shuffle related rows

Comments

• sp4m

  June 2018

  Edit: You can see that I tried to do it blockwise, but I need a full randomization, so this is not what I was looking for.
• sp4m

  June 2018

  Edit: Also tried it with coding:

  
  

  But unfortunately Python always crashes.
• Sylvain

  June 2018

  Hello,

  So if I understood you want to random one column while keeping the other constant?
  If so a stategy could be:

  • first you enter your initial matrix in a loop at the very beginning of your scrip (just to load it);
  • then you extract these values, just random the first column in a new datamatrix, then copy this new randomized datamatrix in the subsequant loop.

  Like this:
  

  With the inline for randomizing and preparing the subsequant loop as:

  from datamatrix import DataMatrix
  import random
  
  # create a list to stock the element from the column of the datamatrix (ie Load_Item_Loop)
  # to randomize
  
  list_column1_to_randomize = list()
  
  # fill this list
  for row in items['Load_Item_Loop'].dm.column1_name:
      list_column1_to_randomize.append(row)
  
  # randomize the list
  random.shuffle(list_column1_to_randomize)
  
  # then create a new datamatrix that will be used for the subsequent loop where
  # column1_name is randomized but the other column not randomized
  # create the new datamatrix
  
  new_dm = DataMatrix(length=len(list_column1_to_randomize))
  # fill the first column with the randomized list
  new_dm.column1_name = list_column1_to_randomize
  # initialize and fill the two other columns
  new_dm.column2_name = ''
  new_dm.column3_name = ''
  
  for i, row in enumerate(new_dm.column2_name):
      new_dm.column2_name[i] = items['Load_Item_Loop'].dm.column2_name[i]
      new_dm.column3_name[i] = items['Load_Item_Loop'].dm.column3_name[i]
  
  # now copy the new_dm in new_loop (it will become the new values of this loop)
  items['new_loop'].dm = new_dm
  

  Find the script too maybe it will be more explicit.
  Just be sure you change the two loop as sequential (I do not think it matters a lot but up to you)

  Best,

  Sylvain
• sp4m

  June 2018

  Hello Sylvain,

  thank you for replying. I started the experiment you added and the first column is randomized, that's exactly what I want! But column 2 and 3 are presented sequentially (even if I change 'order' to 'random'). This should not be the case. Plus, the biggest problem I have is that the items in column 1 are presented two times, so they should be randomized but like this:
  column 1, row 1 to 8 is randomized (e.g. 6, 4, 7, 3, 2, 1, 8, 5) and this order is attached to the items in column 2. Row 9 to 16 in column 1 and 2 should contain the same pairing as row 1 to 8. Does this make any sense? ':D

  Caro
• sp4m

  June 2018

  And maybe you could tell me what is wrong with the code mentioned above? Because I do not understand why Python always crashes.
• Sylvain

  June 2018

  I do not really know why it crashes otherwise if I understood what you want you could try that:

  from datamatrix import DataMatrix, operations
  import random
  
  # create a list to stock the element from the column of the datamatrix (ie Load_Item_Loop)
  # to randomize
  
  list_column1_to_randomize = list()
  
  # fill this list
  for row in items['Load_Item_Loop'].dm.column1_name:
      list_column1_to_randomize.append(row)
  
  # randomize the list
  random.shuffle(list_column1_to_randomize)
  
  # then create a new datamatrix that will be used for the subsequent loop where
  # column1_name is randomized but the other column not randomized
  # create the new datamatrix
  
  new_dm = DataMatrix(length=len(list_column1_to_randomize))
  # fill the first column with the randomized list
  new_dm.column1_name = list_column1_to_randomize
  # initialize and fill the two other columns
  new_dm.column2_name = ''
  new_dm.column3_name = ''
  
  for i, row in enumerate(new_dm.column2_name):
      new_dm.column2_name[i] = items['Load_Item_Loop'].dm.column2_name[i]
      new_dm.column3_name[i] = items['Load_Item_Loop'].dm.column3_name[i]
  
  print(new_dm)
  
  # now shuffle everything but keep row associated
  
  final_dm = operations.shuffle(new_dm)
  
  # repeat it n times and concatenate
  
  repeat = 1
  for r in range(repeat):
      dm_repeat = operations.shuffle(new_dm)
      final_dm = final_dm << dm_repeat
  
  
  
  print(final_dm)
  
  
  # now copy the new_dm in new_loop (it will become the new values of this loop)
  items['new_loop'].dm = final_dm
  
  

  Datamatrix function are on this page:
  http://datamatrix.cogsci.nl/

  And find the modified script.

  Hope it will work this time.
• sp4m

  June 2018

  Hello Sylvain,

  wow, thanks alot! This looks like it could be a very nice solution for my problem. So far I got it going by this code:

  

  But I think your code looks much nicer and as if it could be used in a more general way. I will try it this way as well Thank you so much for your time and this nice piece of code!

  Caro