从 CSV 文件读取时对数组进行数值运算

Question

I am trying to do a few numerical operations on a few arrays while reading some values from CSV files.

I have the coordinates of a receiver which is fixed and I read coordinates of the heliostats from a CSV file which track the Sun.

The coordinates of the receiver:

# co-ordinates of Receiver
XT = 0  # X co-ordinate of Receiver
YT = 0   # Y co-ordinate of Receiver
ZT = 207.724  # Z co-ordinate of Receiver, this is the height of tower 
A = np.array(([XT],[YT],[ZT]))
print(A," are the co-ordinates of the target i.e. the receiver")

The coordinates of the ten heliostats: This data I read from a CSV file with the follwoing data:

#X,Y,Z
#-1269.56,-1359.2,5.7
#1521.28,-68.0507,5.7
#-13.6163,1220.79,5.7
#-1388.76,547.708,5.7
#1551.75,-82.2342,5.7
#405.92,-1853.83,5.7
#1473.43,-881.703,5.7
#1291.73,478.988,5.7
#539.027,1095.43,5.7
#-1648.13,-73.7251,5.7

I read the coordinates of the CSV as follows:

import csv
# Reading data from csv file
with open('Heliostat Field Layout Large heliostat.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
X = []
Y = []
Z = []
for row in readCSV:
    X_coordinates = row[0]
    Y_coordinates = row[1]
    Z_coordinates = row[2]
    X.append(X_coordinates)
    Y.append(Y_coordinates)
    Z.append(Z_coordinates)
Xcoordinate = [float(X[c]) for c in range(1,len(X))]
Ycoordinate=[float(Y[c]) for c in range(1,len(Y))]
Zcoordinate=[float(Z[c]) for c in range(1,len(Z))]

Now, when I try to print the co-ordinates of the ten heliostats, I get three big arrays with all Xcoordinate, Ycoordinate and Zcoordinate grouped into one instead of ten different outputs.

 [[[-1269.56    1521.28     -13.6163 -1388.76    1551.75     405.92    1473.43
1291.73     539.027  -1648.13  ]]

 [[-1359.2      -68.0507  1220.79     547.708    -82.2342 -1853.83
-881.703    478.988   1095.43     -73.7251]]

 [[    5.7        5.7        5.7        5.7        5.7        5.7        5.7
   5.7        5.7        5.7   ]]]  are the co-ordinates of the heliostats

I used:

B = np.array(([Xcoordinate],[Ycoordinate],[Zcoordinate]))
print(B," are the co-ordinates of the heliostats")

What is the mistake?

Further, I would like to have an array where I wuold like B - A for which I use:

#T1 = matrix(A)- matrix(B)
#print(T1," is the target vector for heliostat 1, T1")

How should i do a numerical operation on Arrays A and B? I tried a matrix operation here. Is that wrong?

Answer 1

Your code is correct

The following output is the way numpy arrays are displayed.

[[-1359.2 -68.0507 1220.79 547.708 -82.2342 -1853.83 -881.703 478.988 1095.43 -73.7251]]

Despite the illusion that the values are stuck together, they are perfectly distinct in the array. You can access to a single value with

print(B[1, 0, 0])    # print Y[0]

The substraction of arrays A and B you want to perform will work

T1 = np.matrix(A)- np.matrix(B)
print(T1," is the target vector for heliostat 1, T1")

---

May I make two suggestions ?

• You can read a numpy array written as a matrix in a text file (it's the case here) with the function loadtxt of numpy :

   your_file = 'Heliostat Field Layout Large heliostat.csv' B = np.loadtxt(your_file, delimiter=',', skiprows=1)

  The result will be a (3, 10) numpy array.

• You can perform broadcasing operations directly on numpy arrays (so you don't need to convert it in matrix). You just need to be careful with the dimensions.

  In your original script you just need to write :

   T1 = A - B

  If you get array B with loadtxt as suggested, you will get a (10, 3) array, while A is a (3, 1) array. The array B must first be reshaped in a (3, 10) array :

   B = B.reshape((3, 10)) T1 = A - B

---

EDIT : compute the norm of each 3D vector of T1

norm_T1 = np.sqrt( np.sum( np.array(T1)**2, axis=0 ) )

Note that in your code T1 is a matrix, so T1**2 is a matrix product. In order to compute sqrt( v[0]**2 + v[1]**2 + v[2]**2 ) for each vector v of T1, I first convert it to a numpy array.