nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

list values in a table or array???

irinivozinaki

Hello everyone!

I would like to ask you if there is a way in python to do the following:

I have 20 values and I want to list them in a 5x4 array. Or is it better to list them in a 5x4 table? Which is the difference between the table and array in python???

(Is this helpful?) I need to save this table/array as an ascii file, which will be continuously converted in a raster file!

Thank you very much in advance!!!

Finde mehr Beiträge mit dem Tag

Accepted answers

All comments

irinivozinaki

I finally manage it through the help of the following link...

http://stackoverflow.com/questions/12223167/adding-header-to-numpy-array

Thank you all very much, have a nice day!!!

irinivozinaki

This is the output ascii file

Whereas the headers seem to be ok...
The first row of the calculated values is missing and the second is not properly written...

NCOLS 5
NROWS 4
XLLCORNER 513589
YLLCORNER 3923728
CELLSIZE 10
NODATA_VALUE -100
172 10.14299988747 10.28650045395 10.42899966240 10.57000041008
19.53180027008 19.10220050812 19.15980005264 19.21560001373 19.27019977570
20.64479970932 23.32259988785 23.50019931793 23.67780017853 23.85419940948

irinivozinaki

Yesterday I supposed that converting the ascii to raster file would be the easy thing. May be I was wrong 😞

Something goes wrong with the needed header of the ascii file.

I have created an ascii file (damageFile) which is the same with the one where the calculated values are saved.

I am writing the following...

damageFile=open('C:\\Python26\\ArcGIS10.0\\Python programming\\test2.ascii', "w+")
damageFile.write('NCOLS 5' + "\n")
damageFile.write('NROWS 4' + "\n")
damageFile.write('XLLCORNER 513589.931' + "\n")
damageFile.write('YLLCORNER 3923728.436' + "\n")
damageFile.write('CELLSIZE 10' + "\n")
damageFile.write('NODATA_VALUE -100' + "\n")

then the calculations follow under several scenarios...

and then the statement:

numpy.savetxt("C:\\Python26\\ArcGIS10.0\\Python programming\\test2.ascii", Damage, fmt="%14.11f", delimiter="w+")

and the damageFile is closed...

Can you find any mistake that I can see???

Thank you very much!!!

RaphaelR

you can build elaborate expressions with raster calculator as well:
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//009z000000z7000000.htm

however, going with python only is sometimes more straight forward (long/complex expressions in raster calculator can become a bit hard to read). i guess it´s a preference thing.

irinivozinaki

@ rafaelr

Your help was very important! My problem is solved for small grids! Let's try for bigger ones!!!

I am not good on python programming but I am trying...

I would like to ask you for the raster calculator.
As I can see it is an ArcGIS tool, but as long as the calculations among my cells are not the same every time, for all the cells.
For example I am checking whether the cell value of the first array is greater than one and the cell value of the second array is lower than 3 and if this happens the D value is calculated through a specific equation. But there are several scenarios for the read cell values...

So...It won't help me, will it?

Thank you again!!!

RaphaelR

not sure if i understand correctly but if you´re working on cell by cell basis, wouldn´t this be much easier with just using raster calculator?
anyways, code below creates a new array for the D parameter and writes it to an ascii file (no header, will need one if you want to use AsciiToRaster).

array_d=arcpy.RasterToNumPyArray(raster_d)
array_v=arcpy.RasterToNumPyArray(raster_v)
(height_d, width_d)=array_d.shape
(height_v, width_v)=array_v.shape

# create empty array to store the "D" parameter
newarr = np.zeros((5,4))


for row1 in range (0,height_d):

    row2=row1

    for col1 in range (0,width_d):
    
        col2=col1

        h=array_d.item(row1,col1)
        v=array_v.item(row2,col2)
        
        # calculate the "D" parameter
        expr = h+v
        
        newarr[row1,col1] =  expr

# write the new array to an ascii file
np.savetxt("e:/out.txt", newarr, fmt="%.2f", delimiter= " ")

irinivozinaki

Thank you all very much!!!

More accurately,

I have created part of a code which

a) takes two specific raster files (of a 5x4 grid) following a path

b) creates two separate arrays of 5x4 dimension
    I have used the following:
    array_d=arcpy.RasterToNumPyArray(raster_d)
    array_v=arcpy.RasterToNumPyArray(raster_v)
    (height_d, width_d)=array_d.shape
    (height_v, width_v)=array_velocity.shape

c) Subsequently, the code reads every cell value of both arrays, obtaining two values h, v

    for row1 in range (0,height_d):

        row2=row1

        for col1 in range (0,width_d):

            col2=col1

            h=array_d.item(row1,col1)
            v=array_v.item(row2,col2)

d) according to several scenarios of these values, h and v, the code calculates a parameter, named "D", in every cell. That is, the D parameter depends on the h and v.

I need to save the calculated parameter, "D", for every cell in a new array of the same dimensions (5x4 dimension), in an ascii file.
This ascii file will be converted subsequently to a raster file (I suppose this is the easy thing)

zhengniu

it is depending on how you will use this table or array, what they are used for.

ArkadiuszMatoszka

There are also arcpy functions to convert numpy Arrays to rasters and the other way around.
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//000v00000130000000

Didn't know about that. Always something new to learn 🙂
Cheers.
A

RaphaelR

Hi Irini,

for Arrays in python numpy is really handy.
There are also arcpy functions to convert numpy Arrays to rasters and the other way around.
http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//000v00000130000000

for example

import numpy as np

a = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]

a = np.array(a)
a = np.reshape(a, (4,5))

will get you:

[[ 1  2  3  4  5]
 [ 6  7  8  9 10]
 [11 12 13 14 15]
 [16 17 18 19 20]]

ArkadiuszMatoszka

Hi,
In my considered opinion there is no reason to use either of this to for this purpose. Simple list slicing with defined number of columns will do the trick.

Simple example:

i = range(20)
cols = 4
f = open('D:\\tmp.csv', 'w')
for r in range(len(i)/cols):
    f.write(';'.join([str(v) for v in i[r*cols:(r+1)*cols]]) + '\n')

Regards
Arek

Nimm an der Unterhaltung teil

Angemeldete Mitglieder können Beiträge verfassen, Updates folgen und mehr. Neu hier? Registriere ein kostenloses Konto.

Schnellzugriffe

Community Help
Find useful guides, FAQs, and documents to help you navigate and make the most of Esri Community.