def dot(one, two):
'''
implements one dotprod two.
params:
- one,two: splunkarrays to dot product
returns:
- a new splunk array that correctly represents the dot product of the two passed in arrays
notes:
- the strategy is to iterate through and set the new array with elements using vector dot products (vector_dot_string). i.e each element of the new array is the vector dot product of rows/columns of the old arrays
'''
# check shapes
if one.shape[1] != two.shape[0]:
raise Exception(
"Those shapes don't dot with each other! shapes were %s, %s" %
(one.shape, two.shape))
# initialize the output array
output_sa = SplunkArray(one.name + '_dot_' + two.name,
(one.shape[0], two.shape[1]))
# set the output array's string
output_sa.string = splunk_concat(one.string, two.string)
# now calculate the dot product
for i in range(output_sa.shape[0]):
for j in range(output_sa.shape[1]):
# A_i,j = the i'th row of "one" dotted with the j'th column of "two":
output_sa.set_element(
i, j, vector_dot_string(one.elems[i], two.elems[:, j]))
# output_sa.string += 'eval %s_%s_%s = %s | ' % (output_sa.name, i, j, vector_dot_string(one.elems[i], two.elems[:,j]))
# output_sa.string = output_sa.string[:-2]
output_sa.find_elements()
return output_sa
def dot(one, two):
'''
implements one dotprod two.
params:
- one,two: splunkarrays to dot product
returns:
- a new splunk array that correctly represents the dot product of the two passed in arrays
notes:
- the strategy is to iterate through and set the new array with elements using vector dot products (vector_dot_string). i.e each element of the new array is the vector dot product of rows/columns of the old arrays
'''
# check shapes
if one.shape[1] != two.shape[0]:
raise Exception ("Those shapes don't dot with each other! shapes were %s, %s" % (one.shape, two.shape))
# initialize the output array
output_sa = SplunkArray(one.name + '_dot_' + two.name, (one.shape[0], two.shape[1]))
# set the output array's string
output_sa.string = splunk_concat(one.string, two.string)
# now calculate the dot product
for i in range(output_sa.shape[0]):
for j in range(output_sa.shape[1]):
# A_i,j = the i'th row of "one" dotted with the j'th column of "two":
output_sa.set_element(i, j, vector_dot_string(one.elems[i], two.elems[:,j]))
# output_sa.string += 'eval %s_%s_%s = %s | ' % (output_sa.name, i, j, vector_dot_string(one.elems[i], two.elems[:,j]))
# output_sa.string = output_sa.string[:-2]
output_sa.find_elements()
return output_sa
def elementwise_func(sa, func):
'''
elementwise func "func" on the elements of sa. func expected to be the name of a func in splunk i.e "ln"
'''
output = SplunkArray(func + '_d' + sa.name, sa.shape)
output.string = sa.string
output.find_elements()
for i, j in sa.iterable():
output.set_element(i, j, func + '(%s)' % sa.elems[i][j])
return output
def elementwise_func(sa, func): ''' elementwise func "func" on the elements of sa. func expected to be the name of a func in splunk i.e "ln" ''' output = SplunkArray(func+'_d'+sa.name, sa.shape) output.string = sa.string output.find_elements() for i,j in sa.iterable(): output.set_element(i,j, func+'(%s)' % sa.elems[i][j]) return output
def elementwise_func_withargs(sa, func, arg):
'''
elementwise func "func" on the elements of sa, with passed in arg 'arg'. func expected to be the name of a func in splunk i.e "pow"
pow(field, exponent)
'''
output = SplunkArray(func + '_d' + sa.name, sa.shape)
output.string = sa.string
output.find_elements()
for i, j in sa.iterable():
output.set_element(i, j, func + '(%s,%s)' % (sa.elems[i][j], arg))
return output
def elementwise_func_withargs(sa, func, arg): ''' elementwise func "func" on the elements of sa, with passed in arg 'arg'. func expected to be the name of a func in splunk i.e "pow" pow(field, exponent) ''' output = SplunkArray(func+'_d'+sa.name, sa.shape) output.string = sa.string output.find_elements() for i,j in sa.iterable(): output.set_element(i,j, func+'(%s,%s)' % (sa.elems[i][j], arg)) return output
