2xN matrices

[csgirlie]

I'm trying to store or arrange three sets of two-dimensional data into three 2xN matrices that are stored as NumPy arrays.

1. import os                # for file handling functions
   2. import numpy as np            # for array/matrix processing
   3. import matplotlib.pyplot as plt        # for general plotting
   4. from mpl_toolkits.mplot3d import axes3d    # for 3d plotting
   5.  
   6. wordList=[]
   7. numFiles = 0
   8. numDataSets = numVectors = sizeVector = 0
   9.  
  10. print"\n\nBeginning data processing."
  11. # traverse filePath folder
  12. filePath = "Train"
  13. for file in os.listdir(filePath):
  14.     numDataSets +=1                # one data set per file
  15.     print "Loading the file: " + file + "."
  16.     tempFile = open(filePath+"/"+file, 'rU')
  17.     for line in tempFile:
  18.         numVectors +=1            # one vector per line
  19.         for word in line.split():
  20.             sizeVector +=1        # components in vector
  21.             wordList.append(word)
  22.  
  23. sizeVector = sizeVector / numVectors
  24. numVectors = numVectors / numDataSets
  25.  
  26. # print"\nHere's all the data:\n", wordList, "\n\n"
  27. print "numDataSets: ",numDataSets
  28. print "numVectors: ",numVectors
  29. print "sizeVector: ",sizeVector
  30. x = eval(wordList[5])
  31.  
  32. # Structure our arrays to hold our data.
  33. # We'll use the three sample class data sets from the text.
  34. # sizeVector of rows and numVectors of columns for column vector data.
  35. # In other words, each feature vector will be a column vector for set array.
  36. w1 = np.zeros((sizeVector, numVectors))
  37. w2 = np.zeros((sizeVector, numVectors))
  38. w3 = np.zeros((sizeVector, numVectors))
  39.  
  40. #   Load matrix array with class w1 numeric values,
  41. # replacing elements indexed as in matrices row, col starting from 0.
  42. #   Pull elements from wordList based on dataSet, sizeVector, and
  43. # which vector we're on during the column, row iteration.
  44.  
  45. skip = numVectors*sizeVector
  46.  
  47. dataSet = 0    
  48. for j in range(sizeVector):
  49.     for i in range(numVectors):
  50.         (do something - nothing I've tried is working)
  51. print "\nClass w1 is as follows: \n",w1
  52.  
  53. dataSet = 1    
  54. for j in range(sizeVector):
  55.     for i in range(numVectors):
  56.         (do something - nothing I've tried is working)
  57. print "\nClass w2 is as follows: \n",w2
  58.  
  59. dataSet = 2    
  60. for j in range(sizeVector):
  61.     for i in range(numVectors):
  62.         (do something - nothing I've tried is working)
  63. print "\nClass w3 is as follows: \n",w3

I need advice on how to get my dataSet(s) set up in this 2xN format.

This is re-posted from bytes.com, as I received no responses from anyone there. I'm new to python and am looking for the best forum to use.

[woooee]

Apparently the question is not specific enough. Do you want a numpy array or a multi-dimension list? If you want a multi-dimension list, that can be done with for loops. You can also use a dictionary of lists, using the row number as the key, if that is easier to use. A simple example:

master_list = []
row_list = []
row_list.append("a")
row_list.append("b")
master_list.append(row_list)
row_list = []
row_list.append("c")
row_list.append("d")
row_list.append("e")
master_list.append(row_list)

print master_list
print
for child_list in master_list:
   print child_list
print
print master_list[1]
print master_list[1][2]

[woooee]

Apparently the question is not specific enough. Do you want a numpy array or a multi-dimension list? If you want a multi-dimension list, that can be done with for loops. You can also use a dictionary of lists, using the row number as the key, if that is easier to use. A simple example:

master_list = []
row_list = []
row_list.append("a")
row_list.append("b")
master_list.append(row_list)

## declare row_list in a new block of memory
## if you just delete the contents you will be
## using the same object so any changes to 
## one will change the other as they both point
## to the same block of memory
row_list = []
for j in range(0, 3):
    row_list.append(j)
master_list.append(row_list)

print master_list
print
for child_list in master_list:
   print child_list
print
print master_list[1]
print master_list[1][2]