aggregate | ODK Aggregate is a Java server | SQL Database library
kandi X-RAY | aggregate Summary
kandi X-RAY | aggregate Summary
ODK Aggregate provides a ready-to-deploy server and database to:. ODK Aggregate can be deployed on an Apache Tomcat server, or any servlet 2.5-compatible (or higher) web container, backed with a PostgreSQL or a MySQL database server.
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Top functions reviewed by kandi - BETA
- Processes a multi - part form file
- Reads the next line from the input stream
- Sets the standard site access configuration
- Advances an email address
- Assert that the database is defined in the database
- Update a relation
- Asserts that a relation exists in the database
- Update a relation
- Assert that a relation exists in the database
- Update a relation
- Generate the KML
- Handle an HTTP GET request
- Handles a GET request
- Generate a JSON file
- Generate CSV file
- Returns a JSON object that can be used to create the user
- Gets the datastore
- Handle a click event
- Gets users
- Create the map widget
- Helper method to do the actual parsing
- Performs an enketo request
- Handles an HTTP GET request
- Handles a POST request
- Handles GET request
- Handle a POST request
- Create a kml from a filter
- Handle a GET request
aggregate Key Features
aggregate Examples and Code Snippets
Lines of Code : 103License : Non-SPDX (Apache License 2.0)
Copydef _ragged_segment_aggregate(unsorted_segment_op,
data,
segment_ids,
num_segments,
separator=None,
def _AggregatedGrads(grads,
op,
gradient_uid,
loop_state,
aggregation_method=None):
"""Get the aggregated gradients for op.
Args:
grads: The map of memoized def aggregate_gradients_using_hierarchical_copy(avail_devices, replica_grads):
"""Aggregate gradients using hierarchical copies.
Args:
avail_devices: available GPU devices.
replica_grads: List of lists of (gradient, variable) tuples. The Community Discussions
Trending Discussions on aggregate
QUESTION
Background
I have a complex nested JSON object, which I am trying to unpack into a pandas df in a very specific way.
JSON Object
this is an extract, containing randomized data of the JSON object, which shows examples of the hierarchy (inc. children) for 1x family (i.e. 'Falconer Family'), however there is 100s of them in total and this extract just has 1x family, however the full JSON object has multiple -
ANSWER
Answered 2022-Feb-16 at 06:41I think this gets you pretty close; might just need to adjust the various name columns and drop the extra data (I kept the grouping column).
The main idea is to recursively use pd.json_normalize with pd.concat for all availalable children levels.
EDIT: Put everything into a single function and added section to collapse the name columns like the expected output.
QUESTION
In following program, struct C has two constructors : one from std::initializer_list and the other from std::initializer_list. Then an object of the struct is created with C{{1}}:
ANSWER
Answered 2022-Feb-12 at 23:30The wording could be clearer (which is unsurprising), but GCC and MSVC are correct here: the relevant rule ([over.ics.list]/7) checks only that
overload resolution […] chooses a single best constructor […] to perform the initialization of an object of type
Xfrom the argument initializer list
so the fact that the initialization of B from {1} would be ill-formed is irrelevant.
There are several such places where implicit conversion sequences are more liberal than actual initialization, causing certain cases to be ambiguous even though some of the possibilities wouldn’t actually work. If the programmer was confused and thought one of those near misses was actually a better match, it’s a feature that the ambiguity is reported.
QUESTION
My query follows this structure:
...ANSWER
Answered 2022-Jan-13 at 13:10Looks like it is the "t2.count" that causes the issue.
On dbfiddle I can reproduce the issue ONLY when there is no column named "count" in the table2.
In other words, the error occurs only when table 2 defined like that:
QUESTION
I have a dataframe df:
ANSWER
Answered 2022-Jan-03 at 09:24You could use apply with a custom function as follows:
QUESTION
Is there a way to aggregate (e.g., sum, mean) intervals along a pandas series? I did it the long and non-elegant way but I feel like there has to be a built-in way to do this since people do a lot of time series analysis with pandas (this isn't time series btw). Maybe with use of the pd.Interval object?
ANSWER
Answered 2021-Dec-16 at 20:00You are looking for groupby on pd.cut:
QUESTION
I have an RMarkdown document which summarizes how many records (rows) have various attributes by group. I would like to be able to manipulate which records are included in the table by filtering before the summarizing. I've created a minimal but similar mockup below.
What I would like is an interactive checkbox that would effectively "comment or uncomment" out the line
...ANSWER
Answered 2021-Dec-15 at 22:58Try adding a JS aggregate function callback, instead of using the built-in aggregation:
QUESTION
The code as follows
...ANSWER
Answered 2021-Dec-11 at 11:18Neither definition of the notion of aggregate in C++ Standards refers to the destructor.
For example the definition of an aggregate in C++ 20 (9.4.2 Aggregates) sounds the following way
1 An aggregate is an array or a class (Clause 11) with
(1.1) — no user-declared or inherited constructors (11.4.5),
(1.2) — no private or protected direct non-static data members (11.9),
(1.3) — no virtual functions (11.7.3), and
(1.4) — no virtual, private, or protected base classes (11.7.2).
If to execute this statement in MS VS 2019
QUESTION
I've installed Windows 10 21H2 on both my desktop (AMD 5950X system with RTX3080) and my laptop (Dell XPS 9560 with i7-7700HQ and GTX1050) following the instructions on https://docs.nvidia.com/cuda/wsl-user-guide/index.html:
- Install CUDA-capable driver in Windows
- Update WSL2 kernel in PowerShell:
wsl --update - Install CUDA toolkit in Ubuntu 20.04 in WSL2 (Note that you don't install a CUDA driver in WSL2, the instructions explicitly tell that the CUDA driver should not be installed.):
ANSWER
Answered 2021-Nov-18 at 19:20Turns out that Windows 10 Update Assistant incorrectly reported it upgraded my OS to 21H2 on my laptop.
Checking Windows version by running winver reports that my OS is still 21H1.
Of course CUDA in WSL2 will not work in Windows 10 without 21H2.
After successfully installing 21H2 I can confirm CUDA works with WSL2 even for laptops with Optimus NVIDIA cards.
QUESTION
I have a df:
ANSWER
Answered 2021-Nov-16 at 08:55This is what you need:
QUESTION
std::array is ... (quoting from cppreference):
This container is an aggregate type with the same semantics as a struct holding a C-style array
T[N]as its only non-static data member.
Does that imply that the address of an array is always the same as the address of its first element, i.e. data()?
ANSWER
Answered 2021-Oct-08 at 19:23Technically, a std::array object may have padding at the beginning, in which case the data will be at a higher address than the std::array object. Only for standard-layout classes is there a guarantee that the object itself has the same address as the first non-static data member.
There is no guarantee in the standard that std::array is standard-layout, even if T is int or something like that. All reasonable implementations of std::array will have a single non-static data member of type T[N], no virtual functions, and at most a single inheritance chain with no virtual base classes, which would mean they would be standard-layout as long as T itself is standard-layout. Plus, even if T is not standard-layout, the compiler is not likely to insert padding at the beginning of the std::array object.
So, while an assumption that a std::array object has the same address as the first T object it contains is not portable, it is basically guaranteed in practice. And you can add a static_assert(sizeof(std::array) == sizeof(T[N])); just to be sure that, if someone ever tries to build your code on an exotic implementation where it isn't the case, they'll know it's not supported.
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Install aggregate
These instructions are for IntelliJ IDEA Community edition, which is the (free) Java IDE we use for all the ODK toolsuite, but you don't really need any specific IDE to work with this codebase. Any Java IDE will support any of the steps we will be describing.
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