Cannot Load Counter Name Data Because an Invalid Index -Exception

Access Windows Performance Counters in a locale independent way

The solution is simple: the only problem is to put together all the infos.

First of all, open regedit and go to the following key:

HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Perflib

You will find entries named with three digits (e.g. 009, 010, ...). These three digits are a language id: 009 is English, 010 is Italian, and so on.

In each of these entries you will find a key named Counter. Open it (double click) and copy the content of your preferred language in a text editor. You will have something similar to the following:

1
1847
2
System
4
Memory
6
% Processor Time
10
File Read Operations/sec
12
File Write Operations/sec
14
File Control Operations/sec
16
...

As you can see, there is a number below each label: that is index to use. For example, the index of % Processor Time is 10.

If you have a composite expression (e.g., \Processore(_Total)\% Tempo processore), you have to use \238(_Total)\6 (I used the Italian labels).

In Zabbix, the expression to use for monitoring the average CPU utilization over the last 15 minutes is:

perf_counter[\238(_Total)\6, 900]

I hope to have said all: if there is something not clear, please, leave a comment.

Index to scalar variable assignment in Python is not clear for a float error

def getVWAP(data):
    # if data is a pandas dataframe, just use data['o'].values instead
    open = numpy.array(data['o'])
    low = numpy.array(data['l'])
    high = numpy.array(data['h'])
    close = numpy.array(data['c'])
    volume = numpy.array(data['v'])

    # it's better to use logging.debug for debug output
    print(len(open), len(low), len(high), len(close), len(volume))

    # default dtype is float, but you can be more explicit
    typicalPrice = np.zeros(len(open), dtype=float)
    # another way to improve this is to use zeros_like,
    # which will generalize beyond 1D arrays
    VP = np.zeros_like(open)
    # but actually, we don't need to initialize these arrays at all
    # because we calculate them directly (see below)    

    # numpy arrays can be added/subtracted/... directly
    # it is actually quite a bit faster
    typicalPrice = (open + high + low)/3
    VP = volume * typicalPrice
    totalVolume = np.cumsum(volume)
    totalVP = np.cumsum(VP)
    VWAP = totalVP/totalVolume
    
    # this line is different. A typo?
    VWAP[0] = typicalPrice[0]

Why is my future builder still not working in spite of await in flutter?

In your FutureBuilder you have the condition wrong, (snapshot.hasData != null) is always true, it should be like this:

FutureBuilder(
                future: widgetLoadingFunctions(_selectedIndex),
                builder: (BuildContext context, AsyncSnapshot snapshot) {
                  if (snapshot.hasData) {
                    return widgetOptions(_selectedIndex);
                  } else
                    return CircularProgressIndicator();
                })),

or like this:

FutureBuilder(
                future: widgetLoadingFunctions(_selectedIndex),
                builder: (BuildContext context, AsyncSnapshot snapshot) {
                  if (snapshot.data != null) {
                    return widgetOptions(_selectedIndex);
                  } else
                    return CircularProgressIndicator();
                })),

How to use tensor.item() ? IndexError: invalid index of a 0-dim tensor. Use tensor.item() to convert a 0-dim tensor to a Python number

What this error message says is that you're trying to index into an array which has just one item in it. For example,

In [10]: aten = torch.tensor(2)   

In [11]: aten  
Out[11]: tensor(2)

In [12]: aten[0]
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-12-5c40f6ab046a> in <module>
----> 1 aten[0]

IndexError: invalid index of a 0-dim tensor.  Use tensor.item() to convert a 0-dim 
tensor to a Python number

In the above case, aten is a tensor with just a single number in it. So, using an index (or more) to retrieve that number throws the IndexError.

The correct way to extract the number(item) out of the tensor is to use tensor.item(), here aten.item() as in:

In [14]: aten.item()
Out[14]: 2

invalid redeclaration in auto code generate NSManagedObject Subclass Swift 3

In Xcode 8.1, before using the auto code generator, you must select the entity in your data model:

Then go to the Data Model Inspector tab:

Under "Codegen" select "Manual/Node"

After that you could create a NSManagedObject subclass without errors.

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Alternatively, if you have already used 'Class Definition', you can go into your existing .xcdatamodeld file and set all current entities to 'Manual/None' under Codegen. Make sure to save your project (File -> Save), delete your existing Derived Data, clean the project, and then build. Resolved it for me without having to re-make my whole model.

C++: Write to/read from invalid/out of bound array index?

Your system just happens to not be using the memory that just happens to be 20 * sizeof(int) bytes further from the address of your array. (From the beginning of it.) Or the memory belongs to your process and therefore you can mess with it and either break something for yourself or just by lucky coincidence break nothing.

Bottom line, don't do that :)

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