I am attempting to produce a transformation matrix based on the first column of a csv file. There are 59 possible states, which are integers in a list.
At the moment my output is simply a long list of '0.000s' - in the correct size as far as I can tell (59*59), but without the weights that it should have.
The data is definitely in the activities list, because it can be printed separately.
import csv
data = open('file.csv')
csv_data = csv.reader(data)
data_lines = list(csv_data)
activities = []
for row in data_lines[:5954]:
activities.append(row[0])
activities = list(map(int, activities))
def transition_matrix(activities):
n = 59 #number of states
m = [[0]*n for _ in range(n)]
for (i,j) in zip(activities,activities[1:]):
m[i][j] += 1
#now convert to probabilities:
for row in m:
s = sum(row)
if s > 0:
row[:] = [f/s for f in row]
return m
t = [activities]
m = transition_matrix(t)
for row in m: print(' '.join('{0:.3f}'.format(x) for x in row))
You are declaring t as a list which contains activities.
However, activities is already a list.
This means that your function won't run as expected as you're not passing data in the right format. To fix this, just use t = activities, or just directly pass activites into transition_matrix() without using t.