https://community.wolfram.com RSS Feed for Wolfram Community showing any discussions tagged with Tuning and Debugging sorted by active. https://community.wolfram.com/groups/-/m/t/3772156 **Question:** How do you compute the following limits in a small amount of time? $$\lim_{(a,b,c,d)\to (-\infty,0^{-},0^{+},+\infty)}\frac{\int_{a}^{b}1/x+\int_{c}^{d}1/x}{(b-a)+(d-c)}$$ $$\lim_{(a,b,c,d)\to (-\infty,0^{-},0^{+},+\infty)}\frac{\int_{a}^{b}1/(x^{2/3})+\int_{c}^{d}1/(x^{2/3})}{(b-a)+(d-c)}$$ **Attempt:** I tried the following: Limit[(1/((b - a) + (d - c))) (Integrate[1/x, {x, a, b}] + Integrate[1/x, {x, c, d}]), {a, b, c, d} -> {-Infinity, 0, 0, Infinity}, Direction -> {Reals, -1, 1, Reals}] Limit[(1/((b - a) + (d - c))) (Integrate[1/(x^(2/3)), {x, a, b}] + Integrate[1/(x^(2/3)), {x, c, d}]), {a, b, c, d} -> {-Infinity, 0, 0, Infinity}, Direction -> {Reals, -1, 1, Reals}] However, the computation time of the limits are too long. What can be made to shorten the time? **Motivation:** Let $n\in\mathbb{N}$ and suppose $f:A\subseteq\mathbb{R}^{n}\to\mathbb{R}$ is a function, where $A$ and $f$ are Borel. I want an example of an explicit, unbounded, and continuous $f$ such that the extended mean, w.r.t. the Hausdorff measure in its dimension, is finite. Here is the definition of the extended mean (see Definition 12 [pg. 11-12] of the attatchment): > **Definition (The Extended Mean of $f$)** > > Suppose: > > - $|\cdot|$ is the absolute value > - $\dim_{\mathrm{H}}(\cdot)$ is the Hausdorff dimension > - $\mathcal{H}^{\dim_{\mathrm{H}}(\cdot)}(\cdot)$ is the Hausdorff measure in its dimension on the Borel $\sigma$-algebra > - the integral is defined, w.r.t.\ the Hausdorff measure in its dimension > - $\mathcal{A}(A)$ is the index set > - $\{C_{\gamma}:\gamma\in\mathcal{A}(A)\}$ is a family of sets > - $A$ is a Borel subset of $\mathbb{R}^n$ > - $\mathbb{B}(A)$ is the set of all families of bounded sets with set-theoretic limit $A$ such that $\{C_{\gamma}:\gamma\in\mathcal{A}(A)\}\in\mathbb{B}(A)$, when $\dim_{\mathrm{H}}(C_{\gamma})=\dim_{\mathrm{H}}(A)$ for all $\gamma\in\mathcal{A}(A)$ > > The extended mean of $f:A\subseteq\mathbb{R}^{n}\to\mathbb{R}$ (i.e., > $f$ is Borel), w.r.t.\ the Hausdorff measure in its dimension, is > $M_{f}(A;n)$ when the following is true: > > $$\small{\begin{align}& > \forall(\{A_r:r\in\mathcal{A}(A)\}\in\mathbb{B}(A))\exists!(M_{f}(A;n)\in\mathbb{R})\forall(\epsilon>0)\exists(N\in\mathcal{A}(A))\forall(r\in\mathcal{A}(A))\nonumber\\ > &\left(r\ge > N\Rightarrow\left|\frac{1}{{\mathcal{H}}^{\dim_{\mathrm{H}}(A_r)}(A_r)}\int_{A_r}f\, > d{\mathcal{H}}^{\dim_{\mathrm{H}}(A_r)}-M_{f}(A;n)\right|<\epsilon\right) > \end{align}}$$ > > and when no such $M_{f}(A;n)$ exists, $M_f(A;n)$ is infinite or > undefined. Bharath Krishnan 2026-08-02T04:24:46Z https://community.wolfram.com/groups/-/m/t/3771768 I am using Mathematica 8. I know this is old, but .... It seems that when I have a bug, and Mathematica goes off producing a long string of error messages, the Abort Evaluation (alt-.) does not work. My only alternative is to use Task Manager to kill the kernel. Any comments? David Golber 2026-08-01T19:22:53Z https://community.wolfram.com/groups/-/m/t/3749113 {pM = {xM, yM, 2}, pD = {0, 0, 0}, pN = {0, 2, h}, pA = {2, 0, 0}, relcir = (xM - 1)^2 + (yM - 1)^2 == 1, pQ = {a, b, c}} slq = Solve[{pQ - pA == \[Lambda] (pN - pA)}][[1]] pQ = pQ /. slq AbsoluteTiming@ Reduce[{Norm[pQ - pA] == Norm[pQ - pN] == Norm[pQ - pM] == Norm[pQ - pD], relcir, 0 <= h <= 2, 0 <= \[Lambda] <= 1}, {\[Lambda], h}, {xM, yM}, Reals] How to Speed Up Code for Solving Complex Equations. As shown in the figure below, the code takes nearly 10 minutes to obtain a solution. How can I improve the running efficiency? ![enter image description here][1] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=2026-07-09_095006.png&userId=3746743 David carl 2026-07-09T01:50:36Z https://community.wolfram.com/groups/-/m/t/3741886 While working on internal projects, I often found that want to add extra functionality on top of the existing functions of `TestReport` and `TestCreate`, `TestEvaluate` etc. Recently I made an effort to compile all of these custom functionalities into my own package and publish it for general use on [my own Github account here](https://github.com/SjoerdSmitWolfram/UnitTestFramework). I have tried to make the Github repo reasonably self-explanatory, but I would like to post some of the headline functionality here for everyone's benefit. The main code is found in [UnitTestFramework.wl](https://github.com/SjoerdSmitWolfram/UnitTestFramework/blob/main/UnitTestFramework/Kernel/UnitTestFramework.wl), which I deliberately kept as a single file so that it's easy to load remotely using ``` Get["https://raw.githubusercontent.com/SjoerdSmitWolfram/UnitTestFramework/refs/heads/main/UnitTestFramework/Kernel/UnitTestFramework.wl"] ``` Of course, you can also install the paclet and load it locally. The repository has an [example paclet with a small test suite](https://github.com/SjoerdSmitWolfram/UnitTestFramework/tree/main/Examples) to show broadly how things are expected to be structured. The example paclet also has a WolframScript file that gives can be used and adapted to run your unit tests from the command line so you can easily run them without interrupting your main workflow. # What is UnitTestFramework and why should you use it? UnitTestFramework is a reusable test runner for paclet-style Wolfram Language projects. It is built around the standard MUnit workflow, but adds a more practical layer on top for people who need to run larger or more structured test suites. The main idea is simple: keep using familiar test constructs such as `TestCreate`, but gain better control over how tests are discovered, configured, tagged, skipped, summarized, and run from automation. This matters because once a test suite grows beyond a handful of files, you usually want more than a raw TestReport. You want a way to separate quick local runs from full runs, mark known failures without losing visibility, skip auto-generated or expensive tests when appropriate, and get a summary that is actually useful in CI (continuous integration) and day-to-day development. # Main functionalities ## Configuration of test suites One of the main features of the framework is that test runs are driven by a project-level configuration file such as [TestConfig.m](https://github.com/SjoerdSmitWolfram/UnitTestFramework/blob/main/Examples/Tests/TestConfig.m) (though other formats like .json are also supported to some extent). Instead of hard-coding behavior into ad hoc scripts, you can define things such as: * where test files live * which test files to include * which paclet contexts should be loaded * whether to abort on the first unexpected failure (so you can easily reproduce the kernel state at the point of failure) * whether to run a full test suite or a quicker local version * custom initialization and evaluation behavior and fine control over which contexts are visible while tests are running. * isolation of the contents of each test file (so that variables defined in one test file do not affect tests in another file) * local machine-specific overrides through an optional LocalConfig file * configuration of local dependencies, such as other paclets that you're developing in unison with the one you're currently testing If you're using the .m format for the TestConfig file, you can also extend the unit test framework with your own code, such as helper functions for deciding how to handle numerical noise in outputs. The test configuration file makes the test runner much easier to reuse across projects because it factors out all of the project-specific peculiarities into a file that's easy to commit and maintain. The same framework can be loaded once and then adapted per paclet by changing the config, rather than rewriting the test infrastructure every time. You can even have multiple test files to configure different ways to run the tests. Most projects will require minimal setup to get the test suite up and running; the main property to configure will be the `"PacletContexts"`. Other properties only need to be tinkered with if the project is structured differently from the default assumptions. ## Tagging tests A second major feature is test tagging through `TagTest`. This lets you attach metadata to tests in a structured way and then use that metadata to control execution and reporting. For example, you can mark tests as: * known issues * not yet implemented * performance tests * generated tests * full-report-only tests * to-be-skipped That turns out to be extremely useful in practice. Real test suites are not always just pass or fail. Sometimes a failure is expected because a bug is known. Sometimes a test is intentionally present before the implementation exists (i.e., test-driven development). Sometimes a test is too expensive for every local run. Tags make those cases explicit instead of forcing them into awkward workarounds. ![Examples of tagged tests][1] ## Test summaries The framework also adds categorized summaries on top of the raw test results. Instead of only seeing whether a run passed or failed, you can group results into categories such as Success, Failure, KnownIssue, NotImplemented, PerformanceFailure, Fixed, Implemented, and Skipped. This gives a much better high-level view of the state of a test suite and helps answer questions like: * Which files are producing real failures? * Which failures are already known? * Which not-yet-implemented tests have started passing? * Which tests were skipped in a local run? For CI, the framework also builds a filtered report focused on the categories that should actually affect pass/fail decisions, while still keeping the richer result structure available for analysis. ![A typical test summary][2] ## Command line interface The repository also includes example scripts for running tests from the command line, which makes the framework suitable for automation and CI workflows. That means you can use the same test infrastructure both interactively inside the Wolfram Language and non-interactively from scripts. If you maintain paclets or other structured projects, this makes it much easier to integrate testing into build pipelines, local shell workflows, and repeatable project setup. The example unit tests can be run from the command line (assuming you start it in the root directory of the repository) with the following line: ``` wolframscript -file Examples/Tests/run_tests.wls ``` ![Running the unit tests from the command line][3] The overall goal is to make Wolfram Language testing feel less like a one-off notebook activity and more like a maintainable development workflow. If you have any questions or suggestions, please let me know! [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Taggingtests.png&userId=839741 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Testsummary.png&userId=839741 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=commandline.png&userId=839741 Sjoerd Smit 2026-06-30T14:16:27Z https://community.wolfram.com/groups/-/m/t/3737733 Reduce[{Norm[z1] == Norm[z2] == 2, z1 + z2 == Sqrt[3] + I, y == Norm[z1 - z2]}, y, {z1, z2}] Solve[{Norm[z1] == Norm[z2] == 2, z1 + z2 == Sqrt[3] + I, y == Norm[z1 - z2]}] // FullSimplify Why get different results when solving the same complex equation using Reduce and Solve? ![enter image description here][1] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=2026-06-22_201444.png&userId=3593842 Bill Blair 2026-06-22T12:19:30Z https://community.wolfram.com/groups/-/m/t/3721357 In[83]:= LaunchKernels[] During evaluation of In[83]:= LinkObject::linkd: Unable to communicate with closed link LinkObject['/Applications/Wolfram.app/Contents/MacOS/WolframKernel' -noinit -subkernel -wstp,2002,23]. During evaluation of In[83]:= LinkObject::linkd: Unable to communicate with closed link LinkObject['/Applications/Wolfram.app/Contents/MacOS/WolframKernel' -noinit -subkernel -wstp,2003,24]. During evaluation of In[83]:= LinkObject::linkd: Unable to communicate with closed link LinkObject['/Applications/Wolfram.app/Contents/MacOS/WolframKernel' -noinit -subkernel -wstp,2004,25]. During evaluation of In[83]:= General::stop: Further output of LinkObject::linkd will be suppressed during this calculation. During evaluation of In[83]:= Parallel`Developer`ConnectKernel::failinit: 8 of 8 kernels failed to initialize. Out[83]= {} In[82]:= ParallelKernels[] Out[82]= {} In[80]:= AbsoluteTiming[ counts2X2X2sList = ParallelMap[ ArrayReshape[ (* Convert 1X8 counts into 2X2X2 counts; doing it this weird way - Flatten first - is much faster. *) Flatten@#, {Length@#, 2, 2, 2} ] &, counts1X8sList ] ][[1]] During evaluation of In[80]:= ParallelMap::nopar: No parallel kernels available; proceeding with sequential evaluation. Out[80]= 0.040537 Mark Tuttle 2026-05-24T12:29:20Z https://community.wolfram.com/groups/-/m/t/2437685 I'm very happy with the continued improvement of the Dicom import and export functionality and speed. However, there is one issue with the current implementation that makes it very unuseful if you do quantitative image analysis. It might be that I miss an option if not I think this should be fixed. In the Mathematica documentation and examples, Dicom data is typically shown and imported as images which I understand for display purposes. But I consider the information in Dicom files as data, very well curated and standardized. For many (MRI) applications, the actual quantitative values of voxels stored in Dicom actually have meaning, values, and even units. For example in the image below each voxel value is actually a quantitative measure of T2 relaxation time in the heart, where the values are stored in milliseconds as voxel values as is also mentioned in the metadata. ![enter image description here][1] ![enter image description here][2] To get from the stored values to quantitative values (WV, DV or FP) the fields from the header and the equations are well defined. Header values: - SV = stored value of DICOM PIXEL DATA without scaling - WS = RealWorldValue slope (0040,9225) "RWVSlope" - WI = RealWorldValue intercept (0040,9224) "RWVIntercept" - RS = rescale slope (0028,1053) "RescaleSlope" - RI = rescale intercept (0028,1052) "RescaleIntercept" - SS = scale slope (2005,100E) "ScaleSlope" Outputs: - WV = real world value - FP = precise value - DV = displayed value Formulas: - WV = SV * WS + WI - DV = SV * RS + RI - FP = DV / (RS * SS) So my first try was that I want to obtain the "RawData" to access the SV pixel data, which does not output anything. ![enter image description here][3] Eventually, if I import this Dicom file into Mathematica I have to use a lot of tricks to get to the correct stored values. The Dicom images I use are stored as 12-bit Integers but are converted by Mathematica to a Numerical array with type Int16. Also, I have to specifically specify that I don't want any "DataTransformation" which by default rescales the data and actually changes some voxel values!!!! In[1]:= << QMRITools` {meta, data, bd} = Import[file, {"dicom", {"MetaInformation", "Data", "BitDepth"}}, "DataTransformation" -> None]; dataT = Import[file, {"dicom", {"Data"}}]; {dd = ToExpression[ StringJoin @@ StringCases[NumericArrayType[data], DigitCharacter]], bd} {ss, rs, ri} = meta /@ {"2005_100e", "RescaleSlope", "RescaleIntercept"} {data, dataT} = Normal@{data, dataT}; svT = 2.^bd (dataT/(2.^dd)); pfT = (rs svT + ri)/(rs ss); sv = 2.^bd (data/(2.^dd)); pf = (rs sv + ri)/(rs ss); PlotData[pfT, pf] Out[3]= {16, 12} Out[4]= {1.99854, 0.500366, -2.} For my current research, I need the PF values and to get them correctly I have to: 1. Use "DataTransformation"->None, which is not really well documented what it actually does. But based on what I see actual values of the data are changed by clipping the histogram, which for default handling of medical data is never OK!! ![enter image description here][4] 2. As far as I am aware the only way to obtain the actual stored values of my Dicom data (the actual binary values stored in the file itself) I have to find the actual BiteDepth and the imported data type and rescale my data accordingly. Below are the obtained PF valued data I need with and without DataTransformation. Although the image on the right might look less appealing with default range and scaling it is actually correct when scaled apropriately. ![enter image description here][5] ![enter image description here][6] Am I missing a correct option for getting the actual data stored? If not this should definitely be changed. Dicom is the international standard to transmit, store, retrieve, print, process, and display medical imaging information. With the current implementation, it is impossible to Import and Export such files without actually changing the stored data. Thanks, Martijn [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=dcmtag.png&userId=1332602 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=T2map.png&userId=1332602 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=raw.png&userId=1332602 [4]: https://community.wolfram.com//c/portal/getImageAttachment?filename=hist.png&userId=1332602 [5]: https://community.wolfram.com//c/portal/getImageAttachment?filename=dataTrans1.png&userId=1332602 [6]: https://community.wolfram.com//c/portal/getImageAttachment?filename=dataTrans2.png&userId=1332602 Martijn Froeling 2022-01-05T09:42:43Z https://community.wolfram.com/groups/-/m/t/3644908 **TL;DR** I'm looking for someone to refactor a Mathematica notebook I've got from a fellow researcher so I can use it as a reliable reference implementation. I expect it's a few hours of work for the right person. I can offer financial compensation and/or my own technical expertise. Hello Wolfram community! I hope this is the right place for this kind of request. If not, my apologies! I'm a PhD student in the final stage of my project, an attempt at closed-loop control of water jets from firefighting robots using UAV imagery as feedback. The controller design is based on the Smith predictor architecture, which requires a predictive model to compensate for the long dead time of the system. Accurately predicting the trajectory of water jets is far from trivial. One of the most promising models I could find is described in https://link.springer.com/article/10.1007/s10694-021-01175-1. The model is formulated as a system of ordinary differential equations. I tried implementing it in Python so I can integrate it with my other components. It's almost complete, but despite several months of debugging I haven't been able to resolve the remaining issues. So I contacted the corresponding author. They confirmed some errors I found in the printed versions of the equations, and kindly provided their original Mathematica implementation. This helped, but my own implementation is still incomplete. The issues could stem from additional errors in the printed equations I/we haven't found yet, mistakes in my implementation, or differences in solver behavior (Mathematica's vs. SciPy's solve_ivp() function). Unfortunately, the notebook is hard for me to follow and differs quite a bit from the published paper (structure, variable naming, angle conventions, etc.). I've never worked with Mathematica and don't have the time nor patience to properly learn it before my deadline. The author is currently unable to provide further support, but since I'm getting more and more desperate to finish this subproject, I'm now seeking third-party help. I'm looking for someone to refactor the notebook into a clean, well-structured reference implementation. Specifically, I'd like them to - remove unused and redundant code (many expressions are duplicated) - improve structure - improve documentation - add small quality-of-life improvements if appropriate - flag any noticeable discrepancies The refactored version must reproduce the original results, in particular the figures shown in the paper. Ideally, it should make it easy to experiment with the equations and parameters. One specific goal is to verify whether the rearranged equation forms I use in Python (to match SciPy's solver interface) produce the same results as the original formulation. If you're interested, I'll obtain the author's permission and share the notebook privately so you can assess the scope before we discuss compensation. Bonus points if you have experience with physics-based simulations and are open to occasional follow-up questions :) Many thanks and regards! Merlin Stampa 2026-02-24T20:34:23Z https://community.wolfram.com/groups/-/m/t/3710069 Script: ```wls Do[ queryresult = RunProcess[ { "bq", "query", "--format=json", "--nouse_legacy_sql", "--max_rows=86400", "SELECT DISTINCT ST_X(`geography`) AS longitude, ST_Y(`geography`) AS latitude FROM `personalinformatics.locations` WHERE EXTRACT(DATE from `timestamp` AT TIME ZONE 'America/New_York') = '"<>DateString[mapdate,"ISODate"]<>"'" }, "StandardOutput" ]; data = ImportString[queryresult,"RawJSON"]; table = Table[ GeoPosition[ { ToExpression@data[[i,"latitude"]], ToExpression@data[[i,"longitude"]] } ], {i, Length[data]} ]; map = GeoListPlot[ table, ImageSize->{1080,1080}, GeoServer->"https://tiles.openstreetmap.us/vectiles/`1`/`2`/`3`.pbf", GeoScaleBar->{"Imperial","Metric"}, PlotLabel->Style["Daily GPS Map | " <> DateString[mapdate,"LocaleDateFull"],"Subtitle"] ]; Export["/home/steven/public_html/dailymaps/"<>DateString[mapdate,"ISODate"]<>"_map.png",map]; Print["Completed map export for "<>DateString[mapdate,"ISODate"]]; ,{mapdate, DateRange[DateObject[{2026, 4, 27}], DateObject[{2026, 4, 30}]]}] ``` The following error is returned: ``` GeoServer::styleres: Cannot download vector style resources. ``` I have tried the following URLs for GeoServer and am getting this error (note, there should be backticks around the `1`, `2`, and `3`—this forum composer removes them). - https://tile.openstreetmap.org/`1`/`2`/`3`.pbf (the current OpenStreetMap vector tile URL) - https://tile.openstreetmap.org/`1`/`2`/`3`.png (the current OpenStreetMap raster tile URL) Steven Buehler 2026-05-01T12:48:58Z https://community.wolfram.com/groups/-/m/t/3674343 The rule "BA" -> "AB" is presented in Section 5.9 of the Physics Project book ("The Significance of Causal Invariance") as being causal invariant. The instances of its causal graph shown therein for 5 time steps and initial condition "BBBAA" is given as example, showing that all 5 instances are isomorphic to each other. I've run the example with the MultiwaySystem function (ResourceFunction["MultiwaySystem"][{"BA" -> "AB"}, "BBBAA", 5, "CausalGraphInstances"]) and the function output matched the book content. However: 1) Running the system for only 4 time steps, not all instances are isomorphic to each other, since in this case there 2 types of graphs (among the 5 instances) which are clearly not isomorphic to each other. 2) In the subsequent example in the section -- that changes the initial condition to "BBBBAAAA" -- the MultiwaySystem function couldn't generate the instance causal graph shown in the book, regardless of the number of time steps I tried (from 4 to 10). Actually, for all these time steps different graph types are generated which precludes the existence of isomorphism among them all. Pedro Paulo Balbi 2026-04-04T20:45:37Z https://community.wolfram.com/groups/-/m/t/3672512 I want to decrease the computation time of the following code. If `c` is a large constant, how do we show when: Clear["Global`*"] c=100 LengthS[r_] := LengthS[r] = {3(r-c)!, r!/2 + 1} LengthS1[r_, y_] := LengthS1[r, y] = LengthS[r][[y]] LengthS2[j_, y_] := LengthS2[j, y] = LengthS[j][[y]] V[r_]:=V[r]=r!+1 and: P1=200 Min11[r_, x_] := Min11[r, x] = FindInstance[LengthS1[r1, x] < V[r] && V[r] < LengthS1[r1 + 1, x] && r - P1 <= r1 && r1 <= r + P1, {r1}, PositiveIntegers] Min12[r_, x_] := Min12[r, x] = ArgMin[{RealAbs[LengthS1[r2, x] - V[r]], r - P1 <= r2 <= r + P1}, r2, PositiveIntegers] Min21[r_, y_] := Min21[r, y] = FindInstance[LengthS2[r3, y] < V[r] && V[r] < LengthS2[r3 + 1, y] && r - P1 <= r3 && r3 <= r + P1, {r3}, PositiveIntegers] Min22[r_, y_] := Min22[r, y] = ArgMin[{RealAbs[LengthS2[r4, y] - V[r]], r - P1 <= r4 <= r + P1}, r4, PositiveIntegers] then `rMin1[r,1]==r+c` and `rMin2[r,2]==r` (e.g., `rMin1[r,1]==10+c` and `rMin2[r,2]==10`). rMin1[r_, x_] := rMin1[r, x] = Min12[r, x] + Sign[Floor[RealAbs[2 r - Min11[r, x] - Min12[r, x]]/2]] rMin2[r_, y_] := rMin2[r, y] = Min22[r, y] + Sign[Floor[RealAbs[2 r - Min21[r, y] - Min22[r, y]]/2]] rMin1[10,1] rMin1[10,2] However, it takes too long to compute `rMin1[10,1]` and `rMin2[10,2]` and I do not know what are the actual outputs. Bharath Krishnan 2026-03-31T15:22:31Z https://community.wolfram.com/groups/-/m/t/3635801 I have a few code samples which freeze or crash my kernel on evaluation, can anybody confirm that this isn't a local issue for me? Discrete: AudioGenerator[{"Color", AudioGenerator[TimeSeries[{1}, {1}]]}] Continuous: AudioGenerator[{"Color", AudioGenerator[{"Sawtooth", .4, 5}]}] Joseph Stocke 2026-02-06T21:20:51Z https://community.wolfram.com/groups/-/m/t/3624223 The first graphic is from a notebook many years old, and the second is from the latest version of Mathematica. What's going on? Is this a known regression in functionality? ![enter image description here][1] ![enter image description here][2] n = 7; m = 3; dt = 2 Pi/n; dtm = 2 Pi/m; r = 1./(1 - Sin[dt/2]/Cos[dtm/2]); R = 1. r Cos[(dt + dtm)/2]/Cos[dtm/2]; ToMatrix[z_, r_] := (I/r) {{z, r^2 - z Conjugate[z]}, {1, -Conjugate[z]}}; alist = Table[ ToMatrix[r Exp[I t], r - 1], {t, dt/2, 2 Pi, dt}]; Tlist = Join[{IdentityMatrix[2]}, alist]; homography[{{a_, b_}, {c_, d_}}, z_] := (a z + b)/(c z + d); FindT[T0_, Tlist_] := MemberQ[Tlist, T_ /; Abs[homography[T, 0] - homography[T0, 0]] < 1.0*^-3]; i2 = 1; Do[i1 = i2 + 1; i2 = Length[Tlist]; Do[Scan[(T = Tlist[[i]] . #; If[! FindT[T, Tlist], Tlist = Append[Tlist, T]]) &, alist], {i, i1, i2}], {2}]; plot = Show[ Graphics[ Map[Line[ Table[z = homography[#, R Exp[I t]]; {Re[z], Im[z]}, {t, 0, 2 Pi, dt}]] &, Tlist], AspectRatio -> Automatic], Axes -> True] data = (Table[ z = homography[#1, R Exp[I t]]; {Re[z], Im[z], 0.}, {t, 0, 2 \[Pi], dt}] &) /@ Tlist; L = MeshRegion[Join @@ Most /@ data, Line[Join @@ (Partition[#1, 2, 1, 1] &) /@ Partition[Range[7 Length[data]], 7]]]; f = RegionDistance[L]; \[Theta]1 = 0.08; \[Theta]2 = 0.01; z =. R1 = ImplicitRegion[ f[{x, y, z}] <= \[Theta]1, {{x, -4, 4}, {y, -4, 4}, {z, -2, 2}}]; S1 = DiscretizeRegion[R1, MaxCellMeasure -> 0.0001] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=9870Untitled.png&userId=1537376 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=9363Untitled2.png&userId=1537376 Eric Mockensturm 2026-01-24T22:21:35Z https://community.wolfram.com/groups/-/m/t/3574670 &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/d8e5d5cd-83af-487b-9c48-d4a82ef214f1 Werner Geiger 2025-11-13T21:41:30Z https://community.wolfram.com/groups/-/m/t/3561367 I calculate huge matrices (of the order of 10^4 x 10^4 or more) in C++ (because Mathematica is too slow for this...) in 80-bit (long double) and export it to 128-bit (because Mathematica can only read either 64-bit or 128-bit with BinaryReadList). I import the matrices into Mathematica because it's much easier to make graphics, convergence analysis and so on. So after having loaded them into Mathematica, the numbers have mantissas of about 50 digits (the numbers on the left after the back tick `). But because they were originally calculated only in 80-bits, 50 digits are useless. In order to load them quickly, I need to convert them into compressed text. But before doing this, I would like to reduce the numbers to 20 digits, because this is 80-bit precision. This would reduce space on disk and load them more quickly. However, SetPrecision[z,p] or N[z,p] where z is a number with a mantissa of 50 decimal digits and p=20 is the desired precision does not reduce the digits at all. If I want to reduce it to 16 digits for example, I need to set p=4 or so. Why is this? Normally, when someone talks of a number z having p precision, I understand that it has a mantissa of p decimal digits. Am I missing something? Ulrich Utiger 2025-10-16T16:26:22Z https://community.wolfram.com/groups/-/m/t/3562641 **The problem** I run Mathematica 12 from home via a Win11 VM on Proxmox. This configuration has run fine for years. Recently during an upgrade to Win11 25H2 I went to test to make sure everything was functional with a quick BenchmarkReport[] but it caused the kernel to die at Test 3, FFT. Its a very repeatable failure. Just before upgrading to 25H2 I had changed my processor type for this VM to x86-64-v3 +aes from -v2 + aes. I had issues on another vm where Win11 didnt want to upgrade with v2. I didnt originally run the processor as "host" as I am running dual E5-2699v4 Xeons, Win11 doesnt support by age despite having all the instructions needed. I have used this VM with Win10 and Win11 for years running Mathematica without issue. In the past I would use BenchmarkReport[] as a quick check of functionality after any upgrades or changes. This is the first time its failed. A quick test using ParallelTable[sin[x],{x,0,pi,10^-6}] works fine A quick test of Fourier[{1, 1, 2, 2, 1, 1, 0, 0}] works fine But a simple, Needs["Benchmark`"] BenchmarkReport[] Fails while calculating Step 3, FFT. The kernel simply die with no error message or warning. If I watch carefully with Task Manager it looks like the kernel dies, Mathematica recreates the kernel, then it dies again immediately. I also tried running this command through mathscript with -verbose but it gives me no additional details why its dying. I went back and tested some older notebooks I had. One of the first ones I tried died during a NonLinearModelFit of a PieceWise function with Sin[]s. Piecewise[{ { y0 + ( A1 Sin[ 2 \[Pi] ( x - x1)/t1] Sin[ 2 \[Pi] ( x - x2)/t2] ) + A3 Sin[2 \[Pi] (x - x3)/t3], x >= xon }, {y0, x < xon} }] This had worked in the past but now it dies just like BenchmarkReport, the kernel dies with no errors. **Fixes tried** So, I set the cpu back to v2 + aes for the vm config in proxmox but the kernel still dies. Set the cpu to Host in case its an issue with AES being passed correctly but it still dies I had Ballooning memory on so I turned it off, no change I had NUMA on so I turned it off, no change I uninstalled, reinstalled Mathematica 12.0 but it still fails I installed a demo copy of Mathematica 14.3, BenchmarkReport[] and my notebook run without issue. **System Info** Running a network version of Mathematica 12.0 with MathLM on another VM for the license. License is for 2 instances and 16 kernels. The VM is running under proxmox 8.4.14. The vm was just recently upgraded to Win11 25H2 but I am not sure when I last ran BenchmarkReport[]. I have run BenchmarkReport[] on this vm multiple times with some older flavors of win11 but I cant remember when I last ran it. I had recently installed the virtio drivers for this vm on the previous Win11 version but I hadnt run Mathematica since then. Could be a contributing factor. Proxmox has gone through a recent upgrade with a reboot of the host. I hadnt tried test Mathematica afterwards. Could be a contributing factor. The vm has been tested with cpu set to Host, x86-64-v2+aes, x86-64-v3+aes, numa on and off, ballooning on and off, with 32GB memory configured for the vm. This vm is set to get 2 processors of 8 cores each, The vm is only running microsoft virtual graphic drivers and is only accessed via remote desktop, not SPICE. As far as I can tell Win11 is working as expected. I am considering a fresh install of Win11 if no better ideas surface. The host system is dual E5-2699 v4 with 512GB. The host system runs a mix of vms and containers. **Summary** I know this is probably a very weird edge case of using a VM with such an old version of Mathematica. The kernel dying does seem to fail for more than just Benchmark so its most likely not a single package responsible. The failure is limited to Mathematica 12 as far as I can tell. Just wanted to figure this our before I start embarking on a bunch of calculations. Any thoughts are appreciated. Mike Morrell 2025-10-19T19:10:08Z https://community.wolfram.com/groups/-/m/t/3558524 Hi everyone, I have a Mathematica program that takes an extremely long time to process and still doesn’t produce any result, even after more than 15 hours of runtime. Here are my system details: Supercomputer with 256 GB RAM 8 cores, each running at 3.7 GHz Mathematica uses all CPU cores but only around 3–4 GB of RAM Despite this, the computation doesn’t seem to progress efficiently. I’d like to understand: Why is Mathematica using all the CPU but so little memory? What are the best practices to optimize my code (e.g., parallelization, memory management, symbolic vs numeric evaluation)? How can I identify the performance bottlenecks in my code? If helpful, I can share a simplified version of my code to analyze where the slowdown occurs. Any advice on improving speed or diagnosing such behavior would be greatly appreciated! Thanks in advance! This is my code. also i use vs 12. &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/2a2ecbd9-090f-45c0-915d-15d5e2dd9261 Reza rho 2025-10-09T07:06:05Z https://community.wolfram.com/groups/-/m/t/3545532 Using an example from the documentation f[x_, y_] = Exp[Sin[50 x]] + Sin[60 Exp[y]] + Sin[70 Sin[x]] + Sin[Sin[80 y]] - Sin[10 (x + y)] + 1/4 (x^2 + y^2); AbsoluteTiming @ NMinimize[f[x, y], {x, y}, Method -> "RandomSearch"] {0.0919746, {-2.38708, {x -> -0.124868, y -> 0.290932}}} AbsoluteTiming @ NMinimize[f[x, y], {x, y}, Method -> {"RandomSearch", "SearchPoints" -> 1500}] {4.19461, {-3.30687, {x -> -0.0244031, y -> 0.210612}}} AbsoluteTiming @ (sln = NMinimize[{f[x + dx, y + dy], -0.01 <= dx <= .01 , -.01 <= dy <= .01}, {x, y, dx, dy}, Method -> {"RandomSearch", "SearchPoints" -> 50 }]) {0.432524, {-3.30687, {x -> -0.0156802, y -> 0.212335, dx -> -0.00872292, dy -> -0.00172211}}} {x + dx, y + dy} /. sln[[2]] {-0.0244031, 0.210612} Frank Kampas 2025-09-14T18:03:01Z https://community.wolfram.com/groups/-/m/t/3531785 Wolfram Video Processing is too slow in real-life situations. I love using Wolfram Language for real-life applications, and I appreciate that Wolfram has recently focused on first-class video functionality. However, it’s a pity that while it works fine for demonstrations, it is far too slow for practical use. For example, when I use CapCut to edit and render a 5-minute video, it takes only a few seconds. But in Wolfram Mathematica, the same process is extremely slow. For a simple 7-minute video (with only text overlay), Wolfram takes 6 minutes just to render. That is unusable! Imagine processing a **30-minute video—it could take 45 minutes**, while CapCut would finish in under a minute. ![enter image description here][1] I have also tried adjusting encoders, frame rates, and other settings, but it didn’t help. Can someone suggest a solution? Thank you very much. [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=1755454340--0Codec.nb_-Wolfram.jpg&userId=138946 Jaques Secretin 2025-08-17T18:15:27Z https://community.wolfram.com/groups/-/m/t/3532836 This code runs for a long time without results in Mathematica. What is the reason? FunctionRange[{Abs[x1 + y1 - 1]/Sqrt[2] + Abs[x2 + y2 - 1]/Sqrt[2], x1^2 + y1^2 == 1, x2^2 + y2^2 == 1, x1 x2 + y1 y2 == 1/2}, {x1, y1, x2, y2}, k] Wen Dao 2025-08-19T10:38:02Z