avoding the accumulation of array when using loop.

[Isaac Won]

Hi all,

Thanks to Hans, I have had a good progress on my problem.

Followings are Hans's Idea:

import numpy as np

b = []
c = 4
f = open("text.file", "r")

while c < 10:
c = c + 1


f.seek(0,0)

for columns in ( raw.strip().split() for raw in f ):
b.append(columns[c])

y = np.array(b, float)
print c, y


It's a bit inefficient to read the same file several times.
You might consider reading it just once. For example:


import numpy as np

b = []



f = open("text.file", "r")

data = [ line.strip().split() for line in f ]
f.close()

for c in xrange(5, 11):
for row in data:
b.append(row[c])


y = np.array(b, float)
print c, y
-------------------------------------------------------------------------------

It is a great idea, but I found some problems. I want each individual arrayof y. However, these two codes prodce accumulated array such as [1,2,3], [1,2,3,4,5,6], [1,2,3,4,5,6,7,8,9] and so on. I have tried to initialize forloop for each time to produce array. This effort has not been very successful.
Do you guys have any idea? I will really appreciate ant help and idea.

Thanks,

Isaac

 

[Dave Angel]

Hi all,

Thanks to Hans, I have had a good progress on my problem.

Followings are Hans's Idea:

import numpy as np

b = []
c = 4
f = open("text.file", "r")

while c < 10:
c = c + 1


f.seek(0,0)

for columns in ( raw.strip().split() for raw in f ):
b.append(columns[c])

y = np.array(b, float)
print c, y


It's a bit inefficient to read the same file several times.

Don't bet on it. The OS and the libraries and Python each do some
buffering, so it might be nearly as fast to just reread if it's a small
file. And if it's a huge one, the list would be even bigger. So the
only sizes where the second approach is likely better is the mid-size file.

You might consider reading it just once. For example:


import numpy as np

b = []



f = open("text.file", "r")

data = [ line.strip().split() for line in f ]
f.close()

for c in xrange(5, 11):
for row in data:
b.append(row[c])


y = np.array(b, float)
print c, y

Your description is very confusing. But i don't see why you just don't
just set b=[] inside the outer loop, rather than doing it at the begin
of the program.

for c in xrange(5, 11):
b = []
for row in data:
b.append(row[c])

 

[Isaac Won]

Hi all,
Thanks to Hans, I have had a good progress on my problem.
Followings are Hans's Idea:
import numpy as np
b = []

c = 4

f = open("text.file", "r")

while c < 10:

c = c + 1


f.seek(0,0)

for columns in ( raw.strip().split() for raw in f ):

b.append(columns[c])
y = np.array(b, float)

print c, y


It's a bit inefficient to read the same file several times.

Don't bet on it. The OS and the libraries and Python each do some

buffering, so it might be nearly as fast to just reread if it's a small

file. And if it's a huge one, the list would be even bigger. So the

only sizes where the second approach is likely better is the mid-size file.

You might consider reading it just once. For example:
import numpy as np
b = []
f = open("text.file", "r")
data = [ line.strip().split() for line in f ]

f.close()

for c in xrange(5, 11):

for row in data:

b.append(row[c])
y = np.array(b, float)

print c, y

-------------------------------------------------------------------------------

It is a great idea, but I found some problems. I want each individual array of y. However, these two codes prodce accumulated array such as [1,2,3], [1,2,3,4,5,6], [1,2,3,4,5,6,7,8,9] and so on. I have tried to initializefor loop for each time to produce array. This effort has not been very successful.

Do you guys have any idea? I will really appreciate ant help and idea.

Your description is very confusing. But i don't see why you just don't

just set b=[] inside the outer loop, rather than doing it at the begin

of the program.



for c in xrange(5, 11):

b = []

for row in data:

b.append(row[c])







--



DaveA

Hi Dave,

I really appreciate your advice. It was really helpful.

Isaac

 

[Isaac Won]

Hi all,
Thanks to Hans, I have had a good progress on my problem.
Followings are Hans's Idea:
import numpy as np
b = []

c = 4

f = open("text.file", "r")

while c < 10:

c = c + 1


f.seek(0,0)

for columns in ( raw.strip().split() for raw in f ):

b.append(columns[c])
y = np.array(b, float)

print c, y


It's a bit inefficient to read the same file several times.

Don't bet on it. The OS and the libraries and Python each do some

buffering, so it might be nearly as fast to just reread if it's a small

file. And if it's a huge one, the list would be even bigger. So the

only sizes where the second approach is likely better is the mid-size file.

You might consider reading it just once. For example:
import numpy as np
b = []
f = open("text.file", "r")
data = [ line.strip().split() for line in f ]

f.close()

for c in xrange(5, 11):

for row in data:

b.append(row[c])
y = np.array(b, float)

print c, y

-------------------------------------------------------------------------------

It is a great idea, but I found some problems. I want each individual array of y. However, these two codes prodce accumulated array such as [1,2,3], [1,2,3,4,5,6], [1,2,3,4,5,6,7,8,9] and so on. I have tried to initializefor loop for each time to produce array. This effort has not been very successful.

Do you guys have any idea? I will really appreciate ant help and idea.

Your description is very confusing. But i don't see why you just don't

just set b=[] inside the outer loop, rather than doing it at the begin

of the program.



for c in xrange(5, 11):

b = []

for row in data:

b.append(row[c])







--



DaveA

Hi Dave,

I really appreciate your advice. It was really helpful.

Isaac