diff --git a/FIDDLE/helpers.py b/FIDDLE/helpers.py
index 22fe41e..101498d 100644
--- a/FIDDLE/helpers.py
+++ b/FIDDLE/helpers.py
@@ -153,10 +153,10 @@ def smart_qcut_dummify(x, bin_edges, use_ordinal_encoding=False):
out = pd.get_dummies(x, prefix=x.name)
else:
if use_ordinal_encoding:
- col_names = ['{}>={}'.format(z.name, bin_edge) for bin_edge in bin_edges[:-1]]
+ col_names = ['{}>{}'.format(z.name, bin_edge) for bin_edge in bin_edges[:-1]]
out = pd.DataFrame(0, z.index, col_names)
for i, bin_edge in enumerate(bin_edges[:-1]):
- out.loc[m, col_names[i]] = (z.loc[m] >= bin_edge).astype(int)
+ out.loc[m, col_names[i]] = (z.loc[m] > bin_edge).astype(int)
out = pd.concat([out, pd.get_dummies(z.where(~m, np.nan), prefix=z.name)], axis=1)
else:
z.loc[m] = pd.cut(z.loc[m].astype(float).to_numpy(), bin_edges, duplicates='drop', include_lowest=True)
@@ -179,7 +179,7 @@ def smart_dummify_impute(x):
def make_float(v):
try:
return float(v)
- except ValueError:
+ except (ValueError, TypeError):
return v
assert False
@@ -187,7 +187,7 @@ def is_numeric(v):
try:
float(v)
return True
- except ValueError:
+ except (ValueError, TypeError):
return False
assert False
diff --git a/README.md b/README.md
index 3063b42..8f6c37e 100644
--- a/README.md
+++ b/README.md
@@ -81,8 +81,8 @@ s = sparse.load_npz('{data_path}/s.npz'.format(data_path=...)).todense()
Example usage:
```bash
python -m FIDDLE.run \
- --data_path='./test/small_test/' \
- --population='./test/small_test/pop.csv' \
+ --data_path='./tests/small_test/' \
+ --population='./tests/small_test/pop.csv' \
--T=24 --dt=5 \
--theta_1=0.001 --theta_2=0.001 --theta_freq=1 \
--stats_functions 'min' 'max' 'mean'
diff --git a/tests/icd_test/Run.ipynb b/tests/icd_test/Run.ipynb
index c83b13c..1f903ba 100644
--- a/tests/icd_test/Run.ipynb
+++ b/tests/icd_test/Run.ipynb
@@ -4,15 +4,7 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "zsh:1: no matches found: output-*/\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!rm -rf output-*/"
]
@@ -111,11 +103,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 19)\n",
"number of missing entries :\t 2816 out of 3800 total\n",
- "Time elapsed: 0.025395 seconds\n",
+ "Time elapsed: 0.012328 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 21)\n",
- "Time elapsed: 0.171098 seconds\n",
+ "Time elapsed: 0.101575 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
@@ -123,13 +115,12 @@
"Original : 21\n",
"Nearly-constant: 0\n",
"Correlated : 0\n",
- "Time elapsed: 0.178303 seconds\n",
+ "Time elapsed: 0.104368 seconds\n",
"\n",
"Output\n",
"S: shape=(200, 21), density=0.234\n",
- "Total time: 0.180898 seconds\n",
- "\n",
- "\u001b[0m"
+ "Total time: 0.106207 seconds\n",
+ "\n"
]
}
],
@@ -732,11 +723,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 129)\n",
"number of missing entries :\t 23337 out of 25800 total\n",
- "Time elapsed: 0.057711 seconds\n",
+ "Time elapsed: 0.034244 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 129)\n",
- "Time elapsed: 0.830818 seconds\n",
+ "Time elapsed: 0.558320 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
@@ -744,13 +735,12 @@
"Original : 129\n",
"Nearly-constant: 0\n",
"Correlated : 2\n",
- "Time elapsed: 0.840801 seconds\n",
+ "Time elapsed: 0.564048 seconds\n",
"\n",
"Output\n",
"S: shape=(200, 127), density=0.097\n",
- "Total time: 0.844234 seconds\n",
- "\n",
- "\u001b[0m"
+ "Total time: 0.567541 seconds\n",
+ "\n"
]
}
],
@@ -1353,11 +1343,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 455)\n",
"number of missing entries :\t 86795 out of 91000 total\n",
- "Time elapsed: 0.112510 seconds\n",
+ "Time elapsed: 0.092419 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 455)\n",
- "Time elapsed: 2.377939 seconds\n",
+ "Time elapsed: 1.690453 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
@@ -1365,13 +1355,12 @@
"Original : 455\n",
"Nearly-constant: 0\n",
"Correlated : 87\n",
- "Time elapsed: 2.428499 seconds\n",
+ "Time elapsed: 1.715216 seconds\n",
"\n",
"Output\n",
"S: shape=(200, 368), density=0.055\n",
- "Total time: 2.435949 seconds\n",
- "\n",
- "\u001b[0m"
+ "Total time: 1.719981 seconds\n",
+ "\n"
]
}
],
@@ -1916,7 +1905,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.6"
+ "version": "3.8.5"
}
},
"nbformat": 4,
diff --git a/tests/large_test/Run.ipynb b/tests/large_test/Run.ipynb
index 3033773..c36c240 100644
--- a/tests/large_test/Run.ipynb
+++ b/tests/large_test/Run.ipynb
@@ -91,11 +91,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 12)\n",
"number of missing entries :\t 4 out of 2400 total\n",
- "Time elapsed: 0.030966 seconds\n",
+ "Time elapsed: 0.018219 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 84)\n",
- "Time elapsed: 0.226954 seconds\n",
+ "Time elapsed: 0.202440 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
@@ -103,11 +103,11 @@
"Original : 84\n",
"Nearly-constant: 0\n",
"Correlated : 7\n",
- "Time elapsed: 0.232384 seconds\n",
+ "Time elapsed: 0.208578 seconds\n",
"\n",
"Output\n",
"S: shape=(200, 77), density=0.145\n",
- "Total time: 0.235823 seconds\n",
+ "Total time: 0.211770 seconds\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n",
@@ -121,8 +121,8 @@
"\n",
"Transforming each example...\n",
"Batches of size 100: 2\n",
- "100%|█████████████████████████████████████████████| 2/2 [00:38<00:00, 19.13s/it]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n",
+ "100%|█████████████████████████████████████████████| 2/2 [00:25<00:00, 12.88s/it]\n",
+ "\n",
"Parallel processing done\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 996 out of 200×4×5=4000 total\n",
@@ -131,40 +131,39 @@
"(non-freq) number of missing entries :\t 1510389 out of 200×4×1953=1562400 total\n",
"\n",
"(N × L × ^D) table :\t (200, 4, 1983)\n",
- "Time elapsed: 39.815167 seconds\n",
+ "Time elapsed: 27.030075 seconds\n",
"Discretizing features...\n",
"\n",
"Processing 1978 non-boolean variable columns...\n",
" Computing bin edges for numeric variables...\n",
- "100%|██████████████████████████████████████| 1978/1978 [00:06<00:00, 328.38it/s]\n",
+ "100%|██████████████████████████████████████| 1978/1978 [00:04<00:00, 399.11it/s]\n",
" Discretizing variables to binary features\n",
- "100%|██████████████████████████████████████| 1978/1978 [00:09<00:00, 201.94it/s]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0mFinished discretizing features\n",
+ "100%|██████████████████████████████████████| 1978/1978 [00:10<00:00, 193.81it/s]\n",
+ "Finished discretizing features\n",
"\n",
"Output\n",
- "X_all: shape=(200, 4, 3557), density=0.025\n",
- "Time elapsed: 57.075922 seconds\n",
+ "X_all: shape=(200, 4, 3582), density=0.025\n",
+ "Time elapsed: 43.360937 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-B) Post-filter time-dependent data\n",
"--------------------------------------------------------------------------------\n",
- "(200, 4, 3557) 0.02504322462749508\n",
- "Original : 3557\n",
+ "(200, 4, 3582) 0.024868439419318815\n",
+ "Original : 3582\n",
"Nearly-constant: 77\n",
- "*** time: 8.839366912841797\n",
- "Correlated : 1137\n",
- "*** time: 16.099601984024048\n",
+ "*** time: 5.742851972579956\n",
+ "Correlated : 1144\n",
+ "*** time: 10.776153087615967\n",
"\n",
"Output\n",
- "X: shape=(200, 4, 2343), density=0.034\n",
- "(200, 4, 2343) 0.03446382842509603\n",
- "Time elapsed: 73.185729 seconds\n",
+ "X: shape=(200, 4, 2361), density=0.034\n",
+ "(200, 4, 2361) 0.034196844557390936\n",
+ "Time elapsed: 54.146272 seconds\n",
"\n",
"Output\n",
- "X: shape=(200, 4, 2343), density=0.034\n",
- "Total time: 73.237736 seconds\n",
- "\n",
- "\u001b[0m"
+ "X: shape=(200, 4, 2361), density=0.034\n",
+ "Total time: 54.197789 seconds\n",
+ "\n"
]
}
],
@@ -1054,7 +1053,7 @@
" \n",
" \n",
"\n",
- "800 rows × 3557 columns
\n",
+ "800 rows × 3582 columns
\n",
""
],
"text/plain": [
@@ -1184,7 +1183,7 @@
" [2.0, 3.0) 0 \n",
" [3.0, 4.0) 0 \n",
"\n",
- "[800 rows x 3557 columns]"
+ "[800 rows x 3582 columns]"
]
},
"metadata": {},
@@ -1220,7 +1219,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -1229,7 +1228,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 2,
"metadata": {},
"outputs": [
{
@@ -1293,23 +1292,23 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 12)\n",
"number of missing entries :\t 4 out of 2400 total\n",
- "Time elapsed: 0.018090 seconds\n",
+ "Time elapsed: 0.016319 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 84)\n",
- "Time elapsed: 0.180124 seconds\n",
+ "Time elapsed: 0.277533 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
"--------------------------------------------------------------------------------\n",
"Original : 84\n",
- "Nearly-constant: 2\n",
- "Correlated : 7\n",
- "Time elapsed: 0.184865 seconds\n",
+ "Nearly-constant: 0\n",
+ "Correlated : 8\n",
+ "Time elapsed: 0.287127 seconds\n",
"\n",
"Output\n",
- "S: shape=(200, 75), density=0.176\n",
- "Total time: 0.188878 seconds\n",
+ "S: shape=(200, 76), density=0.200\n",
+ "Total time: 0.291958 seconds\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n",
@@ -1323,8 +1322,8 @@
"\n",
"Transforming each example...\n",
"Batches of size 100: 2\n",
- "100%|█████████████████████████████████████████████| 2/2 [00:35<00:00, 17.88s/it]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n",
+ "100%|█████████████████████████████████████████████| 2/2 [00:24<00:00, 12.47s/it]\n",
+ "\n",
"Parallel processing done\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 996 out of 200×4×5=4000 total\n",
@@ -1333,40 +1332,39 @@
"(non-freq) number of missing entries :\t 1510389 out of 200×4×1953=1562400 total\n",
"\n",
"(N × L × ^D) table :\t (200, 4, 1983)\n",
- "Time elapsed: 37.294821 seconds\n",
+ "Time elapsed: 26.302975 seconds\n",
"Discretizing features...\n",
"\n",
"Processing 1978 non-boolean variable columns...\n",
" Computing bin edges for numeric variables...\n",
- "100%|██████████████████████████████████████| 1978/1978 [00:05<00:00, 377.85it/s]\n",
+ "100%|██████████████████████████████████████| 1978/1978 [00:04<00:00, 399.19it/s]\n",
" Discretizing variables to binary features\n",
- "100%|██████████████████████████████████████| 1978/1978 [00:14<00:00, 139.24it/s]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0mFinished discretizing features\n",
+ "100%|██████████████████████████████████████| 1978/1978 [00:09<00:00, 208.45it/s]\n",
+ "Finished discretizing features\n",
"\n",
"Output\n",
- "X_all: shape=(200, 4, 3587), density=0.039\n",
- "Time elapsed: 58.029910 seconds\n",
+ "X_all: shape=(200, 4, 3587), density=0.036\n",
+ "Time elapsed: 41.840676 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-B) Post-filter time-dependent data\n",
"--------------------------------------------------------------------------------\n",
- "(200, 4, 3587) 0.03878101477557848\n",
+ "(200, 4, 3587) 0.036313771954279345\n",
"Original : 3587\n",
- "Nearly-constant: 3\n",
- "*** time: 7.768070220947266\n",
- "Correlated : 1194\n",
- "*** time: 14.502072095870972\n",
+ "Nearly-constant: 0\n",
+ "*** time: 5.449969053268433\n",
+ "Correlated : 1173\n",
+ "*** time: 10.53041410446167\n",
"\n",
"Output\n",
- "X: shape=(200, 4, 2390), density=0.048\n",
- "(200, 4, 2390) 0.04819874476987448\n",
- "Time elapsed: 72.538985 seconds\n",
+ "X: shape=(200, 4, 2414), density=0.049\n",
+ "(200, 4, 2414) 0.048544946147473074\n",
+ "Time elapsed: 52.379346 seconds\n",
"\n",
"Output\n",
- "X: shape=(200, 4, 2390), density=0.048\n",
- "Total time: 72.603644 seconds\n",
- "\n",
- "\u001b[0m"
+ "X: shape=(200, 4, 2414), density=0.049\n",
+ "Total time: 52.431078 seconds\n",
+ "\n"
]
}
],
@@ -1384,7 +1382,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -1417,7 +1415,7 @@
" ADMISSION_TYPE_value_ELECTIVE | \n",
" ADMISSION_TYPE_value_EMERGENCY | \n",
" ADMISSION_TYPE_value_URGENT | \n",
- " AGE_value>=19.737885622780315 | \n",
+ " AGE_value>19.737885622780315 | \n",
" ... | \n",
" RELIGION_value_EPISCOPALIAN | \n",
" RELIGION_value_GREEK ORTHODOX | \n",
@@ -1824,19 +1822,19 @@
"201125 0 1 \n",
"201128 0 1 \n",
"\n",
- " ADMISSION_TYPE_value_URGENT AGE_value>=19.737885622780315 ... \\\n",
- "ID ... \n",
- "200001 0 1 ... \n",
- "200010 0 1 ... \n",
- "200016 0 1 ... \n",
- "200033 0 1 ... \n",
- "200034 0 1 ... \n",
- "... ... ... ... \n",
- "201110 0 1 ... \n",
- "201113 0 1 ... \n",
- "201124 0 1 ... \n",
- "201125 0 1 ... \n",
- "201128 0 1 ... \n",
+ " ADMISSION_TYPE_value_URGENT AGE_value>19.737885622780315 ... \\\n",
+ "ID ... \n",
+ "200001 0 1 ... \n",
+ "200010 0 1 ... \n",
+ "200016 0 1 ... \n",
+ "200033 0 1 ... \n",
+ "200034 0 1 ... \n",
+ "... ... ... ... \n",
+ "201110 0 1 ... \n",
+ "201113 0 1 ... \n",
+ "201124 0 1 ... \n",
+ "201125 0 1 ... \n",
+ "201128 0 1 ... \n",
"\n",
" RELIGION_value_EPISCOPALIAN RELIGION_value_GREEK ORTHODOX \\\n",
"ID \n",
@@ -1941,22 +1939,22 @@
" RR_mask | \n",
" SpO2_mask | \n",
" SysBP_mask | \n",
- " 220048_value_1 | \n",
- " 220048: 1st AV (First degree AV Block) _value_1 | \n",
- " 220048: 3rd AV (Complete Heart Block) _value_1 | \n",
- " 220048: A Flut (Atrial Flutter) _value_1 | \n",
- " 220048: AF (Atrial Fibrillation)_value_1 | \n",
+ " 220046_value>10.0 | \n",
+ " 220046_value>120.0 | \n",
+ " 220047_value>29.0 | \n",
+ " 220047_value>50.0 | \n",
+ " 220047_value>55.0 | \n",
" ... | \n",
- " SysBP_mean>=66.0 | \n",
- " SysBP_mean>=103.4 | \n",
- " SysBP_mean>=114.43333333333334 | \n",
- " SysBP_mean>=125.0 | \n",
- " SysBP_mean>=138.0 | \n",
- " SysBP_max>=66.0 | \n",
- " SysBP_max>=105.0 | \n",
- " SysBP_max>=116.0 | \n",
- " SysBP_max>=127.0 | \n",
- " SysBP_max>=141.0 | \n",
+ " SysBP_mean>66.0 | \n",
+ " SysBP_mean>103.4 | \n",
+ " SysBP_mean>114.43333333333334 | \n",
+ " SysBP_mean>125.0 | \n",
+ " SysBP_mean>138.0 | \n",
+ " SysBP_max>66.0 | \n",
+ " SysBP_max>105.0 | \n",
+ " SysBP_max>116.0 | \n",
+ " SysBP_max>127.0 | \n",
+ " SysBP_max>141.0 | \n",
" \n",
" \n",
" | ID | \n",
@@ -1995,9 +1993,9 @@
" 1 | \n",
" 1 | \n",
" 0 | \n",
- " 0 | \n",
- " 0 | \n",
- " 0 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " 1 | \n",
" ... | \n",
" 1 | \n",
" 1 | \n",
@@ -2017,7 +2015,7 @@
" 1 | \n",
" 1 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
@@ -2041,7 +2039,7 @@
" 1 | \n",
" 1 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
@@ -2054,7 +2052,7 @@
" 0 | \n",
" 1 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
"
\n",
@@ -2065,7 +2063,7 @@
" 1 | \n",
" 1 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
@@ -2090,9 +2088,9 @@
" 0 | \n",
" 0 | \n",
" 0 | \n",
+ " 1 | \n",
" 0 | \n",
- " 0 | \n",
- " 0 | \n",
+ " 1 | \n",
" 0 | \n",
" 0 | \n",
" ... | \n",
@@ -2141,10 +2139,10 @@
" 1 | \n",
" 1 | \n",
" 1 | \n",
- " 0 | \n",
- " 0 | \n",
- " 0 | \n",
- " 0 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " 1 | \n",
+ " 1 | \n",
" ... | \n",
" 1 | \n",
" 1 | \n",
@@ -2191,7 +2189,7 @@
" 1 | \n",
" 1 | \n",
" 0 | \n",
- " 0 | \n",
+ " 1 | \n",
" 0 | \n",
" 0 | \n",
" ... | \n",
@@ -2213,7 +2211,7 @@
" 1 | \n",
" 0 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
@@ -2237,7 +2235,7 @@
" 1 | \n",
" 0 | \n",
" 1 | \n",
- " 1 | \n",
+ " 0 | \n",
" 0 | \n",
" 0 | \n",
" 0 | \n",
@@ -2274,131 +2272,89 @@
" [2.0, 3.0) 1 1 1 0 1 \n",
" [3.0, 4.0) 1 1 1 0 1 \n",
"\n",
- " 220048_value_1 \\\n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 1 \n",
- " [1.0, 2.0) 1 \n",
- " [2.0, 3.0) 1 \n",
- " [3.0, 4.0) 1 \n",
- "200010 [0.0, 1.0) 0 \n",
- "... ... \n",
- "201125 [3.0, 4.0) 1 \n",
- "201128 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 1 \n",
- " [2.0, 3.0) 1 \n",
- " [3.0, 4.0) 1 \n",
- "\n",
- " 220048: 1st AV (First degree AV Block) _value_1 \\\n",
+ " 220046_value>10.0 220046_value>120.0 220047_value>29.0 \\\n",
+ "ID t_range \n",
+ "200001 [0.0, 1.0) 1 0 1 \n",
+ " [1.0, 2.0) 0 0 0 \n",
+ " [2.0, 3.0) 0 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
+ "200010 [0.0, 1.0) 1 0 1 \n",
+ "... ... ... ... \n",
+ "201125 [3.0, 4.0) 1 1 1 \n",
+ "201128 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 1 0 1 \n",
+ " [2.0, 3.0) 0 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
+ "\n",
+ " 220047_value>50.0 220047_value>55.0 ... SysBP_mean>66.0 \\\n",
+ "ID t_range ... \n",
+ "200001 [0.0, 1.0) 1 1 ... 1 \n",
+ " [1.0, 2.0) 0 0 ... 1 \n",
+ " [2.0, 3.0) 0 0 ... 1 \n",
+ " [3.0, 4.0) 0 0 ... 1 \n",
+ "200010 [0.0, 1.0) 0 0 ... 0 \n",
+ "... ... ... ... ... \n",
+ "201125 [3.0, 4.0) 1 1 ... 1 \n",
+ "201128 [0.0, 1.0) 0 0 ... 0 \n",
+ " [1.0, 2.0) 0 0 ... 1 \n",
+ " [2.0, 3.0) 0 0 ... 1 \n",
+ " [3.0, 4.0) 0 0 ... 1 \n",
+ "\n",
+ " SysBP_mean>103.4 SysBP_mean>114.43333333333334 \\\n",
"ID t_range \n",
- "200001 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "200010 [0.0, 1.0) 0 \n",
- "... ... \n",
- "201125 [3.0, 4.0) 0 \n",
- "201128 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "\n",
- " 220048: 3rd AV (Complete Heart Block) _value_1 \\\n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "200010 [0.0, 1.0) 0 \n",
- "... ... \n",
- "201125 [3.0, 4.0) 0 \n",
- "201128 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "\n",
- " 220048: A Flut (Atrial Flutter) _value_1 \\\n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "200010 [0.0, 1.0) 0 \n",
- "... ... \n",
- "201125 [3.0, 4.0) 0 \n",
- "201128 [0.0, 1.0) 0 \n",
- " [1.0, 2.0) 0 \n",
- " [2.0, 3.0) 0 \n",
- " [3.0, 4.0) 0 \n",
- "\n",
- " 220048: AF (Atrial Fibrillation)_value_1 ... \\\n",
- "ID t_range ... \n",
- "200001 [0.0, 1.0) 0 ... \n",
- " [1.0, 2.0) 0 ... \n",
- " [2.0, 3.0) 0 ... \n",
- " [3.0, 4.0) 0 ... \n",
- "200010 [0.0, 1.0) 0 ... \n",
- "... ... ... \n",
- "201125 [3.0, 4.0) 0 ... \n",
- "201128 [0.0, 1.0) 0 ... \n",
- " [1.0, 2.0) 0 ... \n",
- " [2.0, 3.0) 0 ... \n",
- " [3.0, 4.0) 0 ... \n",
- "\n",
- " SysBP_mean>=66.0 SysBP_mean>=103.4 \\\n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 1 1 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 0 \n",
- "200010 [0.0, 1.0) 0 0 \n",
- "... ... ... \n",
- "201125 [3.0, 4.0) 1 1 \n",
- "201128 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 1 \n",
- "\n",
- " SysBP_mean>=114.43333333333334 SysBP_mean>=125.0 \\\n",
+ "200001 [0.0, 1.0) 1 0 \n",
+ " [1.0, 2.0) 1 0 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 0 0 \n",
+ "200010 [0.0, 1.0) 0 0 \n",
+ "... ... ... \n",
+ "201125 [3.0, 4.0) 1 1 \n",
+ "201128 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 1 1 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 1 1 \n",
+ "\n",
+ " SysBP_mean>125.0 SysBP_mean>138.0 SysBP_max>66.0 \\\n",
+ "ID t_range \n",
+ "200001 [0.0, 1.0) 0 0 1 \n",
+ " [1.0, 2.0) 0 0 1 \n",
+ " [2.0, 3.0) 0 0 1 \n",
+ " [3.0, 4.0) 0 0 1 \n",
+ "200010 [0.0, 1.0) 0 0 0 \n",
+ "... ... ... ... \n",
+ "201125 [3.0, 4.0) 0 0 1 \n",
+ "201128 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 1 0 1 \n",
+ " [2.0, 3.0) 0 0 1 \n",
+ " [3.0, 4.0) 0 0 1 \n",
+ "\n",
+ " SysBP_max>105.0 SysBP_max>116.0 SysBP_max>127.0 \\\n",
"ID t_range \n",
- "200001 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 0 0 \n",
- " [2.0, 3.0) 1 0 \n",
- " [3.0, 4.0) 0 0 \n",
- "200010 [0.0, 1.0) 0 0 \n",
- "... ... ... \n",
- "201125 [3.0, 4.0) 1 0 \n",
- "201128 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 0 \n",
- " [3.0, 4.0) 1 0 \n",
- "\n",
- " SysBP_mean>=138.0 SysBP_max>=66.0 SysBP_max>=105.0 \\\n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 0 1 1 \n",
- " [1.0, 2.0) 0 1 1 \n",
- " [2.0, 3.0) 0 1 1 \n",
- " [3.0, 4.0) 0 1 0 \n",
- "200010 [0.0, 1.0) 0 0 0 \n",
- "... ... ... ... \n",
- "201125 [3.0, 4.0) 0 1 1 \n",
- "201128 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 1 1 \n",
- " [2.0, 3.0) 0 1 1 \n",
- " [3.0, 4.0) 0 1 1 \n",
- "\n",
- " SysBP_max>=116.0 SysBP_max>=127.0 SysBP_max>=141.0 \n",
- "ID t_range \n",
- "200001 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 0 0 \n",
- " [2.0, 3.0) 1 0 0 \n",
- " [3.0, 4.0) 0 0 0 \n",
- "200010 [0.0, 1.0) 0 0 0 \n",
- "... ... ... ... \n",
- "201125 [3.0, 4.0) 1 0 0 \n",
- "201128 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 1 1 0 \n",
- " [2.0, 3.0) 1 0 0 \n",
- " [3.0, 4.0) 1 0 0 \n",
+ "200001 [0.0, 1.0) 1 0 0 \n",
+ " [1.0, 2.0) 1 0 0 \n",
+ " [2.0, 3.0) 1 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
+ "200010 [0.0, 1.0) 0 0 0 \n",
+ "... ... ... ... \n",
+ "201125 [3.0, 4.0) 1 1 0 \n",
+ "201128 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 1 1 1 \n",
+ " [2.0, 3.0) 1 1 0 \n",
+ " [3.0, 4.0) 1 1 0 \n",
+ "\n",
+ " SysBP_max>141.0 \n",
+ "ID t_range \n",
+ "200001 [0.0, 1.0) 0 \n",
+ " [1.0, 2.0) 0 \n",
+ " [2.0, 3.0) 0 \n",
+ " [3.0, 4.0) 0 \n",
+ "200010 [0.0, 1.0) 0 \n",
+ "... ... \n",
+ "201125 [3.0, 4.0) 0 \n",
+ "201128 [0.0, 1.0) 0 \n",
+ " [1.0, 2.0) 0 \n",
+ " [2.0, 3.0) 0 \n",
+ " [3.0, 4.0) 0 \n",
"\n",
"[800 rows x 3587 columns]"
]
@@ -2507,11 +2463,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (200, 12)\n",
"number of missing entries :\t 4 out of 2400 total\n",
- "Time elapsed: 0.018502 seconds\n",
+ "Time elapsed: 0.011708 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (200, 76)\n",
- "Time elapsed: 0.116800 seconds\n",
+ "Time elapsed: 0.123038 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-A) Post-filter time-invariant data\n",
@@ -2519,11 +2475,11 @@
"Original : 76\n",
"Nearly-constant: 0\n",
"Correlated : 7\n",
- "Time elapsed: 0.121063 seconds\n",
+ "Time elapsed: 0.126716 seconds\n",
"\n",
"Output\n",
"S: shape=(200, 69), density=0.162\n",
- "Total time: 0.125685 seconds\n",
+ "Total time: 0.129411 seconds\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n",
@@ -2537,8 +2493,8 @@
"\n",
"Transforming each example...\n",
"Batches of size 100: 2\n",
- "100%|█████████████████████████████████████████████| 2/2 [00:30<00:00, 15.46s/it]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0m\n",
+ "100%|█████████████████████████████████████████████| 2/2 [00:23<00:00, 11.65s/it]\n",
+ "\n",
"Parallel processing done\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 996 out of 200×4×5=4000 total\n",
@@ -2547,16 +2503,16 @@
"(non-freq) number of missing entries :\t 1510389 out of 200×4×1953=1562400 total\n",
"\n",
"(N × L × ^D) table :\t (200, 4, 1983)\n",
- "Time elapsed: 32.386383 seconds\n",
+ "Time elapsed: 24.511847 seconds\n",
"Discretizing features...\n",
"\n",
"Discretizing categorical features...\n",
- "100%|██████████████████████████████████████| 1990/1990 [00:10<00:00, 190.17it/s]\n",
- "\u001b[0m\u001b[0m\u001b[0m\u001b[0mFinished discretizing features\n",
+ "100%|██████████████████████████████████████| 1990/1990 [00:07<00:00, 266.00it/s]\n",
+ "Finished discretizing features\n",
"\n",
"Output\n",
"X_all: shape=(200, 4, 2588), density=0.582\n",
- "Time elapsed: 46.796057 seconds\n",
+ "Time elapsed: 34.279819 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"3-B) Post-filter time-dependent data\n",
@@ -2564,7 +2520,7 @@
"(200, 4, 2588) 0.5818387751159196\n",
"Original : 2588\n",
"Nearly-constant: 1064\n",
- "*** time: 10.0768461227417\n",
+ "*** time: 5.1737799644470215\n",
"/Users/shengputang/Developer/FIDDLE/FIDDLE/helpers.py:426: RuntimeWarning: invalid value encountered in sqrt\n",
" coeffs = C / np.sqrt(np.outer(d, d))\n",
"/Users/shengputang/Developer/FIDDLE/FIDDLE/helpers.py:426: RuntimeWarning: divide by zero encountered in true_divide\n",
@@ -2574,18 +2530,17 @@
"/Users/shengputang/Developer/FIDDLE/FIDDLE/helpers.py:376: RuntimeWarning: invalid value encountered in multiply\n",
" self.corr_matrix *= np.tri(*self.corr_matrix.shape)\n",
"Correlated : 310\n",
- "*** time: 16.394930124282837\n",
+ "*** time: 8.826726913452148\n",
"\n",
"Output\n",
"X: shape=(200, 4, 1214), density=0.366\n",
"(200, 4, 1214) 0.366085255354201\n",
- "Time elapsed: 63.195710 seconds\n",
+ "Time elapsed: 43.112199 seconds\n",
"\n",
"Output\n",
"X: shape=(200, 4, 1214), density=0.366\n",
- "Total time: 63.452329 seconds\n",
- "\n",
- "\u001b[0m"
+ "Total time: 43.318430 seconds\n",
+ "\n"
]
}
],
@@ -3656,7 +3611,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.6"
+ "version": "3.8.5"
}
},
"nbformat": 4,
diff --git a/tests/small_test/Run-docker.ipynb b/tests/small_test/Run-docker.ipynb
index a18976b..c56e7c2 100644
--- a/tests/small_test/Run-docker.ipynb
+++ b/tests/small_test/Run-docker.ipynb
@@ -77,11 +77,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (4, 3)\n",
"number of missing entries :\t 3 out of 12 total\n",
- "Time elapsed: 0.044580 seconds\n",
+ "Time elapsed: 0.037138 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (4, 6)\n",
- "Time elapsed: 0.274032 seconds\n",
+ "Time elapsed: 0.098682 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"2-B) Transform time-dependent data\n",
@@ -93,7 +93,7 @@
"k = 3 ['min', 'max', 'mean']\n",
"\n",
"Transforming each example...\n",
- "100%|█████████████████████████████████████████████| 4/4 [00:01<00:00, 3.60it/s]\n",
+ "100%|█████████████████████████████████████████████| 4/4 [00:00<00:00, 7.10it/s]\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 5 out of 4×4×1=16 total\n",
"(freq) number of imputed entries :\t 4\n",
@@ -101,16 +101,16 @@
"(non-freq) number of missing entries :\t 41 out of 4×4×3=48 total\n",
"\n",
"(N × L × ^D) table :\t (4, 4, 9)\n",
- "Time elapsed: 1.221479 seconds\n",
+ "Time elapsed: 0.652093 seconds\n",
"Discretizing features...\n",
"\n",
"Discretizing categorical features...\n",
- "100%|████████████████████████████████████████████| 9/9 [00:00<00:00, 132.10it/s]\n",
+ "100%|████████████████████████████████████████████| 9/9 [00:00<00:00, 189.23it/s]\n",
"Finished discretizing features\n",
"\n",
"Output\n",
"X_all: shape=(4, 4, 12), density=0.599\n",
- "Time elapsed: 1.397339 seconds\n"
+ "Time elapsed: 0.780475 seconds\n"
]
}
],
@@ -705,11 +705,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (4, 3)\n",
"number of missing entries :\t 3 out of 12 total\n",
- "Time elapsed: 0.057177 seconds\n",
+ "Time elapsed: 0.037977 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (4, 10)\n",
- "Time elapsed: 0.212313 seconds\n",
+ "Time elapsed: 0.101355 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"2-B) Transform time-dependent data\n",
@@ -721,7 +721,7 @@
"k = 3 ['min', 'max', 'mean']\n",
"\n",
"Transforming each example...\n",
- "100%|█████████████████████████████████████████████| 4/4 [00:01<00:00, 2.82it/s]\n",
+ "100%|█████████████████████████████████████████████| 4/4 [00:00<00:00, 6.19it/s]\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 5 out of 4×4×1=16 total\n",
"(freq) number of imputed entries :\t 4\n",
@@ -729,19 +729,19 @@
"(non-freq) number of missing entries :\t 41 out of 4×4×3=48 total\n",
"\n",
"(N × L × ^D) table :\t (4, 4, 9)\n",
- "Time elapsed: 1.567708 seconds\n",
+ "Time elapsed: 0.732639 seconds\n",
"Discretizing features...\n",
"\n",
"Processing 8 non-boolean variable columns...\n",
" Computing bin edges for numeric variables...\n",
- "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 72.63it/s]\n",
+ "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 323.78it/s]\n",
" Discretizing variables to binary features\n",
- "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 28.40it/s]\n",
+ "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 110.27it/s]\n",
"Finished discretizing features\n",
"\n",
"Output\n",
"X_all: shape=(4, 4, 29), density=0.203\n",
- "Time elapsed: 2.102018 seconds\n"
+ "Time elapsed: 0.880507 seconds\n"
]
}
],
@@ -1627,11 +1627,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (4, 3)\n",
"number of missing entries :\t 3 out of 12 total\n",
- "Time elapsed: 0.047925 seconds\n",
+ "Time elapsed: 0.023125 seconds\n",
"\n",
"Output\n",
"S_all, binary features :\t (4, 10)\n",
- "Time elapsed: 0.147781 seconds\n",
+ "Time elapsed: 0.106754 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"2-B) Transform time-dependent data\n",
@@ -1643,7 +1643,7 @@
"k = 3 ['min', 'max', 'mean']\n",
"\n",
"Transforming each example...\n",
- "100%|█████████████████████████████████████████████| 4/4 [00:01<00:00, 3.53it/s]\n",
+ "100%|█████████████████████████████████████████████| 4/4 [00:00<00:00, 4.61it/s]\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 5 out of 4×4×1=16 total\n",
"(freq) number of imputed entries :\t 4\n",
@@ -1651,19 +1651,19 @@
"(non-freq) number of missing entries :\t 41 out of 4×4×3=48 total\n",
"\n",
"(N × L × ^D) table :\t (4, 4, 9)\n",
- "Time elapsed: 1.239074 seconds\n",
+ "Time elapsed: 0.947634 seconds\n",
"Discretizing features...\n",
"\n",
"Processing 8 non-boolean variable columns...\n",
" Computing bin edges for numeric variables...\n",
- "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 165.76it/s]\n",
+ "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 190.83it/s]\n",
" Discretizing variables to binary features\n",
- "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 24.97it/s]\n",
+ "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 46.71it/s]\n",
"Finished discretizing features\n",
"\n",
"Output\n",
"X_all: shape=(4, 4, 29), density=0.474\n",
- "Time elapsed: 1.718451 seconds\n"
+ "Time elapsed: 1.240619 seconds\n"
]
}
],
@@ -2465,7 +2465,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.6"
+ "version": "3.8.5"
}
},
"nbformat": 4,
diff --git a/tests/small_test/Run.ipynb b/tests/small_test/Run.ipynb
index b9a073f..ac2f626 100644
--- a/tests/small_test/Run.ipynb
+++ b/tests/small_test/Run.ipynb
@@ -2484,7 +2484,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -2493,7 +2493,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 2,
"metadata": {},
"outputs": [
{
@@ -2545,11 +2545,11 @@
"--------------------------------------------------------------------------------\n",
"(N × ^d) table :\t (4, 3)\n",
"number of missing entries :\t 3 out of 12 total\n",
- "Time elapsed: 0.018871 seconds\n",
+ "Time elapsed: 0.015474 seconds\n",
"\n",
"Output\n",
- "s_all, binary features :\t (4, 10)\n",
- "Time elapsed: 0.061661 seconds\n",
+ "S_all, binary features :\t (4, 10)\n",
+ "Time elapsed: 0.057708 seconds\n",
"\n",
"--------------------------------------------------------------------------------\n",
"2-B) Transform time-dependent data\n",
@@ -2561,7 +2561,7 @@
"k = 3 ['min', 'max', 'mean']\n",
"\n",
"Transforming each example...\n",
- "100%|█████████████████████████████████████████████| 4/4 [00:00<00:00, 5.89it/s]\n",
+ "100%|█████████████████████████████████████████████| 4/4 [00:00<00:00, 8.43it/s]\n",
"DONE: Transforming each example...\n",
"(freq) number of missing entries :\t 5 out of 4×4×1=16 total\n",
"(freq) number of imputed entries :\t 4\n",
@@ -2569,20 +2569,19 @@
"(non-freq) number of missing entries :\t 41 out of 4×4×3=48 total\n",
"\n",
"(N × L × ^D) table :\t (4, 4, 9)\n",
- "Time elapsed: 0.735244 seconds\n",
+ "Time elapsed: 0.529465 seconds\n",
"Discretizing features...\n",
"\n",
"Processing 8 non-boolean variable columns...\n",
" Computing bin edges for numeric variables...\n",
- "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 313.93it/s]\n",
+ "100%|████████████████████████████████████████████| 8/8 [00:00<00:00, 501.69it/s]\n",
" Discretizing variables to binary features\n",
- "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 38.42it/s]\n",
+ "100%|█████████████████████████████████████████████| 8/8 [00:00<00:00, 82.33it/s]\n",
"Finished discretizing features\n",
"\n",
"Output\n",
"X_all: shape=(4, 4, 29), density=0.420\n",
- "Time elapsed: 0.989317 seconds\n",
- "\u001b[0m"
+ "Time elapsed: 0.665394 seconds\n"
]
}
],
@@ -2601,7 +2600,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -2625,11 +2624,11 @@
" \n",
" \n",
" | \n",
- " AGE_value>=33.0 | \n",
- " AGE_value>=35.8 | \n",
- " AGE_value>=38.6 | \n",
- " AGE_value>=42.0 | \n",
- " AGE_value>=46.0 | \n",
+ " AGE_value>33.0 | \n",
+ " AGE_value>35.8 | \n",
+ " AGE_value>38.6 | \n",
+ " AGE_value>42.0 | \n",
+ " AGE_value>46.0 | \n",
" ROOM_value__101 | \n",
" ROOM_value__102 | \n",
" ROOM_value__103 | \n",
@@ -2708,19 +2707,19 @@
""
],
"text/plain": [
- " AGE_value>=33.0 AGE_value>=35.8 AGE_value>=38.6 AGE_value>=42.0 \\\n",
- "ID \n",
- "1 1 1 1 1 \n",
- "2 0 0 0 0 \n",
- "3 1 1 1 0 \n",
- "4 0 0 0 0 \n",
+ " AGE_value>33.0 AGE_value>35.8 AGE_value>38.6 AGE_value>42.0 \\\n",
+ "ID \n",
+ "1 1 1 1 1 \n",
+ "2 0 0 0 0 \n",
+ "3 1 1 1 0 \n",
+ "4 0 0 0 0 \n",
"\n",
- " AGE_value>=46.0 ROOM_value__101 ROOM_value__102 ROOM_value__103 \\\n",
- "ID \n",
- "1 1 1 0 0 \n",
- "2 0 0 1 0 \n",
- "3 0 0 0 1 \n",
- "4 0 0 0 0 \n",
+ " AGE_value>46.0 ROOM_value__101 ROOM_value__102 ROOM_value__103 \\\n",
+ "ID \n",
+ "1 1 1 0 0 \n",
+ "2 0 0 1 0 \n",
+ "3 0 0 0 1 \n",
+ "4 0 0 0 0 \n",
"\n",
" SEX_value_F SEX_value_M \n",
"ID \n",
@@ -2762,20 +2761,20 @@
" DRUG_A_ROUTE_value_Oral | \n",
" LAB_X_value_5 | \n",
" LAB_X_value_<1 | \n",
- " HR_delta_time>=0.0 | \n",
- " HR_delta_time>=1.0 | \n",
- " HR_value>=61.0 | \n",
+ " HR_delta_time>0.0 | \n",
+ " HR_delta_time>1.0 | \n",
+ " HR_value>61.0 | \n",
" ... | \n",
- " HR_max>=61.0 | \n",
- " HR_max>=69.2 | \n",
- " HR_max>=73.6 | \n",
- " HR_max>=76.2 | \n",
- " HR_max>=82.00000000000001 | \n",
- " HR_mean>=60.333333333333336 | \n",
- " HR_mean>=68.80000000000001 | \n",
- " HR_mean>=73.6 | \n",
- " HR_mean>=75.2 | \n",
- " HR_mean>=82.00000000000001 | \n",
+ " HR_max>61.0 | \n",
+ " HR_max>69.2 | \n",
+ " HR_max>73.6 | \n",
+ " HR_max>76.2 | \n",
+ " HR_max>82.00000000000001 | \n",
+ " HR_mean>60.333333333333336 | \n",
+ " HR_mean>68.80000000000001 | \n",
+ " HR_mean>73.6 | \n",
+ " HR_mean>75.2 | \n",
+ " HR_mean>82.00000000000001 | \n",
"
\n",
" \n",
" | ID | \n",
@@ -3236,100 +3235,100 @@
" [2.0, 3.0) 0 0 0 \n",
" [3.0, 4.0) 0 0 0 \n",
"\n",
- " LAB_X_value_<1 HR_delta_time>=0.0 HR_delta_time>=1.0 \\\n",
- "ID t_range \n",
- "1 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 0 0 \n",
- " [2.0, 3.0) 1 0 0 \n",
- " [3.0, 4.0) 0 0 0 \n",
- "2 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 1 0 \n",
- " [2.0, 3.0) 0 0 0 \n",
- " [3.0, 4.0) 0 0 0 \n",
- "3 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 0 0 \n",
- " [2.0, 3.0) 0 1 0 \n",
- " [3.0, 4.0) 0 1 1 \n",
- "4 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 1 0 \n",
- " [2.0, 3.0) 0 0 0 \n",
- " [3.0, 4.0) 0 0 0 \n",
+ " LAB_X_value_<1 HR_delta_time>0.0 HR_delta_time>1.0 \\\n",
+ "ID t_range \n",
+ "1 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 0 0 \n",
+ " [2.0, 3.0) 1 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
+ "2 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 1 0 \n",
+ " [2.0, 3.0) 0 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
+ "3 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 0 0 \n",
+ " [2.0, 3.0) 0 1 0 \n",
+ " [3.0, 4.0) 0 1 1 \n",
+ "4 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 1 0 \n",
+ " [2.0, 3.0) 0 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
"\n",
- " HR_value>=61.0 ... HR_max>=61.0 HR_max>=69.2 HR_max>=73.6 \\\n",
- "ID t_range ... \n",
- "1 [0.0, 1.0) 1 ... 1 1 0 \n",
- " [1.0, 2.0) 1 ... 1 1 0 \n",
- " [2.0, 3.0) 1 ... 1 1 1 \n",
- " [3.0, 4.0) 1 ... 1 1 1 \n",
- "2 [0.0, 1.0) 0 ... 0 0 0 \n",
- " [1.0, 2.0) 0 ... 0 0 0 \n",
- " [2.0, 3.0) 1 ... 1 1 1 \n",
- " [3.0, 4.0) 1 ... 1 1 1 \n",
- "3 [0.0, 1.0) 0 ... 0 0 0 \n",
- " [1.0, 2.0) 1 ... 1 1 1 \n",
- " [2.0, 3.0) 1 ... 1 1 1 \n",
- " [3.0, 4.0) 1 ... 1 1 1 \n",
- "4 [0.0, 1.0) 1 ... 1 1 1 \n",
- " [1.0, 2.0) 1 ... 1 1 1 \n",
- " [2.0, 3.0) 1 ... 1 0 0 \n",
- " [3.0, 4.0) 1 ... 1 1 0 \n",
+ " HR_value>61.0 ... HR_max>61.0 HR_max>69.2 HR_max>73.6 \\\n",
+ "ID t_range ... \n",
+ "1 [0.0, 1.0) 1 ... 1 1 0 \n",
+ " [1.0, 2.0) 1 ... 1 1 0 \n",
+ " [2.0, 3.0) 1 ... 1 1 1 \n",
+ " [3.0, 4.0) 1 ... 1 1 1 \n",
+ "2 [0.0, 1.0) 0 ... 0 0 0 \n",
+ " [1.0, 2.0) 0 ... 0 0 0 \n",
+ " [2.0, 3.0) 1 ... 1 1 1 \n",
+ " [3.0, 4.0) 1 ... 1 1 1 \n",
+ "3 [0.0, 1.0) 0 ... 0 0 0 \n",
+ " [1.0, 2.0) 1 ... 1 1 1 \n",
+ " [2.0, 3.0) 1 ... 1 1 1 \n",
+ " [3.0, 4.0) 1 ... 1 1 1 \n",
+ "4 [0.0, 1.0) 1 ... 1 1 1 \n",
+ " [1.0, 2.0) 1 ... 1 1 1 \n",
+ " [2.0, 3.0) 1 ... 1 0 0 \n",
+ " [3.0, 4.0) 1 ... 1 1 0 \n",
"\n",
- " HR_max>=76.2 HR_max>=82.00000000000001 \\\n",
- "ID t_range \n",
- "1 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 0 0 \n",
- " [2.0, 3.0) 0 0 \n",
- " [3.0, 4.0) 0 0 \n",
- "2 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 0 0 \n",
- " [2.0, 3.0) 1 0 \n",
- " [3.0, 4.0) 0 0 \n",
- "3 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 1 \n",
- "4 [0.0, 1.0) 1 0 \n",
- " [1.0, 2.0) 1 0 \n",
- " [2.0, 3.0) 0 0 \n",
- " [3.0, 4.0) 0 0 \n",
+ " HR_max>76.2 HR_max>82.00000000000001 \\\n",
+ "ID t_range \n",
+ "1 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 0 0 \n",
+ " [2.0, 3.0) 0 0 \n",
+ " [3.0, 4.0) 0 0 \n",
+ "2 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 0 0 \n",
+ " [2.0, 3.0) 1 0 \n",
+ " [3.0, 4.0) 0 0 \n",
+ "3 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 1 1 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 1 1 \n",
+ "4 [0.0, 1.0) 1 0 \n",
+ " [1.0, 2.0) 1 0 \n",
+ " [2.0, 3.0) 0 0 \n",
+ " [3.0, 4.0) 0 0 \n",
"\n",
- " HR_mean>=60.333333333333336 HR_mean>=68.80000000000001 \\\n",
- "ID t_range \n",
- "1 [0.0, 1.0) 1 1 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 1 \n",
- "2 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 1 0 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 1 \n",
- "3 [0.0, 1.0) 0 0 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 1 \n",
- " [3.0, 4.0) 1 1 \n",
- "4 [0.0, 1.0) 1 1 \n",
- " [1.0, 2.0) 1 1 \n",
- " [2.0, 3.0) 1 0 \n",
- " [3.0, 4.0) 1 1 \n",
+ " HR_mean>60.333333333333336 HR_mean>68.80000000000001 \\\n",
+ "ID t_range \n",
+ "1 [0.0, 1.0) 1 1 \n",
+ " [1.0, 2.0) 1 1 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 1 1 \n",
+ "2 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 1 0 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 1 1 \n",
+ "3 [0.0, 1.0) 0 0 \n",
+ " [1.0, 2.0) 1 1 \n",
+ " [2.0, 3.0) 1 1 \n",
+ " [3.0, 4.0) 1 1 \n",
+ "4 [0.0, 1.0) 1 1 \n",
+ " [1.0, 2.0) 1 1 \n",
+ " [2.0, 3.0) 1 0 \n",
+ " [3.0, 4.0) 1 1 \n",
"\n",
- " HR_mean>=73.6 HR_mean>=75.2 HR_mean>=82.00000000000001 \n",
- "ID t_range \n",
- "1 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 0 0 \n",
- " [2.0, 3.0) 1 0 0 \n",
- " [3.0, 4.0) 1 0 0 \n",
- "2 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 0 0 0 \n",
- " [2.0, 3.0) 1 1 0 \n",
- " [3.0, 4.0) 1 0 0 \n",
- "3 [0.0, 1.0) 0 0 0 \n",
- " [1.0, 2.0) 1 1 1 \n",
- " [2.0, 3.0) 1 1 1 \n",
- " [3.0, 4.0) 1 1 1 \n",
- "4 [0.0, 1.0) 1 1 0 \n",
- " [1.0, 2.0) 1 1 0 \n",
- " [2.0, 3.0) 0 0 0 \n",
- " [3.0, 4.0) 0 0 0 \n",
+ " HR_mean>73.6 HR_mean>75.2 HR_mean>82.00000000000001 \n",
+ "ID t_range \n",
+ "1 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 0 0 \n",
+ " [2.0, 3.0) 1 0 0 \n",
+ " [3.0, 4.0) 1 0 0 \n",
+ "2 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 0 0 0 \n",
+ " [2.0, 3.0) 1 1 0 \n",
+ " [3.0, 4.0) 1 0 0 \n",
+ "3 [0.0, 1.0) 0 0 0 \n",
+ " [1.0, 2.0) 1 1 1 \n",
+ " [2.0, 3.0) 1 1 1 \n",
+ " [3.0, 4.0) 1 1 1 \n",
+ "4 [0.0, 1.0) 1 1 0 \n",
+ " [1.0, 2.0) 1 1 0 \n",
+ " [2.0, 3.0) 0 0 0 \n",
+ " [3.0, 4.0) 0 0 0 \n",
"\n",
"[16 rows x 29 columns]"
]
@@ -3382,7 +3381,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.6"
+ "version": "3.8.5"
}
},
"nbformat": 4,