Skip to content

Commit ceb93f6

Browse files
bdholt1bdholt1
committed
graphs generated in one step
1 parent 67e8a3e commit ceb93f6

9 files changed

+207
-104
lines changed

Diff for: ‎benchmarks/bench_elasticnet.py

+10-10
Original file line numberDiff line numberDiff line change
@@ -69,17 +69,17 @@ def bench_pymvpa(X, y, T, valid):
6969

7070
print 'Loading data ...'
7171
data = misc.load_data(dataset)
72+
7273
print 'Done, %s samples with %s features loaded into ' \
73-
'memory' % data[0].shape
74+
'memory\n' % data[0].shape
75+
76+
score, res = misc.bench(bench_skl, data)
77+
misc.print_result("elasticnet", dataset, "scikits.learn", score, res)
7478

75-
score, res_skl = misc.bench(bench_skl, data)
76-
print 'scikits.learn: mean %s, std %s' % (res_skl.mean(), res_skl.std())
77-
print 'MSE ', score
79+
score, res = misc.bench(bench_mlpy, data)
80+
misc.print_result("elasticnet", dataset, "MLPy", score, res)
7881

79-
score, res_mlpy = misc.bench(bench_mlpy, data)
80-
print 'MLPy: mean %s, std %s' % (res_mlpy.mean(), res_mlpy.std())
81-
print 'MSE ', score
82+
score, res = misc.bench(bench_pymvpa, data)
83+
misc.print_result("elasticnet", dataset, "PyMVPA", score, res)
8284

83-
score, res_pymvpa = misc.bench(bench_pymvpa, data)
84-
print 'PyMVPA: mean %s, std %s' % (res_pymvpa.mean(), res_pymvpa.std())
85-
print 'MSE ', score
85+
misc.save_results()

Diff for: ‎benchmarks/bench_kmeans.py

+21-31
Original file line numberDiff line numberDiff line change
@@ -119,34 +119,24 @@ def bench_milk(X, y, T, valid):
119119
data = misc.load_data(dataset)
120120

121121
print 'Done, %s samples with %s features loaded into ' \
122-
'memory' % data[0].shape
123-
124-
score, res_shogun = misc.bench(bench_shogun, data)
125-
print 'Shogun: mean %.2f, std %.2f' % (
126-
np.mean(res_shogun), np.std(res_shogun))
127-
print 'Score: %2f\n' % score
128-
129-
score, res_mdp = misc.bench(bench_mdp, data)
130-
print 'MDP: mean %.2f, std %.2f' % (
131-
np.mean(res_mdp), np.std(res_mdp))
132-
print 'Score: %2f\n' % score
133-
134-
score, res_skl = misc.bench(bench_skl, data)
135-
print 'scikits.learn: mean %.2f, std %.2f' % (
136-
np.mean(res_skl), np.std(res_skl))
137-
print 'Score: %2f\n' % score
138-
139-
score, res_mlpy = misc.bench(bench_mlpy, data)
140-
print 'MLPy: mean %.2f, std %.2f' % (
141-
np.mean(res_mlpy), np.std(res_mlpy))
142-
print 'Score: %2f\n' % score
143-
144-
score, res_pybrain = misc.bench(bench_pybrain, data)
145-
print 'Pybrain: mean %.2f, std %.2f' % (
146-
np.mean(res_pybrain), np.std(res_pybrain))
147-
print 'Score: %2f\n' % score
148-
149-
score, res_milk = misc.bench(bench_milk, data)
150-
print 'milk: mean %.2f, std %.2f' % (
151-
np.mean(res_milk), np.std(res_milk))
152-
print 'Score: %2f\n' % score
122+
'memory\n' % data[0].shape
123+
124+
score, res = misc.bench(bench_shogun, data)
125+
misc.print_result("kmeans", dataset, "Shogun", score, res)
126+
127+
score, res = misc.bench(bench_mdp, data)
128+
misc.print_result("kmeans", dataset, "MDP", score, res)
129+
130+
score, res = misc.bench(bench_skl, data)
131+
misc.print_result("kmeans", dataset, "scikits.learn", score, res)
132+
133+
score, res = misc.bench(bench_mlpy, data)
134+
misc.print_result("kmeans", dataset, "MLPy", score, res)
135+
136+
score, res = misc.bench(bench_pybrain, data)
137+
misc.print_result("kmeans", dataset, "Pybrain", score, res)
138+
139+
score, res = misc.bench(bench_milk, data)
140+
misc.print_result("kmeans", dataset, "milk", score, res)
141+
142+
misc.save_results()

Diff for: ‎benchmarks/bench_knn.py

+15-19
Original file line numberDiff line numberDiff line change
@@ -107,28 +107,24 @@ def bench_milk(X, y, T, valid):
107107
data = misc.load_data(dataset)
108108

109109
print 'Done, %s samples with %s features loaded into ' \
110-
'memory' % data[0].shape
110+
'memory\n' % data[0].shape
111111

112-
score, res_shogun = misc.bench(bench_shogun, data)
113-
print 'Shogun: mean %.2f, std %.2f\n' % (res_shogun.mean(), res_shogun.std())
114-
print 'Score: %.2f' % score
112+
score, res = misc.bench(bench_shogun, data)
113+
misc.print_result("knn", dataset, "Shogun", score, res)
115114

116-
score, res_mdp = misc.bench(bench_mdp, data)
117-
print 'MDP: mean %.2f, std %.2f\n' % (res_mdp.mean(), res_mdp.std())
118-
print 'Score: %.2f' % score
115+
score, res = misc.bench(bench_mdp, data)
116+
misc.print_result("knn", dataset, "MDP", score, res)
119117

120-
score, res_skl = misc.bench(bench_skl, data)
121-
print 'scikits.learn: mean %.2f, std %.2f\n' % (res_skl.mean(), res_skl.std())
122-
print 'Score: %.2f' % score
118+
score, res = misc.bench(bench_skl, data)
119+
misc.print_result("knn", dataset, "scikits.learn", score, res)
123120

124-
score, res_mlpy = misc.bench(bench_mlpy, data)
125-
print 'MLPy: mean %.2f, std %.2f\n' % (res_mlpy.mean(), res_mlpy.std())
126-
print 'Score: %.2f' % score
121+
score, res = misc.bench(bench_mlpy, data)
122+
misc.print_result("knn", dataset, "MLPy", score, res)
127123

128-
score, res_milk = misc.bench(bench_milk, data)
129-
print 'milk: mean %.2f, std %.2f\n' % (res_milk.mean(), res_milk.std())
130-
print 'Score: %.2f' % score
124+
score, res = misc.bench(bench_pymvpa, data)
125+
misc.print_result("knn", dataset, "PyMVPA", score, res)
131126

132-
score, res_pymvpa = misc.bench(bench_pymvpa, data)
133-
print 'PyMVPA: mean %.2f, std %.2f\n' % (res_pymvpa.mean(), res_pymvpa.std())
134-
print 'Score: %.2f' % score
127+
score, res = misc.bench(bench_milk, data)
128+
misc.print_result("knn", dataset, "milk", score, res)
129+
130+
misc.save_results()

Diff for: ‎benchmarks/bench_lassolars.py

+12-16
Original file line numberDiff line numberDiff line change
@@ -66,19 +66,15 @@ def bench_pymvpa(X, y, T, valid):
6666
data = misc.load_data(dataset)
6767

6868
print 'Done, %s samples with %s features loaded into ' \
69-
'memory' % data[0].shape
70-
71-
score, res_skl = misc.bench(bench_skl, data)
72-
print 'scikits.learn: mean %.2f, std %.2f' % (
73-
np.mean(res_skl), np.std(res_skl))
74-
print 'MSE: %s\n' % score
75-
76-
score, res_mlpy = misc.bench(bench_mlpy, data)
77-
print 'MLPy: mean %.2f, std %.2f' % (
78-
np.mean(res_mlpy), np.std(res_mlpy))
79-
print 'MSE: %s\n' % score
80-
81-
score, res_pymvpa = misc.bench(bench_pymvpa, data)
82-
print 'PyMVPA: mean %.2f, std %.2f' % (
83-
np.mean(res_pymvpa), np.std(res_pymvpa))
84-
print 'MSE: %s\n' % score
69+
'memory\n' % data[0].shape
70+
71+
score, res = misc.bench(bench_skl, data)
72+
misc.print_result("lassolars", dataset, "scikits.learn", score, res)
73+
74+
score, res = misc.bench(bench_mlpy, data)
75+
misc.print_result("lassolars", dataset, "MLPy", score, res)
76+
77+
score, res = misc.bench(bench_pymvpa, data)
78+
misc.print_result("lassolars", dataset, "PyMVPA", score, res)
79+
80+
misc.save_results()

Diff for: ‎benchmarks/bench_logistic.py

+5-4
Original file line numberDiff line numberDiff line change
@@ -36,8 +36,9 @@ def bench_skl(X, y, T, valid):
3636
data = misc.load_data(dataset)
3737

3838
print 'Done, %s samples with %s features loaded into ' \
39-
'memory' % data[0].shape
39+
'memory\n' % data[0].shape
4040

41-
res_skl = misc.bench(bench_skl, data)
42-
print 'MLPy: mean %.2f, std %.2f\n' % (
43-
np.mean(res_skl), np.std(res_skl))
41+
score, res = misc.bench(bench_skl, data)
42+
misc.print_result("logistic", dataset, "scikits.learn", score, res)
43+
44+
misc.save_results()

Diff for: ‎benchmarks/bench_pca.py

+7-5
Original file line numberDiff line numberDiff line change
@@ -108,16 +108,18 @@ def bench_milk(X, y, T, valid):
108108
'memory' % data[0].shape
109109

110110
score, res = misc.bench(bench_mdp, data)
111-
misc.print_result("MDP", score, res)
111+
misc.print_result("pca", dataset, "MDP", score, res)
112112

113113
score, res = misc.bench(bench_skl, data)
114-
misc.print_result("scikits.learn", score, res)
114+
misc.print_result("pca", dataset, "scikits.learn", score, res)
115115

116116
score, res = misc.bench(bench_pymvpa, data)
117-
misc.print_result("PyMVPA", score, res)
117+
misc.print_result("pca", dataset, "PyMVPA", score, res)
118118

119119
score, res = misc.bench(bench_pybrain, data)
120-
misc.print_result("Pybrain", score, res)
120+
misc.print_result("pca", dataset, "Pybrain", score, res)
121121

122122
score, res = misc.bench(bench_milk, data)
123-
misc.print_result("milk", score, res)
123+
misc.print_result("pca", dataset, "milk", score, res)
124+
125+
misc.save_results()

Diff for: ‎benchmarks/bench_svm.py

+9-9
Original file line numberDiff line numberDiff line change
@@ -175,27 +175,27 @@ def bench_orange(X, y, T, valid):
175175
'memory\n' % data[0].shape
176176

177177
score, res = misc.bench(bench_shogun, data)
178-
misc.print_result("svm", dataset, "Shogun", score, res)
178+
misc.print_result("svm", dataset, "Shogun", score, res)
179179

180180
score, res = misc.bench(bench_mdp, data)
181-
misc.print_result("svm", dataset, "MDP", score, res)
181+
misc.print_result("svm", dataset, "MDP", score, res)
182182

183183
score, res = misc.bench(bench_skl, data)
184-
misc.print_result("svm", dataset, "scikits.learn", score, res)
184+
misc.print_result("svm", dataset, "scikits.learn", score, res)
185185

186186
score, res = misc.bench(bench_mlpy, data)
187-
misc.print_result("svm", dataset, "MLPy", score, res)
187+
misc.print_result("svm", dataset, "MLPy", score, res)
188188

189189
score, res = misc.bench(bench_pymvpa, data)
190-
misc.print_result("svm", dataset, "PyMVPA", score, res)
190+
misc.print_result("svm", dataset, "PyMVPA", score, res)
191191

192192
score, res = misc.bench(bench_pybrain, data)
193-
misc.print_result("svm", dataset, "Pybrain", score, res)
193+
misc.print_result("svm", dataset, "Pybrain", score, res)
194194

195195
score, res = misc.bench(bench_milk, data)
196-
misc.print_result("svm", dataset, "milk", score, res)
196+
misc.print_result("svm", dataset, "milk", score, res)
197197

198198
score, res = misc.bench(bench_orange, data)
199-
misc.print_result("svm", dataset, "Orange", score, res)
199+
misc.print_result("svm", dataset, "Orange", score, res)
200200

201-
misc.save_results()
201+
misc.save_results()

Diff for: ‎benchmarks/misc.py

+14-10
Original file line numberDiff line numberDiff line change
@@ -2,6 +2,7 @@
22
import numpy as np
33
import os
44

5+
56
def load_data(dataset):
67

78
f = open(os.path.dirname(__file__) + '/data/%s_train.data' % dataset)
@@ -33,6 +34,7 @@ def load_data(dataset):
3334
def dtime_to_seconds(dtime):
3435
return dtime.seconds + (dtime.microseconds * 1e-6)
3536

37+
3638
def bench(func, data, n=10):
3739
"""
3840
Benchmark a given function. The function is executed n times and
@@ -44,7 +46,8 @@ def bench(func, data, n=10):
4446
----------
4547
func: function to benchmark
4648
47-
data: tuple (X, y, T, valid) containing training (X, y) and validation (T, valid) data.
49+
data: tuple (X, y, T, valid) containing training (X, y)
50+
and validation (T, valid) data.
4851
4952
Returns
5053
-------
@@ -64,24 +67,24 @@ def bench(func, data, n=10):
6467
print '%s error in function %s: ' % (repr(detail), func)
6568
time = []
6669
return score, np.array(time)
67-
6870

6971
task_string = ""
7072
dataset_string = ""
7173
packages = []
7274
scores = []
7375
means = []
7476
stds = []
75-
76-
def print_result(task, dataset, package, score, timing_results):
77+
78+
79+
def print_result(task, dataset, package, score, timing_results):
7780
global task_string
7881
global dataset_string
7982
global packages
8083
global scores
8184
global means
82-
global stds
83-
84-
print '%s on dataset %s' %(task, dataset)
85+
global stds
86+
87+
print '%s on dataset %s' % (task, dataset)
8588
mean = np.mean(timing_results)
8689
std = np.std(timing_results)
8790
print '%s: mean %.2f, std %.2f' % (package, mean, std)
@@ -92,8 +95,9 @@ def print_result(task, dataset, package, score, timing_results):
9295
packages.append(package)
9396
scores.append(score)
9497
means.append(mean)
95-
stds.append(std)
96-
98+
stds.append(std)
99+
100+
97101
def save_results():
98102
global task_string
99103
global dataset_string
@@ -106,4 +110,4 @@ def save_results():
106110
USAGE = """usage: python %s dataset
107111
108112
where dataset is one of {madelon, arcene}
109-
"""
113+
"""

0 commit comments

Comments
 (0)