"data row7 col9\" >0.574</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col10\" class=\"data row7 col10\" >0.032</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col11\" class=\"data row7 col11\" >0.004</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row7_col12\" class=\"data row7 col12\" >1.02</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row8\" class=\"row_heading level0 row8\" >28</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col0\" class=\"data row8 col0\" >DeepWalk</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col1\" class=\"data row8 col1\" >biotex_lda_bvlac_ext_2</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col2\" class=\"data row8 col2\" >0.426</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col3\" class=\"data row8 col3\" >0.4</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col4\" class=\"data row8 col4\" >0.1</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col5\" class=\"data row8 col5\" >0.05</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col6\" class=\"data row8 col6\" >0.244</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col7\" class=\"data row8 col7\" >0.976</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col8\" class=\"data row8 col8\" >0.426</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col9\" class=\"data row8 col9\" >0.4</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col10\" class=\"data row8 col10\" >0.1</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col11\" class=\"data row8 col11\" >0.05</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row8_col12\" class=\"data row8 col12\" >0.976</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row9\" class=\"row_heading level0 row9\" >49</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col0\" class=\"data row9 col0\" >GraphEditDistance</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col1\" class=\"data row9 col1\" >dev_du_gen_region</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col2\" class=\"data row9 col2\" >0.106</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col3\" class=\"data row9 col3\" >0.098</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col4\" class=\"data row9 col4\" >0.002</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col5\" class=\"data row9 col5\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col6\" class=\"data row9 col6\" >0.0515</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col7\" class=\"data row9 col7\" >0.206</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col8\" class=\"data row9 col8\" >0.106</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col9\" class=\"data row9 col9\" >0.098</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col10\" class=\"data row9 col10\" >0.002</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col11\" class=\"data row9 col11\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row9_col12\" class=\"data row9 col12\" >0.206</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820level0_row10\" class=\"row_heading level0 row10\" >1</th>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col0\" class=\"data row10 col0\" >Graph2Vec</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col1\" class=\"data row10 col1\" >biotex_bvlac_ext_1</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col2\" class=\"data row10 col2\" >0.012</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col3\" class=\"data row10 col3\" >0.026</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col4\" class=\"data row10 col4\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col5\" class=\"data row10 col5\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col6\" class=\"data row10 col6\" >0.0095</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col7\" class=\"data row10 col7\" >0.038</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col8\" class=\"data row10 col8\" >0.012</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col9\" class=\"data row10 col9\" >0.026</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col10\" class=\"data row10 col10\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col11\" class=\"data row10 col11\" >0</td>\n",
- " <td id=\"T_f54c6818_4afa_11e9_bcf6_6a0002e84820row10_col12\" class=\"data row10 col12\" >0.038</td>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >6</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col0\" class=\"data row0 col0\" >BOW</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col1\" class=\"data row0 col1\" >inra_gen_country</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.685714</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.290909</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.418182</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col5\" class=\"data row0 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col6\" class=\"data row0 col6\" >0.708985</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col7\" class=\"data row0 col7\" >0.404545</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row0_col8\" class=\"data row0 col8\" >1.61818</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >5</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col0\" class=\"data row1 col0\" >VertexEdgeOverlap</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col1\" class=\"data row1 col1\" >gen_country</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.654545</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col3\" class=\"data row1 col3\" >0.280519</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col4\" class=\"data row1 col4\" >0.397403</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col5\" class=\"data row1 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col6\" class=\"data row1 col6\" >0.706389</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col7\" class=\"data row1 col7\" >0.388961</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row1_col8\" class=\"data row1 col8\" >1.55584</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row2\" class=\"row_heading level0 row2\" >21</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col0\" class=\"data row2 col0\" >VertexEdgeOverlap</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col1\" class=\"data row2 col1\" >biotex_lda_bvlac_gen_country</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col2\" class=\"data row2 col2\" >0.662338</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col3\" class=\"data row2 col3\" >0.272727</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col4\" class=\"data row2 col4\" >0.38961</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col5\" class=\"data row2 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col6\" class=\"data row2 col6\" >0.703791</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col7\" class=\"data row2 col7\" >0.387013</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row2_col8\" class=\"data row2 col8\" >1.54805</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row3\" class=\"row_heading level0 row3\" >29</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col0\" class=\"data row3 col0\" >MCS</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col1\" class=\"data row3 col1\" >biotex_lda_bvlac_ext_1</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col2\" class=\"data row3 col2\" >0.67013</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col3\" class=\"data row3 col3\" >0.267532</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col4\" class=\"data row3 col4\" >0.374026</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col5\" class=\"data row3 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col6\" class=\"data row3 col6\" >0.708985</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col7\" class=\"data row3 col7\" >0.383766</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row3_col8\" class=\"data row3 col8\" >1.53506</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row4\" class=\"row_heading level0 row4\" >19</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col0\" class=\"data row4 col0\" >MCS</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col1\" class=\"data row4 col1\" >biotex_lda_bvlac_ext_2</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col2\" class=\"data row4 col2\" >0.664935</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col3\" class=\"data row4 col3\" >0.267532</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col4\" class=\"data row4 col4\" >0.371429</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col5\" class=\"data row4 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col6\" class=\"data row4 col6\" >0.708985</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col7\" class=\"data row4 col7\" >0.381818</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row4_col8\" class=\"data row4 col8\" >1.52727</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row5\" class=\"row_heading level0 row5\" >69</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col0\" class=\"data row5 col0\" >VertexEdgeOverlap</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col1\" class=\"data row5 col1\" >dev_du_gen_region</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col2\" class=\"data row5 col2\" >0.667532</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col3\" class=\"data row5 col3\" >0.249351</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col4\" class=\"data row5 col4\" >0.381818</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col5\" class=\"data row5 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col6\" class=\"data row5 col6\" >0.690807</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col7\" class=\"data row5 col7\" >0.380519</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row5_col8\" class=\"data row5 col8\" >1.52208</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row6\" class=\"row_heading level0 row6\" >20</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col0\" class=\"data row6 col0\" >MCS</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col1\" class=\"data row6 col1\" >inra_gen_country</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col2\" class=\"data row6 col2\" >0.646753</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col3\" class=\"data row6 col3\" >0.262338</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col4\" class=\"data row6 col4\" >0.374026</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col5\" class=\"data row6 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col6\" class=\"data row6 col6\" >0.66224</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col7\" class=\"data row6 col7\" >0.376623</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row6_col8\" class=\"data row6 col8\" >1.50649</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row7\" class=\"row_heading level0 row7\" >54</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col0\" class=\"data row7 col0\" >Jaccard</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col1\" class=\"data row7 col1\" >inra</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col2\" class=\"data row7 col2\" >0.654545</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col3\" class=\"data row7 col3\" >0.212987</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col4\" class=\"data row7 col4\" >0.394805</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col5\" class=\"data row7 col5\" >0.223377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col6\" class=\"data row7 col6\" >0.649255</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col7\" class=\"data row7 col7\" >0.371429</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row7_col8\" class=\"data row7 col8\" >1.48571</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row8\" class=\"row_heading level0 row8\" >28</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col0\" class=\"data row8 col0\" >DeepWalk</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col1\" class=\"data row8 col1\" >biotex_lda_bvlac_ext_2</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col2\" class=\"data row8 col2\" >0.462338</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col3\" class=\"data row8 col3\" >0.433766</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col4\" class=\"data row8 col4\" >0.119481</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col5\" class=\"data row8 col5\" >0.0623377</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col6\" class=\"data row8 col6\" >0.659632</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col7\" class=\"data row8 col7\" >0.269481</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row8_col8\" class=\"data row8 col8\" >1.07792</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row9\" class=\"row_heading level0 row9\" >30</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col0\" class=\"data row9 col0\" >WeisfeleirLehmanKernel</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col1\" class=\"data row9 col1\" >biotex_bvlac</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col2\" class=\"data row9 col2\" >0.47013</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col3\" class=\"data row9 col3\" >0.527273</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col4\" class=\"data row9 col4\" >0.0415584</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col5\" class=\"data row9 col5\" >0.00519481</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col6\" class=\"data row9 col6\" >0.568792</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col7\" class=\"data row9 col7\" >0.261039</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row9_col8\" class=\"data row9 col8\" >1.04416</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row10\" class=\"row_heading level0 row10\" >52</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col0\" class=\"data row10 col0\" >Graph2Vec</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col1\" class=\"data row10 col1\" >biotex_lda_bvlac</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col2\" class=\"data row10 col2\" >0.0285714</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col3\" class=\"data row10 col3\" >0.0415584</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col4\" class=\"data row10 col4\" >0.0025974</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col5\" class=\"data row10 col5\" >0</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col6\" class=\"data row10 col6\" >0.0545411</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col7\" class=\"data row10 col7\" >0.0181818</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row10_col8\" class=\"data row10 col8\" >0.0727273</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820level0_row11\" class=\"row_heading level0 row11\" >1</th>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col0\" class=\"data row11 col0\" >Graph2Vec</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col1\" class=\"data row11 col1\" >biotex_bvlac_ext_1</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col2\" class=\"data row11 col2\" >0.0155844</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col3\" class=\"data row11 col3\" >0.0207792</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col4\" class=\"data row11 col4\" >0</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col5\" class=\"data row11 col5\" >0</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col6\" class=\"data row11 col6\" >0.0363613</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col7\" class=\"data row11 col7\" >0.00909091</td>\n",
+ " <td id=\"T_239dc4d8_4c06_11e9_895b_6a0002e84820row11_col8\" class=\"data row11 col8\" >0.0363636</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
- "<pandas.io.formats.style.Styler at 0x13d4df048>"
+ "<pandas.io.formats.style.Styler at 0x135903da0>"
]
},
- "execution_count": 125,
+ "execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "index,data_pa=pareto_frontier_multi(data[\"c1 c2 c3 c4\".split()].values)\n",
+ "index,data_pa=pareto_frontier_multi(data[\"c1 c2 c3 c4 c5\".split()].values)\n",
"colorize(data.iloc[index].sort_values(\"sum\",ascending=False),to_colorize)\n"
]
},
{
"cell_type": "code",
- "execution_count": 131,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
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" color: white;\n",
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+ " }</style><table id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >mesure</th> <th class=\"col_heading level0 col1\" >type</th> <th class=\"col_heading level0 col2\" >c1</th> <th class=\"col_heading level0 col3\" >c2</th> <th class=\"col_heading level0 col4\" >c3</th> <th class=\"col_heading level0 col5\" >c4</th> <th class=\"col_heading level0 col6\" >c5</th> <th class=\"col_heading level0 col7\" >mean</th> <th class=\"col_heading level0 col8\" >sum</th> <th class=\"col_heading level0 col9\" >c1_w</th> <th class=\"col_heading level0 col10\" >c2_w</th> <th class=\"col_heading level0 col11\" >c3_w</th> <th class=\"col_heading level0 col12\" >c4_w</th> <th class=\"col_heading level0 col13\" >sum_w</th> <th class=\"col_heading level0 col14\" >c5_w</th> </tr></thead><tbody>\n",
" <tr>\n",
- " <th id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >7</th>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row0_col0\" class=\"data row0 col0\" >BOW</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row0_col1\" class=\"data row0 col1\" >dev_du</td>\n",
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- " <tr>\n",
- " <th id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820level0_row1\" class=\"row_heading level0 row1\" >32</th>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col0\" class=\"data row1 col0\" >BOW</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col1\" class=\"data row1 col1\" >biotex_bvlac_gen_region</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col2\" class=\"data row1 col2\" >0.622</td>\n",
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- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col7\" class=\"data row1 col7\" >1.336</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col8\" class=\"data row1 col8\" >0.622</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col9\" class=\"data row1 col9\" >0.208</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col10\" class=\"data row1 col10\" >0.314</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col11\" class=\"data row1 col11\" >0.192</td>\n",
- " <td id=\"T_35e6ba34_4afb_11e9_bbce_6a0002e84820row1_col12\" class=\"data row1 col12\" >1.336</td>\n",
+ " <th id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820level0_row0\" class=\"row_heading level0 row0\" >7</th>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col0\" class=\"data row0 col0\" >BOW</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col1\" class=\"data row0 col1\" >dev_du</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col2\" class=\"data row0 col2\" >0.698</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col3\" class=\"data row0 col3\" >0.194</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col4\" class=\"data row0 col4\" >0.342</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col5\" class=\"data row0 col5\" >0.202</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col6\" class=\"data row0 col6\" >0.589836</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col7\" class=\"data row0 col7\" >0.359</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col8\" class=\"data row0 col8\" >1.436</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col9\" class=\"data row0 col9\" >0.0698</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col10\" class=\"data row0 col10\" >0.0776</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col11\" class=\"data row0 col11\" >0.1368</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col12\" class=\"data row0 col12\" >0.0202</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col13\" class=\"data row0 col13\" >0.363384</td>\n",
+ " <td id=\"T_f8f26ac6_4bfe_11e9_94f0_6a0002e84820row0_col14\" class=\"data row0 col14\" >0.0589836</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
- "<pandas.io.formats.style.Styler at 0x13d608f28>"
+ "<pandas.io.formats.style.Styler at 0x12b1a1940>"
]
},
- "execution_count": 131,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "index,data_pa=pareto_frontier_multi(data[data.mesure==\"BOW\"][\"c1 c2 c3 c4\".split()].values)\n",
+ "index,data_pa=pareto_frontier_multi(data[data.mesure==\"BOW\"][\"c1 c2 c5\".split()].values)\n",
"colorize(data[data.mesure==\"BOW\"].iloc[index].sort_values(\"sum\",ascending=False).head(15),to_colorize)"
]
},
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diff --git a/run_automatic_annotation.py b/run_automatic_annotation.py
index 8e64ae4..bf04d41 100644
--- a/run_automatic_annotation.py
+++ b/run_automatic_annotation.py
@@ -1,22 +1,44 @@
# coding = utf-8
-import argparse
-import logging,json
+import argparse, shutil, os
+import logging, json
+from mytoolbox.env import yes_or_no
+from auto_fill_annotation import main
+
for _ in ("boto", "elasticsearch", "urllib3", "sklearn"):
logging.getLogger(_).setLevel(logging.CRITICAL)
-parser=argparse.ArgumentParser()
+parser = argparse.ArgumentParser()
-parser.add_argument("dataset",help="Name of the dataset")
-parser.add_argument("sim_matrix_dir",help="Similarity Matrix Directory")
+parser.add_argument("dataset", help="Name of the dataset")
+parser.add_argument("sim_matrix_dir", help="Similarity Matrix Directory")
parser.add_argument("graph_data_dir", help="STR without transformation graph directory")
-parser.add_argument("adjacency_fn", help ="Adjacency Information json filename")
-parser.add_argument("inclusion_fn", help ="Inclusion Information json filename")
-parser.add_argument("selected_json_file",help="Filename containing the STR graph you want to make your evaluation on")
-parser.add_argument("-t","--threshold",default=0.5,help="Threshold for the third criteria")
+parser.add_argument("adjacency_fn", help="Adjacency Information json filename")
+parser.add_argument("inclusion_fn", help="Inclusion Information json filename")
+parser.add_argument("selected_json_file", help="Filename containing the STR graph you want to make your evaluation on")
+parser.add_argument("length_json_file", help="Filename containing the STR text length")
+parser.add_argument("-t", "--threshold", default=0.5, help="Threshold for the third criteria")
+parser.add_argument("-g", "--ming1",type=int, default=0, help="Return evaluation results based on min size for G1")
+parser.add_argument("-j", "--ming2",type=int, default=0, help="Return evaluation results based on min size for G2")
+parser.add_argument("-m", "--nb_car_doc1",type=int, default=0, help="Return evaluation results based on min size of associated text for G1")
+parser.add_argument("-n", "--nb_car_doc2",type=int, default=0, help="Return evaluation results based on min size of associated text for G2")
+
+args = parser.parse_args()
+if os.path.exists("temp_cluster") and yes_or_no("Do you want to compute STR's clusters all over again ?"):
+ shutil.rmtree('temp_cluster', ignore_errors=True)
+ os.makedirs("temp_cluster")
-args=parser.parse_args()
-from auto_fill_annotation import main
-main(args.dataset,args.sim_matrix_dir,args.graph_data_dir,json.load(open(args.selected_json_file)),args.threshold,args.inclusion_fn, args.adjacency_fn)
\ No newline at end of file
+main(args.dataset,
+ args.sim_matrix_dir,
+ args.graph_data_dir,
+ json.load(open(args.selected_json_file)),
+ args.threshold,
+ args.inclusion_fn,
+ args.adjacency_fn,
+ args.length_json_file,
+ args.ming1,
+ args.ming2,
+ args.nb_car_doc1,
+ args.nb_car_doc2)
diff --git a/run_test.py b/run_test.py
new file mode 100644
index 0000000..11246ec
--- /dev/null
+++ b/run_test.py
@@ -0,0 +1,128 @@
+# coding = utf-8
+import argparse
+import os
+
+import pandas as pd
+import numpy as np
+
+from tqdm import tqdm
+from skcriteria.madm import closeness, simple
+from skcriteria import Data, MIN, MAX
+
+
+def pareto_frontier_multi(myArray):
+ # Sort on first dimension
+ myArray = myArray[myArray[:, 0].argsort()]
+ # Add first row to pareto_frontier
+ pareto_frontier = myArray[0:1, :]
+ indices, i = [], 1
+ # Test next row against the last row in pareto_frontier
+ for row in myArray[1:, :]:
+ if sum([row[x] >= pareto_frontier[-1][x]
+ for x in range(len(row))]) == len(row):
+ # If it is better on all features add the row to pareto_frontier
+ pareto_frontier = np.concatenate((pareto_frontier, [row]))
+ indices.append(i)
+ i += 1
+ return indices, pareto_frontier
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("input")
+parser.add_argument("output_fn")
+parser.add_argument("-t","--topn",type=int,default=5)
+args = parser.parse_args()
+
+writer = pd.ExcelWriter(args.output_fn, engine='xlsxwriter')
+
+if not os.path.exists(args.input):
+ raise FileNotFoundError("{0} does not exists !".format(args.input))
+
+data = pd.read_csv(args.input, index_col=0)
+data["mesure"] = data.mesure.apply(lambda x: "BOW" if x == "BagOfNodes" else x)
+data["sum"] = data["c1 c2 c3 c4 c5".split()].sum(axis=1)
+
+combination_pareto_criteria = [
+ ("c1_c2_c3_c4_c5", "c1 c2 c3 c4 c5".split()),
+ ("c1_c2_c5", "c1 c2 c5".split()),
+ ("c1_c2_c3", "c1 c2 c3".split()),
+ ("c3_c4", "c3 c4".split()),
+ ("c5", "c5".split()),
+ ("c2", "c2".split()),
+]
+
+weight_criteria = [
+ ("all_0.2", [0.2, 0.2, 0.2, 0.2, 0.2]),
+ ("c1_0.5_c5_0.5", [0.5, 0., 0., 0., 0.5]),
+ ("c2_0.5_c5_0.5", [0., 0.5, 0., 0., 0.5]),
+ ("c1_0.33_c2_0.33_c3_0,33", [0.33, 0.33, 0.33, 0., 0.]),
+ ("c1_0.5_c2_0.5", [0.5, 0.5, 0., 0., 0.]),
+ ("c3_0.5_c4_0.5", [0., 0., 0.5, 0.5, 0.])
+]
+
+
+def get_top_combination_wsm(dataframe, weights,topn):
+ data = dataframe["c1 c2 c3 c4 c5".split()].values
+ dd = Data(data, criteria=[MAX, MAX, MAX, MAX, MAX], weights=weights[1])
+ index_max = np.argsort(simple.WeightedSum().decide(dd)._rank)[:topn]
+ df = dataframe.iloc[index_max]
+ df["name"]=weights[0]
+ df["type_score"] = "wsm"
+ return df
+
+
+def get_top_combination_pareto(dataframe, columns,topn):
+ index, data_pa = pareto_frontier_multi(dataframe[columns[1]].values)
+ df = data.iloc[index]
+ df = df.sort_values(by = "sum",ascending=False).head(topn)
+ df["name"]=columns[0]
+ df["type_score"] = "pareto"
+ return df
+
+
+def write_excel(writer, dataframe, title):
+ dataframe.to_excel(writer, "result", index=False)
+ number_of_rows=len(dataframe)
+ worksheet = writer.sheets["result"]
+ workbook = writer.book
+ C_letter = 67
+ I_letter= 73
+
+ format1 = workbook.add_format({'bg_color': '#FFC7CE',
+ 'font_color': '#9C0006'})
+
+ # Add a format. Green fill with dark green text.
+ format2 = workbook.add_format({'bg_color': '#C6EFCE',
+ 'font_color': '#006100'})
+ for i in range(C_letter,I_letter):
+ begin=2
+ for end in range(6,number_of_rows + 1,5):
+ ch_=chr(i)
+ color_range = "{0}{1}:{0}{2}".format(ch_,begin,end)
+ worksheet.conditional_format(color_range, {'type': 'bottom',
+ 'value': '1',
+ 'format': format1})
+
+ worksheet.conditional_format(color_range, {'type': 'top',
+ 'value': '1',
+ 'format': format2})
+ begin=end+1
+ writer.save()
+
+result = None
+for comb_ in tqdm(combination_pareto_criteria, desc="Pareto computation"):
+ dd = get_top_combination_pareto(data, comb_,args.topn)
+ if not isinstance(result,pd.DataFrame):
+ result = dd
+ else:
+ result = pd.concat((result,dd),axis=0)
+
+for weight in tqdm(weight_criteria, desc="WSM computation"):
+ dd= get_top_combination_wsm(data, weight,args.topn)
+ if not isinstance(result,pd.DataFrame):
+ result = dd
+ else:
+ result = pd.concat((result,dd),axis=0)
+
+
+write_excel(writer,result,args.output_fn.split("/")[-1])
\ No newline at end of file
diff --git a/strpython/eval/automatic_annotation.py b/strpython/eval/automatic_annotation.py
index c5fb261..1ff9150 100644
--- a/strpython/eval/automatic_annotation.py
+++ b/strpython/eval/automatic_annotation.py
@@ -9,6 +9,17 @@ from ..models.str import STR
from ..helpers.match_cache import MatchingCache
from ..helpers.relation_extraction import AdjacencyRelation, InclusionRelation
+import sys
+
+class JsonProgress(object):
+ def __init__(self,fn):
+ self.count = 0
+ self.fn= fn
+ def __call__(self, obj):
+ self.count += 1
+ if self.count %10 == 0:
+ sys.stdout.write("\rLoading"+self.fn+": %8d" % self.count)
+ return obj
class AnnotationAutomatic(object):
"""
@@ -23,10 +34,11 @@ class AnnotationAutomatic(object):
self.inc_rel_db = InclusionRelation()
self.inclusion,self.adjacency = {},{}
if inclusion_fn:
- self.inclusion = json.load(open(inclusion_fn))
+ self.inclusion = json.load(open(inclusion_fn),object_hook=JsonProgress(inclusion_fn))
if adjacency_fn:
- self.adjacency = json.load(open(adjacency_fn))
+ self.adjacency = json.load(open(adjacency_fn),object_hook=JsonProgress(adjacency_fn))
self.threshold = threshold_c3
+
def all(self, str1, str2, id1=None, id2=None):
"""
@@ -47,7 +59,7 @@ class AnnotationAutomatic(object):
return list(value)
crit_ = [self.criterion1(str1, str2), self.criterion2(str1, str2), self.criterion3(str1, str2, id1, id2),
- self.criterion4(str1, str2, id1, id2)]
+ self.criterion4(str1, str2, id1, id2),self.criteria5(str1, str2, id1, id2)]
self.matching_cache.add(id1, id2, *crit_)
return crit_
diff --git a/strpython/helpers/geo_relation_database.py b/strpython/helpers/geo_relation_database.py
index 772d43c..a51cbff 100644
--- a/strpython/helpers/geo_relation_database.py
+++ b/strpython/helpers/geo_relation_database.py
@@ -27,7 +27,7 @@ class GeoRelationMatchingDatabase():
(idse1 text, idse2 text, value integer)
"""
matching_schema = """CREATE TABLE matching
- (dataset text, g1 integer, g2 integer, c1 integer, c2 integer, c3 integer,c4 integer)
+ (dataset text, g1 integer, g2 integer, c1 integer, c2 integer, c3 integer,c4 integer, c5 REAL )
"""
cursor.execute(inclusion_schema)
cursor.execute(adjacency_schema)
@@ -74,7 +74,7 @@ class GeoRelationMatchingDatabase():
self._db_connection.commit()
cursor.close()
- def add_matching(self, dataset: str, G1: int, G2: int, c1: bool, c2: bool, c3: bool, c4: bool):
+ def add_matching(self, dataset: str, G1: int, G2: int, c1: bool, c2: bool, c3: bool, c4: bool,c5: float):
"""
Add a matching criteria result within the database
Parameters
@@ -96,8 +96,8 @@ class GeoRelationMatchingDatabase():
"""
cursor = self._db_connection.cursor()
- cursor.execute('INSERT INTO matching VALUES(?,?,?,?,?,?,?)',
- (dataset, G1, G2, int(c1), int(c2), int(c3), int(c4)))
+ cursor.execute('INSERT INTO matching VALUES(?,?,?,?,?,?,?,?)',
+ (dataset, G1, G2, int(c1), int(c2), int(c3), int(c4),float(c5)))
self._db_connection.commit()
cursor.close()
@@ -169,7 +169,7 @@ class GeoRelationMatchingDatabase():
result_ = cursor.fetchone()
cursor.close()
if result_:
- return True, tuple(map(int, result_[-4:]))
+ return True, tuple(map(float, result_[-5:]))
return False, False
@@ -185,9 +185,9 @@ if __name__ == "__main__":
assert g.get_inclusion("GD1", "GD2") == (True, True)
assert g.get_inclusion("GD2", "GD1") == (False, False)
- g.add_matching("test", 1, 2, True, True, False, True)
- g.add_matching("test2", 1, 2, True, False, False, True)
- assert g.get_matching(1, 2, "test") == (True, (True, True, False, True))
- assert g.get_matching(1, 2, "test2") != (True, (True, True, False, True))
+ g.add_matching("test", 1, 2, True, True, False, True,0.)
+ g.add_matching("test2", 1, 2, True, False, False, True,0.)
+ assert g.get_matching(1, 2, "test") == (True, (True, True, False, True,0.))
+ assert g.get_matching(1, 2, "test2") != (True, (True, True, False, True,0.))
print("Passed the tests !")
diff --git a/strpython/helpers/match_cache.py b/strpython/helpers/match_cache.py
index 82669a2..7e79c28 100644
--- a/strpython/helpers/match_cache.py
+++ b/strpython/helpers/match_cache.py
@@ -12,6 +12,6 @@ class MatchingCache:
def is_match(self, id_str1: int, id_str2: int):
return self.db_rel_match.get_matching(id_str1, id_str2, self.dataset)
- def add(self, id_str1: int, id_str2: int, c1: int, c2: int, c3: int, c4: int):
+ def add(self, id_str1: int, id_str2: int, c1: int, c2: int, c3: int, c4: int, c5: float):
if not self.is_match(id_str1, id_str2)[0]:
- self.db_rel_match.add_matching(self.dataset, id_str1, id_str2, c1, c2, c3, c4)
+ self.db_rel_match.add_matching(self.dataset, id_str1, id_str2, c1, c2, c3, c4,c5)
diff --git a/strpython/helpers/sim_matrix.py b/strpython/helpers/sim_matrix.py
index 0462de5..1d57994 100644
--- a/strpython/helpers/sim_matrix.py
+++ b/strpython/helpers/sim_matrix.py
@@ -36,6 +36,6 @@ def matrix_to_pandas_dataframe(matrix, selected, sim_measure, type_str, n=5):
top_n = np.argsort(matrix[line])[::-1][1:n + 1]
rank = 1
for val in top_n:
- tab_array.append([line, val, sim, type_, rank, 0, 0, 0, 0])
+ tab_array.append([line, val, sim, type_, rank, 0, 0, 0, 0,300000])
rank += 1
- return pd.DataFrame(tab_array, columns="G1 G2 sim_measure type_str rank c1 c2 c3 c4".split())
+ return pd.DataFrame(tab_array, columns="G1 G2 sim_measure type_str rank c1 c2 c3 c4 c5".split())
--
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