Average product of arrays

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Laxmi Bhatta
Laxmi Bhatta 2023-3-10
评论： Laxmi Bhatta 2023-3-12
Hi
I have an excel sheet having following informations;
flows occupancy
{6,18,17,14} {0.0383,0.13,0.1794,0.1522}
{12,14,12,5} {0.0717,0.0978,0.1117,0.0633}
{16,11,13,12} {0.1006,0.08,0.0978,0.1839}
In one column there is flows {x1,x2,x3,x4} and another column there is occupancy {y1,y2,y3,y4}
I need to make Matlab code as follows
averageproduct = average (x1*y1+x2*y2+x3*y3+x4*y4)
the number of rows are about more than 15000
Could you help me in this matter
  2 个评论
Laxmi Bhatta
Laxmi Bhatta 2023-3-11
移动：Stephen23 2023-3-11
% Define the data as arrays
flows = {[6,18,17,14]; [12,14,12,5]; [16,11,13,12]};
occupancy = {[0.0383,0.13,0.1794,0.1522]; [0.0717,0.0978,0.1117,0.0633]; [0.1006,0.08,0.0978,0.1839]};
I have 25000 data and how would I type such a huge data, could you please make this defination that can be valid for all.
Stephen23
Stephen23 2023-3-11
编辑：Stephen23 2023-3-11
Ran in:
"I have an excel sheet ..."
What you uploaded is a CSV file. A CSV file is a text file that exists completely independently from MS Excel.
"In one column there is flows {x1,x2,x3,x4} and another column there is occupancy {y1,y2,y3,y4}"
Note that the CSV file columns FLOWS and OCCUPANCY do not have constant four terms each, e.g. from row 944 the number of terms increases from four to five, then from row 1896 it decreases back to four again. So your solution needs to take this into account (e.g. as my answer does).
For example, the term distribution for FLOWS is as follows:
T = readtable('pems_rawdata_NB.csv');
V = cellfun(@(t)numel(sscanf(strrep(t,'{',''),'%f,')),T.flows);
plot(V,'*r')
ax = gca;
ax.XAxis.Exponent = 0;
xlabel('Row Number')
ylabel('Number of Terms')

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采纳的回答

Stephen23
Stephen23 2023-3-11
编辑：Stephen23 2023-3-11
Ran in:
T = readtable('pems_rawdata_NB.csv')
T = 25866×15 table
fk_pems_id postmile unixtime flows occupancy Var6 Var7 Var8 Var9 Var10 Var11 Var12 Var13 Var14 Var15 __________ ________ __________ _________________ _________________________________ ____ ____ ____ ___________ _____ _____ _____ ______ __________ ______ 4.0004e+05 26 1.2025e+09 {'{6,18,17,14}' } {'{0.0383,0.13,0.1794,0.1522}' } NaN NaN NaN {'#VALUE!'} NaN NaN NaN 1.0341 0.00064256 2.3132 4.0004e+05 26 1.2025e+09 {'{12,14,12,5}' } {'{0.0717,0.0978,0.1117,0.0633}'} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{16,11,13,12}'} {'{0.1006,0.08,0.0978,0.1839}' } NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{8,11,9,8}' } {'{0.0467,0.085,0.1244,0.0572}' } NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{8,11,9,8}' } {'{0.0467,0.085,0.1244,0.0572}' } NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{10,17,17,11}'} {'{0.0639,0.1206,0.1333,0.1228}'} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{8,12,8,6}' } {'{0.0517,0.0828,0.0906,0.0722}'} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {'{12,13,8,12}' } {'{0.0761,0.0894,0.1294,0.1939}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{5,12,7,7}' } {'{0.0289,0.0778,0.0472,0.0806}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{4,11,8,7}' } {'{0.0256,0.0722,0.1133,0.1122}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{9,10,10,6}' } {'{0.0522,0.0644,0.07,0.0933}' } NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{17,16,9,16}' } {'{0.1089,0.1117,0.1133,0.1689}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{8,12,6,11}' } {'{0.0489,0.0861,0.1006,0.1078}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{13,17,8,10}' } {'{0.0772,0.1111,0.0811,0.1056}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{5,8,4,6}' } {'{0.0311,0.0483,0.025,0.0622}' } NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {'{12,11,11,9}' } {'{0.0761,0.0717,0.1039,0.1339}'} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0
F = @(c)cellfun(@(t) sscanf(strrep(t,'{',''),'%f,'), c,'uni',0);
T = convertvars(T,{'flows','occupancy'}, F) % convert text to numeric
T = 25866×15 table
fk_pems_id postmile unixtime flows occupancy Var6 Var7 Var8 Var9 Var10 Var11 Var12 Var13 Var14 Var15 __________ ________ __________ ____________ ____________ ____ ____ ____ ___________ _____ _____ _____ ______ __________ ______ 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {'#VALUE!'} NaN NaN NaN 1.0341 0.00064256 2.3132 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN 30 NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0 4.0004e+05 26 1.2025e+09 {4×1 double} {4×1 double} NaN NaN NaN {0×0 char } NaN NaN NaN NaN 0 0
A = @(x,y) sum(x.*y); % "average product"
V = rowfun(A, T, 'InputVariables',{'flows','occupancy'}, 'ExtractCellContents',true, 'OutputFormat','uniform')
V = 25866×1
7.7504 3.8865 5.9678 2.8858 2.8858 6.3061 2.5652 5.4374 1.9727 2.5884

更多回答（1 个）

Shubham
Shubham 2023-3-10
Hi Laxmi,
Here's a sample code in MATLAB that should achieve what you're looking for:
% Define the data as arrays
flows = {[6,18,17,14]; [12,14,12,5]; [16,11,13,12]};
occupancy = {[0.0383,0.13,0.1794,0.1522]; [0.0717,0.0978,0.1117,0.0633]; [0.1006,0.08,0.0978,0.1839]};
% Convert the cell arrays to matrices
flows_mat = cell2mat(flows);
occupancy_mat = cell2mat(occupancy);
% Calculate the average product using element-wise multiplication and sum
averageproduct = sum(flows_mat .* occupancy_mat, 2) / size(flows_mat, 2);
% Display the result
disp(averageproduct);
This code should work for any number of rows in your data. The code first converts the cell arrays to matrices using the cell2mat function, then calculates the average product using element-wise multiplication and the sum function. Finally, it divides the sum by the number of columns in the data to get the average.
Hope this helps!
  3 个评论
显示 1更早的评论
Shubham
Shubham 2023-3-11
Yes, you can modify the previous code to read data from a CSV file using the readtable function. Here is an updated version of the code:
% read data from CSV file
data = readtable('filename.csv');
% extract flows and occupancy from the table
flows = data{:, 'D'};
occupancy = data{:, 'E'};
% calculate the average product
averageproduct = mean(flows .* occupancy);
In this code, you should replace 'filename.csv' with the actual name of your CSV file. The readtable function creates a table from the CSV file, and then the {:,'D'} and {:,'E'} indexing expressions extract the data from the 'D' and 'E' columns, respectively. The rest of the code is the same as before - it calculates the average product using element-wise multiplication and the mean function.
Laxmi Bhatta
Laxmi Bhatta 2023-3-11
>> data=readtable('C:\Users\z5266795\pems_rawdata_NB.csv');
flows=data{:,4};
occupancy=data{:,5};
averageproduct = mean(flows .* occupancy, 1);
speed = averageproduct*3600/1609.34;
Time = data{:,3};
Space= data{:,2};
y = Space;
x = Time;
[X,Y] = meshgrid(x,y);
Z = speed
figure;
heatmap(X,Y,Z,'Colormap',jet);
xlabel('Time (unix)');
ylabel('Postmile)');
title('Vehicle Speed Heatmap');
colorbar;
Undefined operator '.*' for input arguments of type 'cell'. I got this error while coding
I have also uploaded the csv data
Afetr slightly modifying the data
again have got the error
data=readtable('C:\Users\z5266795\pems_rawdata_NB.csv');
flows=data{:,4};
occupancy=data{:,5};
flows_mat = cell2mat(flows);
occupancy_mat = cell2mat(occupancy);
averageproduct = mean(flows_mat .* occupancy_mat, 2);
speed = averageproduct*3600/1609.34;
Time = data{:,3};
Space= data{:,2};
y = Space;
x = Time;
[X,Y] = meshgrid(x,y);
Z = speed
figure;
heatmap(X,Y,Z,'Colormap',jet);
xlabel('Time (unix)');
ylabel('Postmile)');
title('Vehicle Speed Heatmap');
colorbar;
Error using cat
Dimensions of arrays being concatenated are not consistent.
Error in cell2mat (line 83)
m{n} = cat(1,c{:,n});

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