Python numpy.testing.build_err_msg() Examples
The following are 15
code examples of numpy.testing.build_err_msg().
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Example #1
| Source File: test_utils.py From dynamic-training-with-apache-mxnet-on-aws with Apache License 2.0 | 6 votes |
|
def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan=False):
"""Test that two numpy arrays are almost equal. Raise exception message if not.
Parameters
----------
a : np.ndarray
b : np.ndarray
threshold : None or float
The checking threshold. Default threshold will be used if set to ``None``.
"""
rtol = get_rtol(rtol)
atol = get_atol(atol)
if almost_equal(a, b, rtol, atol, equal_nan=equal_nan):
return
index, rel = find_max_violation(a, b, rtol, atol)
np.set_printoptions(threshold=4, suppress=True)
msg = npt.build_err_msg([a, b],
err_msg="Error %f exceeds tolerance rtol=%f, atol=%f. "
" Location of maximum error:%s, a=%f, b=%f"
% (rel, rtol, atol, str(index), a[index], b[index]),
names=names)
raise AssertionError(msg)
Example #2
| Source File: test_io.py From Computable with MIT License | 6 votes |
|
def _assert_floatstr_lines_equal(actual_lines, expected_lines):
"""A string comparison function that also works on Windows + Python 2.5.
This is necessary because Python 2.5 on Windows inserts an extra 0 in
the exponent of the string representation of floating point numbers.
Only used in TestSaveTxt.test_complex_arrays, no attempt made to make this
more generic.
Once Python 2.5 compatibility is dropped, simply use `assert_equal` instead
of this function.
"""
for actual, expected in zip(actual_lines, expected_lines):
if actual != expected:
expected_win25 = expected.replace("e+00", "e+000")
if actual != expected_win25:
msg = build_err_msg([actual, expected], '', verbose=True)
raise AssertionError(msg)
Example #3
| Source File: test_utils.py From mxnet-lambda with Apache License 2.0 | 6 votes |
|
def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan=False):
"""Test that two numpy arrays are almost equal. Raise exception message if not.
Parameters
----------
a : np.ndarray
b : np.ndarray
threshold : None or float
The checking threshold. Default threshold will be used if set to ``None``.
"""
rtol = get_rtol(rtol)
atol = get_atol(atol)
if almost_equal(a, b, rtol, atol, equal_nan=equal_nan):
return
index, rel = find_max_violation(a, b, rtol, atol)
np.set_printoptions(threshold=4, suppress=True)
msg = npt.build_err_msg([a, b],
err_msg="Error %f exceeds tolerance rtol=%f, atol=%f. "
" Location of maximum error:%s, a=%f, b=%f"
% (rel, rtol, atol, str(index), a[index], b[index]),
names=names)
raise AssertionError(msg)
Example #4
| Source File: test_utils.py From SNIPER-mxnet with Apache License 2.0 | 6 votes |
|
def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan=False):
"""Test that two numpy arrays are almost equal. Raise exception message if not.
Parameters
----------
a : np.ndarray
b : np.ndarray
threshold : None or float
The checking threshold. Default threshold will be used if set to ``None``.
"""
rtol = get_rtol(rtol)
atol = get_atol(atol)
if almost_equal(a, b, rtol, atol, equal_nan=equal_nan):
return
index, rel = find_max_violation(a, b, rtol, atol)
np.set_printoptions(threshold=4, suppress=True)
msg = npt.build_err_msg([a, b],
err_msg="Error %f exceeds tolerance rtol=%f, atol=%f. "
" Location of maximum error:%s, a=%f, b=%f"
% (rel, rtol, atol, str(index), a[index], b[index]),
names=names)
raise AssertionError(msg)
Example #5
| Source File: timer_comparison.py From recruit with Apache License 2.0 | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #6
| Source File: timer_comparison.py From lambda-packs with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #7
| Source File: timer_comparison.py From vnpy_crypto with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #8
| Source File: timer_comparison.py From Mastering-Elasticsearch-7.0 with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #9
| Source File: timer_comparison.py From GraphicDesignPatternByPython with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #10
| Source File: timer_comparison.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #11
| Source File: timer_comparison.py From pySINDy with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #12
| Source File: timer_comparison.py From coffeegrindsize with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #13
| Source File: timer_comparison.py From Carnets with BSD 3-Clause "New" or "Revised" License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #14
| Source File: timer_comparison.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
Example #15
| Source File: timer_comparison.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ '\n(shapes %s, %s mismatch)' % (x.shape,
y.shape),
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg)
