add the regression benchmark

benchmarks/regression/outputs.py

@@ -0,0 +1,64 @@
+# Copyright (c) 2015, Zhenwen Dai
+# Licensed under the BSD 3-clause license (see LICENSE.txt)
+
+from __future__ import print_function
+import abc
+import os
+import numpy as np
+
+class Output(object):
+    __metaclass__ = abc.ABCMeta
+    
+    @abc.abstractmethod
+    def output(self, config, results):
+        """Return the test data: training data and labels"""
+        return None
+
+class ScreenOutput(Output):
+            
+    def output(self, config, results):
+        print('='*10+'Report'+'='*10)
+        print('\t'.join([' ']+[m.name+'('+e+')' for m in config['methods'] for e in [a.name for a in config['evaluations']]+['time']]))
+        for task_i in range(len(config['tasks'])):
+            print(config['tasks'][task_i].name+'\t', end='')
+
+            outputs = []
+            for method_i in range(len(config['methods'])):
+                for ei in range(len(config['evaluations'])+1):
+                    m,s = results[task_i, method_i, ei].mean(), results[task_i, method_i, ei].std()
+                    outputs.append('%e(%e)'%(m,s))
+            print('\t'.join(outputs))
+
+class CSVOutput(Output):
+    
+    def __init__(self, outpath, prjname):
+        self.fname = os.path.join(outpath, prjname+'.csv')
+        
+    def output(self, config, results):
+        with open(self.fname,'w') as f:
+            f.write(','.join([' ']+[m.name+'('+e+')' for m in config['methods'] for e in [a.name for a in config['evaluations']]+['time']])+'\n')
+            for task_i in range(len(config['tasks'])):
+                f.write(config['tasks'][task_i].name+',')
+
+                outputs = []
+                for method_i in range(len(config['methods'])):
+                    for ei in range(len(config['evaluations'])+1):
+                        m,s = results[task_i, method_i, ei].mean(), results[task_i, method_i, ei].std()
+                        outputs.append('%e (%e)'%(m,s))
+                f.write(','.join(outputs)+'\n')
+            f.close()
+            
+class H5Output(Output):
+    
+    def __init__(self, outpath, prjname):
+        self.fname = os.path.join(outpath, prjname+'.h5')
+        
+    def output(self, config, results):
+            try:
+                import h5py
+                f = h5py.File(self.fname,'w')
+                d = f.create_dataset('results',results.shape, dtype=results.dtype)
+                d[:] = results
+                f.close()
+            except:
+                raise 'Fails to write the parameters into a HDF5 file!'