ORpKTKoVQnFhs / Public_Research (public) (License: MIT) (since 2019-12-01) (hash sha1)
This is a collection of programs related to research on my masters degree.
Clone URLs: https://rocketgit.com/user/ORpKTKoVQnFhs/Public_Research ssh://rocketgit@ssh.rocketgit.com/user/ORpKTKoVQnFhs/Public_Research git://git.rocketgit.com/user/ORpKTKoVQnFhs/Public_Research
00_simslope bite_counter master
List of commits:
Subject Hash Author Date (UTC)
simslope0_py: modified print statements 792110c3c83aa8ff78f7bf87ec8c01a4eacc94c7 Josiah_Mullins_E6440 2019-12-06 18:29:16
simslope0_py: optimization? 06c5626d1f26185d4f0da6bb535547228b198eab Josiah_Mullins_E6440 2019-12-06 18:21:34
simslope0_py: filename and exit dca5feb38bc896c2742e23da245c49e5c80ef30f Josiah_Mullins_E6440 2019-12-06 17:50:04
simslope_c: Output to file f8c52e106738ec13223144579d2b74aa0d290ade Josiah_Mullins_E6440 2019-12-06 17:41:09
simslope.c: type change 707e5be5af137023c28c12d54af35394cc32c9cc Josiah_Mullins_Optiplex_Mini 2019-12-01 22:21:44
Indentation 8606ab9f5e9d3b01f698a3303f5e6d39418b7bd5 Josiah_Mullins_Optiplex_Mini 2019-12-01 21:41:16
Simslope Initial commit. e9ccd3d49b4b1342341f1866a3f7a941af503b30 Josiah_Mullins_Optiplex_Mini 2019-12-01 21:24:04
Commit 792110c3c83aa8ff78f7bf87ec8c01a4eacc94c7 - simslope0_py: modified print statements
improved output in print statement formatting.
Author: Josiah_Mullins_E6440
Author date (UTC): 2019-12-06 18:29
Committer name: Josiah_Mullins_E6440
Committer date (UTC): 2019-12-06 18:29
Parent(s): 06c5626d1f26185d4f0da6bb535547228b198eab
Signing key:
Tree: 9d33ff842726737f15fd726e11cbcefd155255dc
File Lines added Lines deleted
00_simslope/simslope0.py 7 8
File 00_simslope/simslope0.py changed (mode: 100644) (index 47a2474..d7ebf1d)
13 13 #import tensorflow as tf #import tensorflow as tf
14 14 #from tensorflow import keras #from tensorflow import keras
15 15 import numpy as np import numpy as np
16 #To allow premature exit.
17 16 import sys import sys
18 17
19 18 # open file # open file
 
... ... d=[[int(x) for x in line.split()] for line in f]
22 21 f.close() f.close()
23 22
24 23 # copy to classes and data. # copy to classes and data.
24 #The cconvoluted statements below do pre-allocation of memory.
25 25 #classes contains the slope data. #classes contains the slope data.
26 26 #data contains the point data. #data contains the point data.
27 27 classes=[None]*len(d) classes=[None]*len(d)
 
... ... for a in range(0,len(d)):
33 33 for b in range(1,len(d[a])): for b in range(1,len(d[a])):
34 34 data[a][b-1] = d[a][b] data[a][b-1] = d[a][b]
35 35
36 print(len(classes))
37 print(len(data))
38 print(len(data[0]))
36 print('dimension of classes =',len(classes))
37 print('dimension of data =',len(data),'x',len(data[0]))
39 38
40 39 # normalize each row of data # normalize each row of data
41 40 normdata=[[None]*len(data[0]) for i in range(len(data))] normdata=[[None]*len(data[0]) for i in range(len(data))]
 
... ... for a in range(0,len(data)):
45 44 for b in range(0,len(data[a])): for b in range(0,len(data[a])):
46 45 normdata[a][b] = ((float(data[a][b])-s)/(t-s)) normdata[a][b] = ((float(data[a][b])-s)/(t-s))
47 46
48 print(len(normdata))
49 print(len(normdata[0]))
50 sys.exit()
47 print('dimension of normdata = ',len(normdata),'x',len(normdata[0]))
48
49
51 50 classes=np.array(classes) classes=np.array(classes)
52 51 data=np.array(normdata) data=np.array(normdata)
53 52
54 53 print("data has shape", data.shape) print("data has shape", data.shape)
55 54 print("classes has shape ", classes.shape) print("classes has shape ", classes.shape)
56
55 sys.exit()
57 56 # convert classes to one hot vectors (each vector position is a class) # convert classes to one hot vectors (each vector position is a class)
58 57 # don't need this, but left it in here in case I ever do # don't need this, but left it in here in case I ever do
59 58 # i.e. convert classes like 1 2 3 4 to [1 0 0 0] [0 1 0 0] [0 0 1 0] [0 0 0 1] # i.e. convert classes like 1 2 3 4 to [1 0 0 0] [0 1 0 0] [0 0 1 0] [0 0 0 1]
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