fig | General Java utilities | Analytics library

 by   percyliang Java Version: Current License: MIT

kandi X-RAY | fig Summary

kandi X-RAY | fig Summary

fig is a Java library typically used in Analytics applications. fig has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can download it from GitHub.

Last updated Oct. 9, 2014.

            kandi-support Support

              fig has a highly active ecosystem.
              It has 33 star(s) with 23 fork(s). There are 3 watchers for this library.
              It had no major release in the last 6 months.
              There are 10 open issues and 5 have been closed. On average issues are closed in 12 days. There are 2 open pull requests and 0 closed requests.
              It has a negative sentiment in the developer community.
              The latest version of fig is current.

            kandi-Quality Quality

              fig has 0 bugs and 0 code smells.

            kandi-Security Security

              fig has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              fig code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              fig is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              fig releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              fig saves you 9342 person hours of effort in developing the same functionality from scratch.
              It has 19085 lines of code, 3160 functions and 242 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed fig and discovered the below as its top functions. This is intended to give you an instant insight into fig implemented functionality, and help decide if they suit your requirements.
            • Verify cross - entropy
            • Verify the variance of a dataset
            • Verify the expected log - like log - likelihood of the distribution
            • Compute digamma function
            • Loads the children
            • Sets the offset
            • Read next line
            • Entry point for testing
            • Checks that the set contains only one value
            • Computes the entropy of each node
            • Create an iterator of the lines in the specified path
            • Bench for testing
            • Processes a command line
            • Samples the poisson
            • Entry point for debugging
            • Execute this command
            • Run the filter
            • Test program
            • Run a system command
            • Sample Erlang function
            • Randomly sample number of elements in a list
            • Computes the cross - entropy
            • Main test function
            • Parses the number of seconds and returns the number of seconds
            • Main entry point
            • Computes the cross - entropy of this dirichlet
            Get all kandi verified functions for this library.

            fig Key Features

            No Key Features are available at this moment for fig.

            fig Examples and Code Snippets

            No Code Snippets are available at this moment for fig.

            Community Discussions


            Padding scipy affine_transform output to show non-overlapping regions of transformed images
            Asked 2022-Mar-28 at 11:54

            I have source (src) image(s) I wish to align to a destination (dst) image using an Affine Transformation whilst retaining the full extent of both images during alignment (even the non-overlapping areas).

            I am already able to calculate the Affine Transformation rotation and offset matrix, which I feed to scipy.ndimage.interpolate.affine_transform to recover the dst-aligned src image.

            The problem is that, when the images are not fuly overlapping, the resultant image is cropped to only the common footprint of the two images. What I need is the full extent of both images, placed on the same pixel coordinate system. This question is almost a duplicate of this one - and the excellent answer and repository there provides this functionality for OpenCV transformations. I unfortunately need this for scipy's implementation.

            Much too late, after repeatedly hitting a brick wall trying to translate the above question's answer to scipy, I came across this issue and subsequently followed to this question. The latter question did give some insight into the wonderful world of scipy's affine transformation, but I have as yet been unable to crack my particular needs.

            The transformations from src to dst can have translations and rotation. I can get translations only working (an example is shown below) and I can get rotations only working (largely hacking around the below and taking inspiration from the use of the reshape argument in scipy.ndimage.interpolation.rotate). However, I am getting thoroughly lost combining the two. I have tried to calculate what should be the correct offset (see this question's answers again), but I can't get it working in all scenarios.

            Translation-only working example of padded affine transformation, which follows largely this repo, explained in this answer:



            Answered 2022-Mar-22 at 16:44

            If you have two images that are similar (or the same) and you want to align them, you can do it using both functions rotate and shift :



            User inputs for R ggplot or plotly without shiny
            Asked 2022-Mar-10 at 21:37

            I have an Rmarkdown with a simple scatter plot (a map for instance), and I would like users to be able to provide some arbitrary x and y coordinates via an input and have those plotted on the graph (in red in the example below). The problem is, I don't have a shiny server so I cannot rely on that option. Is there a implement this, for instance, via javascript or something?

            This is what I have:



            Answered 2022-Mar-04 at 19:18

            This may not be what you want but you can do this by adding a runtime of shiny in your yaml



            Plotly Python update figure with dropMenu
            Asked 2022-Feb-18 at 19:54

            i am currently working with plotly i have a function called plotChart that takes a dataframe as input and plots a candlestick chart. I am trying to figure out a way to pass a list of dataframes to the function plotChart and use a plotly dropdown menu to show the options on the input list by the stock name. The drop down menu will have the list of dataframe and when an option is clicked on it will update the figure in plotly is there away to do this. below is the code i have to plot a single dataframe



            Answered 2022-Feb-18 at 07:18

            I adapted an example from the plotly community to your example and created the code. The point of creation is to create the data for each subplot and then switch between them by means of buttons. The sample data is created using representative companies of US stocks. one issue is that the title is set but not displayed. We are currently investigating this issue.



            split geometric progression efficiently in Python (Pythonic way)
            Asked 2022-Jan-22 at 10:09

            I am trying to achieve a calculation involving geometric progression (split). Is there any effective/efficient way of doing it. The data set has millions of rows. I need the column "Traded_quantity"

            Marker Action Traded_quantity 2019-11-05 09:25 0 0 09:35 2 BUY 3 09:45 0 0 09:55 1 BUY 4 10:05 0 0 10:15 3 BUY 56 10:24 6 BUY 8128

            turtle = 2 (User defined)

            base_quantity = 1 (User defined)



            Answered 2022-Jan-22 at 10:09


            Problem resizing plot on tkinter figure canvas
            Asked 2022-Jan-15 at 02:30

            Python 3.9 on Mac running OS 11.6.1. My application involves placing a plot on a frame inside my root window, and I'm struggling to get the plot to take up a larger portion of the window. I thought rcParams in matplotlib.pyplot would take care of this, but I must be overlooking something.

            Here's what I have so far:



            Answered 2022-Jan-14 at 23:23

            try something like this:



            Cross-reference a python code chunk in Rmarkdown with reticulate
            Asked 2021-Oct-25 at 09:27

            I have a Rmarkdown document containing some python code chunks using the reticulate library. The code executes output perfectly; however, how would I cross-reference the generated plots in the text using its label? I am using bookdown::pdf_documents2 etc, and have no issue with inline reference of R chunks using the standard \@ref(fig:my-plot).

            An MWE would be:



            Answered 2021-Oct-25 at 09:27

            I must have been making an error when previously attempting fig.cap within the chunk, as Daniel correctly suggests in the question comments. Attempting with this again, I can cross-reference perfectly with the python chunk across all HTML, PDF and word outputs. The updated MWE is:



            Is there a way to improve the performance of this fractal calculation algorithm?
            Asked 2021-Oct-23 at 20:30

            Yesterday I came across the new 3Blue1Brown video about Newton's fractal and I was really mesmerized by his live representation of the fractal. (Here's the video link for anybody interested, it's at 13:40:

            I wanted to have a go at it myself and tried to code it in python (I think he uses python too).

            I spent a few hours trying to improve my naive implementation and got to a point where I just don't know how could I make it faster.

            The code looks like this:



            Answered 2021-Oct-19 at 08:43
            for _ in range(n_steps):
                state -= (get_function_value(state) / get_function_derivative_value(state))



            Change a matplotlib 3D figure's frames into x,y and z arrows
            Asked 2021-Sep-16 at 14:37

            Can one can change the arrows of a figure into an arrow by superimposing arrows on top of the x, y and z axes to create the illusion of the axes being arrows or perhaps directly change the settings of the frames as Matplot lib framing in order to get the same outcome on a 3D plot, showing (x,y,z) with arrows?

            Turning this



            Answered 2021-Sep-13 at 13:12

            I don't usually use 3D graphs, and I did a lot of research to answer your question. Here's a great approach I found. I created a new Arrow 3D class and implemented it. In your code, I added the class and added arrows to the x-, y-, and z-axes. I manually shifted their positions to align them on the axes.



            Automated legend creation for 3D plot
            Asked 2021-Sep-07 at 07:33

            I'm trying to update below function to report the clusters info via legend:



            Answered 2021-Sep-02 at 01:32

            In the function to visualize the clusters, you need ax.legend instead of plt.legend



            Interpolating non-uniformly distributed points on a 3D sphere
            Asked 2021-Jul-02 at 16:35

            I have several points on the unit sphere that are distributed according to the algorithm described in (and implemented in the code below). On each of these points, I have a value that in my particular case represents 1 minus a small error. The errors are in [0, 0.1] if this is important, so my values are in [0.9, 1].

            Sadly, computing the errors is a costly process and I cannot do this for as many points as I want. Still, I want my plots to look like I am plotting something "continuous". So I want to fit an interpolation function to my data, to be able to sample as many points as I want.

            After a little bit of research I found scipy.interpolate.SmoothSphereBivariateSpline which seems to do exactly what I want. But I cannot make it work properly.

            Question: what can I use to interpolate (spline, linear interpolation, anything would be fine for the moment) my data on the unit sphere? An answer can be either "you misused scipy.interpolation, here is the correct way to do this" or "this other function is better suited to your problem".

            Sample code that should be executable with numpy and scipy installed:



            Answered 2021-Jul-02 at 16:35

            You can use Cartesian coordinate instead of Spherical coordinate.

            The default norm parameter ('euclidean') used by Rbf is sufficient


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install fig

            You can download it from GitHub.
            You can use fig like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the fig component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer For Gradle installation, please refer .


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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