[英]Python: read timesteps from csv to arrays: Post-processing model-data with numpy;
I am still trying to come around with python, but this problem exceeds my knowledge: 我仍在尝试使用python,但是这个问题超出了我的知识范围:
Topic: hydrodynamic postprocessing: csv output of hydraulic software to array, split timesteps 主题:流体动力后处理:液压软件的csv输出到阵列,分段时间步
Here is the data and how far i came with a working code: 这是数据,以及有效代码的有效距离:
Input-file (see below): 输入文件(见下文):
First row: Number of result-nodes 第一行:结果节点数
Second row: Header 第二行:标题
Third row: timestep @ time= 第三行:timestep @ time =
Following: all results of this timestep (in this file: 13541 nodes, variable) ....the same again for next timestep. 随后:该时间步的所有结果(在此文件中:13541个节点,变量)..下一个时间步再次相同。
# Number of Nodes: 13541
#X Y Z depth wse
# Output at t = 0
5603.7598 4474.4902 37.470001 0 37.470001
5610.5 4461.6001 36.020001 0 36.020001
5617.25 4448.71 35.130001 0 35.130001
5623.9902 4435.8198 35.07 0 35.07
5630.7402 4422.9199 35.07 0 35.07
5761.5801 4402.79 35.369999 0 35.369999
COMMENT:....................13541 timesteps...........
# Output at t = 120.04446
5603.7598 4474.4902 37.470001 3.6977223 41.167724
5610.5 4461.6001 36.020001 4.1377293 40.15773
5617.25 4448.71 35.130001 3.9119012 39.041902
5623.9902 4435.8198 35.07 3.7923947 38.862394
5630.7402 4422.9199 35.07 3.998436 39.068436
5761.5801 4402.79 35.369999 3.9750571 39.345056
COMMENT:....................13541 timesteps...........
# Output at t = 240.06036
5603.7598 4474.4902 37.470001 11.131587 48.601588
5610.5 4461.6001 36.020001 12.564266 48.584266
5617.25 4448.71 35.130001 13.498463 48.628464
5623.9902 4435.8198 35.07 13.443041 48.513041
5630.7402 4422.9199 35.07 11.625824 46.695824
5761.5801 4402.79 35.369999 19.49551 54.865508
PROBLEM: I need a loop, which reads in n-timesteps into arrays. 问题:我需要一个循环,将n个时间步读入数组。
The result should be: array for each timestep: in this case 27 timesteps with 13541 elements each. 结果应为:每个时间步的数组:在这种情况下,为27个时间步,每个时间步都有13541个元素。
timestep_1=[all elements of this timestep: shape=13541,5] timestep_1 = [此时间步长的所有元素:shape = 13541,5]
timestep_2=[] timestep_2 = []
timestep_3[] timestep_3 []
........ ........
timestep_n=[] timestep_n = []
My code so far: 到目前为止,我的代码:
import numpy as np
import csv
from numpy import *
import itertools
#read file to big array
array=np.array([row for row in csv.reader(open("ascii-full.csv", "rb"), delimiter='\t')])
firstRow=array[0]
secondRow=array[1]
# find out how many nodes
strfirstRow=' '.join(map(str,firstRow))
first=strfirstRow.split()
print first[4]
nodes=first[4]
nodes=float(nodes)
#count timesteps
temp=(len(array)-3)/nodes
timesteps=int(temp)+1
#split array into timesteps:
# X Y Z h(t1) h(t2) h(tn)
ts1=array[3:nodes+3]#13541
#print ts1
ts2=array[nodes+4:nodes*2+4]
#print ts2
.......
read ts3 to last timestep to arrays with loop....
Maybe someone can help me, thanks!!! 也许有人可以帮助我,谢谢!!!
You can use np.genfromtxt()
to get a 3-D array like: 您可以使用
np.genfromtxt()
获得3-D数组,例如:
import numpy as np
gen = (a for a in open('test.txt') if not a[0] in ['#', 'C'])
a = np.genfromtxt(gen).reshape(-1, 6, 5)
where a[i]
will represent the output at timestep i
. 其中
a[i]
代表时间步长i
的输出。
My take on your problem is, instead of reading the whole file into an array and process the array, read it line by line, creating the arrays as the data is read. 我对您的问题的看法是,与其将整个文件读入一个数组并进行处理,不如逐行读取它,而是在读取数据时创建数组。
I read the number of rows and columns per timestep as described in the file, then create a new array for each timestep read (adding it to a list), then populating it with the read data. 我按文件中所述读取每个时间步的行数和列数,然后为每个读取的时间步创建一个新数组(将其添加到列表中),然后使用读取的数据填充它。
import numpy as np
timesteps = []
timestep_results = []
f = open("ascii-full.csv", "rb")
# First line is number of rows (not counting the initial #)
rows = int(f.readline().strip()[1:].split()[-1])
counter = 0
# Second line is number of columns
columns = len(f.readline().strip().split())
# Next lines
for line in f:
if line.startswith("#"):
# it's a header: add time to timestep list, begin new array
timesteps.append( float(line.strip().split("=")[1]) )
timestep_results.append( np.zeros((rows, columns)) )
counter = 0
else:
# it's data: add to array in appropiate row
timestep_results[-1][counter] = map(float, line.strip().split())
counter += 1
f.close()
Hope it helps! 希望能帮助到你!
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