## Manipulation of expressions: Iterate over the deeper values ​​in a nested association

Is it possible to iterate over the values ​​of the deepest layer of keys in a nested association? For example:

``````assoc = <| "a"->0, "b" -> <| "c"->"one", "d" -> 2, "e" -> 3 |>, "f" -> 4 |>
``````

Would it be possible to iterate over the values ​​of the deepest level in this example? `{0, "one", 2,3,4}`? Or is it possible to iterate over the deeper level of the keys so that you can test the type for the value of each key?

## Google sheets – Iterate through the range, copy the value of the cell to the single cell reference

I have a sheet where I would like to track inventory transfers and update the inventory master sheet accordingly. I'm a little new in this. I have a range that consists of a column of new values ​​(calculated with formulas) and a column with cell references where I would like to copy those values ​​(on another sheet).

Currently, my code only works for the first row, but it does not repeat itself in the range and I can not understand why. I thought that using an "index" variable would correctly reassign the values ​​for sourceCell and sourceRef, but maybe it's redundant?

Any help would be appreciated.

``````copypaste () {function
var sheet1 = ss.getSheetByName ("FMGXfers");
var sheet2 = ss.getSheetByName ("FMGInventory");
var numRows = sheet1.getRange (& # 39; R1 & # 39;). getDisplayValue ();

index var = 3
var sourceCell = & # 39; T & # 39; + index;
var sourceRef = & # 39; U & # 39; + index;
var targetCell = sheet1.getRange (sourceRef) .getDisplayValue ();
var sourceValue = sheet1.getRange (sourceCell) .getValues ​​();

for (var i = 1; i <numRows; i ++) {
sheet2.getRange (targetCell) .setValues ​​(sourceValue);
index var = index ++;
var sourceCell = & # 39; T & # 39; + index;
var sourceRef = & # 39; U & # 39; + index;
}
}
``````

## complexity theory – NL – iterate all the edges of a graph in the registry space

There is absolutely no problem to iterate over all the edges in a graph in the log space (even in the deterministic log space!). The details depend on how the graphic is encoded. For example, if the graph is coded as an adjacency matrix, then it can simply go over all the pairs of vertices.

However, this does not give an NL algorithm to click. The problem is that you need to iterate $$k$$-tuples of vertices, not constant. $$k$$. This is something you can not do in the registration space.

NP is sometimes described in terms of witnesses. However, the "official" definitions are using non-deterministic Turing machines, which can have more than one correct movement at any given time. The class of languages ​​accepted by non-deterministic Turing machines do not coincide with the class of languages ​​to which a polynomial-sized token is assigned and can be verified in polynomial time. Unfortunately, there is no such alternative description for non-deterministic record space Turing machines.

## react – How to iterate a URL in Javascript

In the case that it is a text file, it must be taken into account that, within a require (url), someone has some idea?

## python – Iterate over a matrix and save in a dictatorship

Since this matrix:

``````array ([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]], dtype = uint8)
``````

I'm wanting to do it to count values ​​on each line and then save them by line.
The following code is doing the general sum. I would like to have the account by line.

``````def count (image):
array = np.array (image)
training[[ array == 0 ]]= 1
training[[ array == 255 ]]= 0
for row in matrix:
unique, counts = np.unique (array[row,] , return_counts = True)
d = dict (zip (unique, counts))
return new
``````

The result:

``````{0: 234710, 1: 515}
``````

## Tensioning objects are only iterable when avid execution is enabled. To iterate over this tensor use tf.map_fn

I created a custom loss function and tried to execute it, which caused me an error.

mse = Custom_loss (y_real, y_pred, df_for_loss, price)

def Custom_loss (y_true, y_pred, df_for_loss, price, sample_weight = None, multioutput = & # 39; uniform_average & # 39;):

``````df_for_loss['y_pred']= y_pred
df_for_loss['agg_closing_stock'] = np.where (df_for_loss.agg_closing_stock> 0, (price / 2) * df_for_loss.agg_closing_stock, df_for_loss.agg_closing_stock)

df_for_loss['agg_closing_stock'] = np.where (df_for_loss.agg_closing_stock == 0, price * df_for_loss.y_pred, df_for_loss.agg_closing_stock)
df_for_loss.agg_closing_stock = df_for_loss.agg_closing_stock.astype (& # 39; float32 & # 39 ;, raise_on_error = False)
y_pred = y_pred.astype (& # 39; float32 & # 39 ;, raise_on_error = False)
data = tf.convert_to_tensor (df_for_loss.agg_closing_stock)
y_pred = K.tf.math.multiply (y_pred, data)

output_errors = np.average ((y_true - y_pred) ** 2, axis = 0,
weights = sample_weight)
if it is an instance (multioutput, string_types):
If multioutput == & # 39; raw_values ​​& # 39;
return output_errors
elif multioutput == & # 39; uniform_average & # 39 ;:
# pass None as weights to np.average: uniform average
multioutput = None

returns np.average (output_errors, weights = multioutput)
``````

## python 3.x – Iterate through groups of rows with different indexed values

The data looks like this:

Data = {& # 39; group_id: [‘1′,’1′,’1′,’1′,’2′,’2′,’2’],
& # 39; Gravity & # 39; [4,2,7,4,8,9,3,5]}

I need:

1) Take the first row of the Severity Code of each group
2) Obtain the absolute value of all the rows (difference) of the identified severity code of each group (from # 1). Example: Group severity code 1 (4) … first row diff = 0; second row diff = 2; third row diff = 3; The same for group 2.
3) In each group, find the closest neighbor of each source, up to the severity of the first row.

I have identified the first row and indexed the severity code. When iterating, the code only uses the last indexed severity code to calculate the difference.

``````df = pd.DataFrame (Data)
first_row = b.groupby (['group_id']).First()
for the row in first1.itertuples (index = True, name = & # 39; Pandas & # 39;):
value = getattr (row, & # 39; Severity & # 39;)
df['dif'] = (df['Severity'] - value) .abs ()
``````

I hope the output is in a Dataframe with a column & # 39; dif & # 39; added I can extract nearest neighbors in each group for each source where True. Repeat the process: extract the rows where True and pass the False to find additional rows with a new severity of the first row. Repeat again until there are no rows, or all rows are False.

## c # – How to iterate efficiently in the data list and search data in another datatable?

I have a list that contains 25000 data and I am iterating in all the data and in each iteration, I am looking for data in another data table. All my routine is taking a long time to finish.

``````PrivateComid UpdateCommentFirst (string strCommentPath, string TickerName)
{
counter of int = 0;
bool QcViewAllFileExist = false;
bool QcCommentFileExist = false;
bool AllowUpdate = false;
string savepath = Convert.ToString (ConfigurationManager.AppSettings["OutputPath"]) .Trim () + TickerName + "\" + TickerName + "_QC-ViewwAll.xml";
DataSet QCCommentstmp = new DataSet ();
DataSet QCViewAlltmp = new DataSet ();

if (File.Exists (strCommentPath))
{
QcCommentFileExist = true;
}

if (File.Exists (savepath))
{
QcViewAllFileExist = true;
}

if (QcCommentFileExist && QcViewAllFileExist)
{
{
{
AllowUpdate = true;
}
}

if (AllowUpdate)
{

.Select (row => new clsCommentPopup
{
// BrokerFor, Formula, LineItem, Section, PeriodCollection
bolFollowUP = (row.Field("FollowUP")) == null? false: Convert.ToBoolean ((row.Field("Follow"))),
bolThisPeriod = (row.Field("ThisPeriod")) == null? false: Convert.ToBoolean ((row.Field("This period"))),
Formula = (row.("Formula")) == null? string.Empty: (row.Field("Formula")),
ModelValue = (row.Field("ModelValue")) == null? string.Empty: (row.Field("ModelValue")),
ExternalComment = (row.Field("ExternalComment")) == null? string.Empty: (row.Field("ExternalComment")),
InternalComment = (row.Field("InternalComment")) == null? string.Empty: (row.Field("InternalComment")),
strEndPeriod = (row.Field("EndPeriod")) == null? string.Empty: (row.Field("EndPeriod")),
strStartPeriod = (row.Field("StartPeriod")) == null? string.Empty: (row.Field("StartPeriod")),
PeriodType = (row.Field("PeriodType")) == null? string.Empty: (row.Field("PeriodType")),
SectionFor = (row.Field("Section")) == null? string.Empty: (row.Field("Section")),
LiFor = (row.Field("LineItem")) == null? string.Empty: (row.Field("Elemento en línea")),
QcPeriodFor = (row.Field("QcPeriod")) == null? string.Empty: (row.Field("QcPeriod")),
BrokerFor = (row.Field("BrokerFor")) == null? string.Empty: (row.Field("BrokerFor")),
PeriodCollection = (row.Field("PeriodCollection")) == null? string.Empty: (row.Field("PeriodCollection")),
boolIgnoreValue = (row.Field("IgnoreValue")) == null? false: Convert.ToBoolean ((row.Field("IgnoreValue"))),
IgnoreData = (! QCCommentstmp.Tables[0].Columns.Contains ("IgnoreData")? string.Empty: (row.Field("IgnoreData") == null? string.Empty: row.Field("IgnoreData")))
}).To list();

if (QCCommentlist! = null)
{
foreach (comment var in QCCommentlist)
{
string section = comment.SectionFor;
string li = comment.LiFor;
string broker = comment.BrokerFor;
string period = comment.PeriodCollection;
string strQCPeriodValue = "";

if (comment.boolIgnoreValue && period.Trim ()! = "")
{
var QcViewColumnName = QCViewAlltmp.Tables[0]. Columns.Cast() .AsParalelo ()
.Where (x => x.ColumnName.Contains (period))
.Select (x => new {x.ColumnName}). FirstOrDefault ();

if (QcViewColumnName! = null)
{
period = QcViewColumnName.ColumnName;

if (period.Trim ()! = "")
{
var datarow = QCViewAlltmp.Tables[0].AsEnumerable (). AsParallel ()
.Where (row => row .field("GroupKey"). Split (& # 39; ~ & # 39;)[0].ToUpper () == section.ToUpper ()
&& row.Field("GroupKey"). Split (& # 39; ~ & # 39;)[1].ToUpper () == li.ToUpper ()
&& row.Field("Section") .ToUpper () == broker.ToUpper ());

if (datarow! = null && datarow.Count ()> 0)
{
strQCPeriodValue = (datarow.FirstOrDefault ()[period] ! = null? datarow.FirstOrDefault ()[period].ToString (): string.Empty);
if (strQCPeriodValue.Trim ()! = string.Empty)
{
comment.IgnoreData = strQCPeriodValue;
counter ++;
}
}
}
}
}
}
}

SerializeQcComment (QCCommentlist);
toolTip1.Hide (this);
}
}
}
``````

Yes ignored field is there in the data set table QCCommentstmp `QCCommentstmp.Tables[0].Columns.Contains ("IgnoreData")` then deserialize the data from the QCCommentstmp table to list them `List QCCommentlist`

iterate in the QCCommentlist data using for looping and find data in QCViewAlltmp.Tables[0] data table for each iteration

when QCCommentlist has 25000 data then I'm iterating through all the 25000 data and finding data in another data table. If data is found, I am updating the data in the list. This process is getting very slow and the code is taking a long time to complete the entire iteration and data search in the data table.

please check my code and tell me how to restructure my code, as a result, there will be an improvement in the speed of code execution.

If my approach is incorrect, guide me with the correct approach and also tell me the relevant code that I can use in my previous code. As a result, my routine will take a minimum time to complete if I repeat more than 25,000 data. Searching for suggestions and better code to achieve the same task.

## javascript: Iterate the HTML table to highlight the differences where the cells have multiple comparison elements

I want to highlight the differences between the first row of a table and all the other rows in the column.

I have discovered how to achieve this when each cell in the table only has 1 element / comparison. But I would like to extend this to multiple comparisons per cell separated by "," s.

Here is the code for the only element per cell. https://jsfiddle.net/t19Lqbkn/
using the following code:

``````    var table = document.getElementById ("mytab1");
for (var i = 1, row; row = table.rows[i]; i ++) {
var matc = table.rows[1]
for (var j = 0, col; col = row.cells[j]; j ++) {
if (col.innerHTML! == matc.cells[j].innerHTML) {col.innerHTML = ""+ col.innerHTML +"";}

}
}
``````

And here is a table with several elements per cell.
https://jsfiddle.net/6c7s9mky/

As you can see in the second link. The first column of the second row, only the element "Eva" should be red, and in the last row of the first column there should be no red text.

## java – Retrieve sum data from the database or iterate at run time

I have an object (Shopping cart) that has a list of CartItems, which contains the related productstrong text and the amount purchased.

``````Public class ShoppingCart extends BaseEntity {

Private list cartItems = new ArrayList <> ();

@DateTimeFormat (pattern = "dd / MM / yyyy hh: MM: ss")
private LocalDateTime dateTime;

@Enumerated
private PaymentMethod paymentMethod = PaymentMethod.CASH;

public class CartItem extends BaseEntity {

@ManyToOne
Private product of the product;

@ManyToOne (fetch = FetchType.LAZY)
@JoinColumn
Private ShoppingCart ShoppingCart;

Public class product extends BaseEntity {

@Not empty
name of the private chain;

Private double price;

int private amount;
``````

I have a view that summarizes all the shopping carts, and I do not know if I should save that amount within the ShoppingCart entity, or iterate to find the sum.
Here is the code, right now I am iterating.

``````@GetMapping ("/")
Public string getProduct (@ModelAttribute ("reportDto") ReportDto reportDto, Model model) {

double total = 0, cash = 0, credit = 0, debit = 0;
int quantity
List results
if (reportDto.getBeginDate () == null || reportDto.getEndDate () == null) {
results = shoppingCartService.findAll ();
} else {
results = shoppingCartService.findByDateTimeBetween (reportDto.getBeginDate (), reportDto.getEndDate ());
}
total = results. current ()
.mapToDouble (shoppingCart -> shoppingCart.getCartItems (). stream ()
.mapToDouble (cartItem -> cartItem.getProduct (). getPrice () * cartItem.getQuantity ()). sum ())
.sum();
quantity = results.stream (). mapToInt (
shoppingCart -> shoppingCart.getCartItems (). stream (). mapToInt (cartItem -> cartItem.getQuantity ()). sum ())
.sum();

cash = results.stream (). filter (shoppingCart -> shoppingCart.getPaymentMethod (). isCash ())
.mapToDouble (shoppingCart -> shoppingCart.getCartItems (). stream ()
.mapToDouble (cartItem -> cartItem.getProduct (). getPrice () * cartItem.getQuantity ()). sum ())
.sum();

credit = results.stream (). filter (shoppingCart -> shoppingCart.getPaymentMethod (). isCredit ())
.mapToDouble (shoppingCart -> shoppingCart.getCartItems (). stream ()
.mapToDouble (cartItem -> cartItem.getProduct (). getPrice () * cartItem.getQuantity ()). sum ())
.sum();

debit = results.stream (). filter (shoppingCart -> shoppingCart.getPaymentMethod (). isDebit ())
.mapToDouble (shoppingCart -> shoppingCart.getCartItems (). stream ()
.mapToDouble (cartItem -> cartItem.getProduct (). getPrice () * cartItem.getQuantity ()). sum ())
.sum();