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author | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-01-23 18:29:21 -0700 |
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committer | GitHub <noreply@github.com> | 2020-01-23 18:29:21 -0700 |
commit | 7f122fdb38cd34916820d6ff4fb0e3a49fde80fc (patch) | |
tree | 47efddb979957029945a473fde6ed2cde2c2b196 /lj_matrix/frob_norm.py | |
parent | bd4fb4d77919bc75d3d181e124c3c5752a74dff3 (diff) | |
parent | 4704314c9b4d1066383da5c3d6ca87bba9067c8d (diff) |
Merge pull request #1 from luevano/add_parallel
Add parallel
Diffstat (limited to 'lj_matrix/frob_norm.py')
-rw-r--r-- | lj_matrix/frob_norm.py | 51 |
1 files changed, 51 insertions, 0 deletions
diff --git a/lj_matrix/frob_norm.py b/lj_matrix/frob_norm.py new file mode 100644 index 000000000..4c3a2945d --- /dev/null +++ b/lj_matrix/frob_norm.py @@ -0,0 +1,51 @@ +"""MIT License + +Copyright (c) 2019 David Luevano Alvarado + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. +""" +import math + + +def frob_norm(array): + """ + Calculates the frobenius norm of a given array or matrix. + array: array of data. + """ + + arr_sh_len = len(array.shape) + arr_range = range(len(array)) + fn = 0.0 + + # If it is a 'vector'. + if arr_sh_len == 1: + for i in arr_range: + fn += array[i]*array[i] + + return math.sqrt(fn) + + # If it is a matrix. + elif arr_sh_len == 2: + for i in arr_range: + for j in arr_range: + fn += array[i, j]*array[i, j] + + return math.sqrt(fn) + else: + print('Error. Array size greater than 2 ({}).'.format(arr_sh_len)) |