abstract out common error functions

Author: Gregory Yauney

benchmarks/blackscholes/error.py

@@ -1,26 +1,20 @@
+import sys
 import numpy as np
-from scipy.special import erf
+sys.path.append('../..')
+from error_utils import *
 
 names_and_norms = [('l0', 0), ('l1', 1), ('l2', 2)]
 variances = [1, 100, 1000, 10000, 100000]
 names_and_args = [('%s_%d' % (name, variance), norm, variance)
   for name, norm in names_and_norms for variance in variances]
 error_names = [name for name, _, _ in names_and_args]
 
-def error_function(perforated, variance):
-    return erf(abs(perforated)/variance)
-
-def vector_from_file(fn):
-    with open(fn) as f:
-        f.readline()  # skip the count
-        return np.asarray([float(line) for line in f if line.strip()])
-
 def error(standard_fn, perforated_fn):
-    standard = vector_from_file(standard_fn)
-    perforated = vector_from_file(perforated_fn)
+    standard = get_vector(standard_fn)
+    perforated = get_vector(perforated_fn)
 
     results = {name:
-      error_function(np.linalg.norm(standard - perforated, ord=norm), variance)
+      norm_and_error_function(standard, perforated, norm, variance)
       for name, norm, variance in names_and_args}
 
     # any nan incurs the max error

benchmarks/img-blur/error.py

@@ -1,27 +1,21 @@
-import PIL
-import PIL.Image
-import numpy as np
-from scipy.special import erf
+import sys
+sys.path.append('../..')
+from error_utils import *
 
 names_and_norms = [('l0', 0), ('l1', 1), ('l2', 2)]
 variances = [1000, 10000, 100000]
 names_and_args = [('%s_%d' % (name, variance), norm, variance)
   for name, norm in names_and_norms for variance in variances]
 error_names = [name for name, _, _ in names_and_args]
 
-def error_function(perforated, variance):
-    return erf(abs(perforated)/variance)
-
 def error(standard_fn, perforated_fn):
-    standard_img = PIL.Image.open(standard_fn)
-    perforated_img = PIL.Image.open(perforated_fn)
 
     try:
-        standard = np.asarray(standard_img.getdata())
-        perforated = np.asarray(perforated_img.getdata())
+        standard = get_image(standard_fn)
+        perforated = get_image(perforated_fn)
     except ValueError:
         return {name: 1.0 for name in error_names}
 
     return {name:
-      error_function(np.linalg.norm(standard - perforated, ord=norm), variance)
+      norm_and_error_function(standard, perforated, norm, variance)
       for name, norm, variance in names_and_args}

benchmarks/sobel/error.py

@@ -1,27 +1,21 @@
-import PIL
-import PIL.Image
-import numpy as np
-from scipy.special import erf
+import sys
+sys.path.append('../..')
+from error_utils import *
 
 names_and_norms = [('l0', 0), ('l1', 1), ('l2', 2)]
 variances = [1000, 10000, 100000]
 names_and_args = [('%s_%d' % (name, variance), norm, variance)
   for name, norm in names_and_norms for variance in variances]
 error_names = [name for name, _, _ in names_and_args]
 
-def error_function(perforated, variance):
-    return erf(abs(perforated)/variance)
-
 def error(standard_fn, perforated_fn):
-    standard_img = PIL.Image.open(standard_fn)
-    perforated_img = PIL.Image.open(perforated_fn)
 
     try:
-        standard = np.asarray(standard_img.getdata())
-        perforated = np.asarray(perforated_img.getdata())
+        standard = get_image(standard_fn)
+        perforated = get_image(perforated_fn)
     except ValueError:
         return {name: 1.0 for name in error_names}
 
     return {name:
-      error_function(np.linalg.norm(standard - perforated, ord=norm), variance)
+      norm_and_error_function(standard, perforated, norm, variance)
       for name, norm, variance in names_and_args}

error_utils.py

@@ -0,0 +1,28 @@
+import sys
+from scipy.special import erf
+import numpy as np
+import PIL
+import PIL.Image
+
+def error_function(standard, perforated, variance):
+	return erf(abs(standard - perforated)/variance)
+
+def norm_and_error_function(standard, perforated, norm, variance):
+	return error_function(0, np.linalg.norm(standard - perforated, ord=norm), variance)
+
+def string_to_matrix(s):
+	# rows separated by '\n'
+	# columns separated by ' '
+	return np.asarray([[float(e) for e in l.split()] for l in s.strip().split('\n')])
+
+def get_contents(fn):
+	with open(fn, 'r') as f:
+		return f.read()
+
+def get_vector(fn):
+	with open(fn) as f:
+		f.readline()  # skip the count
+		return np.asarray([float(line) for line in f if line.strip()])
+
+def get_image(fn):
+	return np.asarray(PIL.Image.open(fn).getdata())

tests/matrix_multiply/error.py

@@ -1,37 +1,25 @@
 import sys
-import numpy as np
-from scipy.special import erf
+sys.path.append('../..')
+from error_utils import *
 
 names_and_norms = [('l2', 2), ('froebenius', 'fro')]
 variances = [1, 10, 100]
 names_and_args = [('%s_%d' % (name, variance), norm, variance)
   for name, norm in names_and_norms for variance in variances]
 error_names = [name for name, _, _ in names_and_args]
 
-def string_to_matrix(s):
-	return np.asarray([[float(e) for e in l.split()] for l in s.strip().split('\n')])
-
-def error_function(perforated, variance):
-	return erf(abs(perforated)/variance)
-
 def error(standard_fn, perforated_fn):
-	standard = get_contents(standard_fn)
-	perforated = get_contents(perforated_fn)
-	standard = string_to_matrix(standard)
-	perforated = string_to_matrix(perforated)
+	standard = string_to_matrix(get_contents(standard_fn))
+	perforated = string_to_matrix(get_contents(perforated_fn))
 
 	# max error if sizes differ
 	if standard.shape != perforated.shape:
 		return {name: 1.0 for name in error_names}
 
 	return {name:
-	  error_function(np.linalg.norm(standard - perforated, ord=norm), variance)
+	  norm_and_error_function(standard, perforated, norm, variance)
 	  for name, norm, variance in names_and_args}
 
-def get_contents(fn):
-	with open(fn, 'r') as f:
-		return f.read()
-
 def main():
 	standard_fn = sys.argv[1] if len(sys.argv) > 2 else 'standard.txt'
 	perforated_fn = sys.argv[2] if len(sys.argv) > 2 else 'perforated.txt'