I don't think that you can vectorize this. But an acceleration is possible:
lastrow = max(find(dataset.price(filteredrows)==price_x & ...
strcmp(dataset.ordertype(filteredrows), 'buy')));
% Replacement:
lastrow = find(dataset.price(filteredrows)==price_x & ...
strcmp(dataset.ordertype(filteredrows), 'buy')), 1, 'last');
And:
dataset.last_buy_quantity_price_x = zeros(height(dataset), 1);
...
if ~isempty(lastrow)
dataset.last_buy_quantity_price_x(row) = dataset.quantity(lastrow);
end
end
Compare the ordertype with 'buy' once only before the loop:
isBuy = strcmp(dataset.ordertype, 'buy');
Then inside the loop:
lastrow = find(dataset.price(filteredrows)==price_x & isBux(filteredrows), 1, 'last');
The same works with "dataset.price == price_x" also.
What about removing all or(dataset.price ~= price_x, ~strcmp(dataset.ordertype, 'buy') before the loop? This might reduce the data set massively:
price_x = 1.1;
m = or(dataset.price ~= price_x, ...
~strcmp(dataset.ordertype, 'buy'));
name = dataset.assetname(m);
time = dataset.time(m);
price = dataset.price(m);
quantity = dataset.quantity(m);
last_buy = zeros(numel(name),1);
for row = 1:numel(name)
filtered = strcmp(name(row), name) & (time(row) >= time);
lastrow = find(filtered, 1, 'last');
if ~isempty(lastrow)
last_buy(row) = quantity(lastrow);
end
end
dataset.last_buy_quantity_price_x = zeros(height(dataset), 1);
dataset.last_buy_quantity_price_x(m) = last_buy;
This saves teh time for addressing the struct fields also and I think the simpler the code looks like, the easier is it to maintain.
