omega | A Scala Implementation of the Omega Test | Functional Testing library
kandi X-RAY | omega Summary
kandi X-RAY | omega Summary
A Omega test implementation in Scala. Omega test is an algorithm that can determine whether exists integer solutions of a set of integer constraints[1]. For examples, given constraints. the Omega test will figure out it is satisfiable by some integers of x and y. the Omega test determines that there is no assignments of x and y can make them satisfied.
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Trending Discussions on omega
QUESTION
I'm trying to write a light curve simulation for transit, however, when use more than one value for the inclination ('ibound' in the code below), there will be some weird horizontal line in the final figure, but it will not happen if only one value is used each time, e.g.ibound=[80,82] is not ok, but ibound=[80] or ibound=[82] gives the correct result.
...ANSWER
Answered 2022-Apr-08 at 17:46Its an artifact of the plt.plot()
function. As you have put all the results into the same list the plotter will attempt to connect all the data points with a single continuous line. So the end data point of the first pass will get joined to the first point of the second pass.
You can see this clearly if you change the plot parameters,
plt.plot(xaxis, yaxis, 'or', linewidth=1)
Which gives,
As you can see there has been no attempt by the plotter to connect the data points with a continuous line & hence no additional horizontal line.
QUESTION
Beginning with two pandas dataframes of different shapes, what is the fastest way to select all rows in one dataframe that do not exist in the other (or drop all rows in one dataframe that already exist in the other)? And are the fastest methods different for string-valued columns vs. numeric columns? Operation should be roughly equivalent to the code below
...ANSWER
Answered 2022-Feb-26 at 13:15Beginning with 2 dataframes:
QUESTION
I've mostly worked with MATLAB, and I am converting some of my code that I have written into Python. I am running into an issue where I have a boolean mask that I am calling Omega, and when I apply the mask to different m by n matrices that I call X and M I get different objects. Here is my code
...ANSWER
Answered 2022-Mar-21 at 22:12M
is a np.matrix
, which are always 2-D (so it has two dimensions). As the error message indicates, you can only use a 0- or 1-D array when assigning to an array masked with a boolean mask (which is what you're doing).
Instead, convert M
to an array first (which, as @hpaulj pointed out, is better than using asarray
+ ravel
)
QUESTION
I'm facing a mathematical/programming problem which I don't really understand. In the following α,β,θc
are given parameters, ϕ
is the variable. I have to solve the equation Cp=0
, where:
and:
The solutions that I have computed are:
Coding the above solutions with Python/Numpy, I find that:
- If
β=0
, then both solutions are correct:Cp(ϕ1)=Cp(ϕ2)=0
. - However, if
β!=0
thenCp(ϕ1)!=0
(which is wrong) andCp(ϕ2)=0
. Why? I checked again and again the signs and terms on my coded expressions, they seem fine to me...
Here is the code:
...ANSWER
Answered 2022-Mar-21 at 10:53Seems like your analytical solution has a mistake.
I rewrote the target function in form
QUESTION
ANSWER
Answered 2022-Mar-20 at 12:50Your fitted curve will look like this
QUESTION
Dear stackoverflow community,
I am currently trying to create a custom layer that transforms every value of an input with integers into a vector with length "omega". Currently I combine the tensorflow functions tf.map_fn with the function tf.range to create a ragged tensor and fill that tensor up with zeros afterwards.
The Custom layer is defined as follows:
...ANSWER
Answered 2022-Mar-09 at 14:41Try using tf.while_loop
and tf.tensor_scatter_nd_update
:
QUESTION
Here I am using two threads. One thread create a dataframe and pass it to another thread through queue. Another thread collect the dataframe from the queue and append it to a csv file. Here when I run the code ,sometimes I got wrongvalues in entire dataframe. shoudl i have to do any corrections in the code ?
Here is my code:
...ANSWER
Answered 2022-Mar-15 at 08:22After having played around with the code a bit more, I think the issue is not the increasing queue size, but the global df, which gets reused by getpoints all the time.
Try replacing q.put(df)
by q.put(df.copy())
, which stores a copy of the dataframe in the queue, instead of the "global" one, which might get modified when it is received.
QUESTION
I have a TABLE sec.sec_secret_tab in the SEC schema
OWNER SERVICE_NAME SECRET ALPHA service_1 A1 ALPHA service_2 A2 BETA service_1 B1 BETA service_2 B2and this function:
...ANSWER
Answered 2022-Feb-24 at 18:24You can use the UTL_CALL_STACK
package, specifically the OWNER
function:
This function returns the owner name of the unit of the subprogram at the specified dynamic depth.
You want the owner of the calling package, so that's level 2:
QUESTION
After upgrading to android 12, the application is not compiling. It shows
"Manifest merger failed with multiple errors, see logs"
Error showing in Merged manifest:
Merging Errors: Error: android:exported needs to be explicitly specified for . Apps targeting Android 12 and higher are required to specify an explicit value for
android:exported
when the corresponding component has an intent filter defined. See https://developer.android.com/guide/topics/manifest/activity-element#exported for details. main manifest (this file)
I have set all the activity with android:exported="false"
. But it is still showing this issue.
My manifest file:
...ANSWER
Answered 2021-Aug-04 at 09:18I'm not sure what you're using to code, but in order to set it in Android Studio, open the manifest of your project and under the "activity" section, put android:exported="true"(or false if that is what you prefer). I have attached an example.
QUESTION
I want to populate a huge sparse matrix in python, with the aim to implement Crank-Nicolson numerical method in 2D.
I did it by lopping through all the interior nodes using two nested for loops, but it is extremely slow. Because it is a nested for loop with matrices, I thought of Numba, but it doesn't work with sparse matrices. I cannot convert the matrix to a dense format before passing it as an argument to a numba-jitted function, because of memory issues.
I want to ask what shall I look for in order to make the function populating the A
matrix below quicker?
I tried with scipy.sparse.diags
, but I again ended up using two nested for loops, just as in the (naive) code below.
The problem is that the k
value is computed from i
and j
, and I don't know how to manipulate it without the double for loop.
The code which populates the A
matrix with the double for loop is:
ANSWER
Answered 2022-Feb-23 at 00:15Scipy sparse matrices are pretty slow. This is especially true for the DOK matrices using inefficient hash-tables internally. However, reading/Setting a specific cell of a sparse matrices in a loop is insanely slow (eg. each access takes 10~15 us on my machine). You should avoid that like the plague.
One solution to solve this problem is to create an array of indices and values and write the values to the space matrix in vectorized way. The computation of the indices/values can be optimized with Numba. Here is an example:
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