3d Point Cloud Plot Python

generates a 3D scatter plot of points with a 2D array of height values. 3D PDF Examples Welcome to our 3D PDF Gallery. The images of the points2D through the surface parameterization are 3D points. The tiling of the LAS files is based on 1,000 by 1,000 ground spacing. If perspective=FALSE, distance is set to 0 (i. Configuring DNS for the cloud distribution point. Plotting the coordinates I get a point cloud as expected: However, depending on the mesh, there are huge irregular gaps between the points. The viewing point (camera) is located at a distance of 1/distance from the origin. This viewer is now included as part of a new open-source Python package called the Point Processing Tool Kit (PPTK). I The PCL framework contains numerous state-of-the art. plot is that it can be used to create scatter plots where the properties of each individual point (size, face color, edge color, etc. Little past the halfway point. ''' from mpl_toolkits. txt is the input file for the python script. 6 Ways to Plot Your Time Series Data with Python. TIP: To get better point clouds change line 260 in osmbundler/__init__. "[1] This tutorial shows the workflow from how to import an XYZ file and export an STL file. 3D segmentation is a key step to bring out the implicit geometrical information from the. The registration methods work for 2D and 3D point clouds. You should realize that with the finite number of sample points used, it is possible for Plot3D to. To rank the methods we compute average precision. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits. These are fully independent, compilable examples. On the right are three scatter plots of the same point cloud. Point Clouds: Lidar versus 3D Vision F. Several tools are available for navigating around point clouds. This was was undoubtedly the year of the electric scooter. I want to use scipy. I used projectlaser() function but it didnt give me 3D point cloud. Our scope of the project included development of 3D BIM model and preparation of 2D construction drawings. More IndicesPtr indices_ A pointer to the vector of point indices to use. showPointCloud. 7%, with 1024 input points only) classification accuracy on ScanNet. Welsh and Powell, 1967) of 2D or 3D labelled points (i. Given a 3D point cloud, we assign different planar surfaces different colors. Seaborn is a graphic library built on top of Matplotlib. Here is the comprehensive glossary of trending AI terms and frameworks that are break down into much simplified words. In this lesson, you will learn how to reclassify a raster dataset in Python. Computes 3D points from stereo pairs and outputs a point cloud as a set of LAS files. I made a script in python with scipy. Now we can pass these into the Axes3D. A picture is worth a thousand words, and with Python’s matplotlib library, it fortunately takes far less than a thousand words of code to create a production-quality graphic. I use the plotly python api (Scatter3d) method to create 3D scatter plots. PLY file contains ONLY vertex and NOT faces. To best understand how matplotlib works, we'll subordinate our data with a viable real-life scenario. > mesh() is only for functions but not arbitrary data-points. we can litteraly draw a quiver plot using a single. The service was shut down on 2nd Jan 2017 : PythonAnywhere "Host, run, and code Python in the cloud!". Re: Display Pointcloud in 3d Just want to point that the following line supposed not to compile by any C++ compiler: int[][][] Matrix; if you need multidimensional array when you don't know (number of dimensions -1 ) size of dimensions at the compile time, you normally should use a single dimensional array equivalent. Description. Save 3D Elements as Objects Save Rectangular Doors and Windows from 3D Model Elements Save Custom-Shape Doors or Windows Create Custom Components for Doors, Windows, Curtain Wall, Stair, Railing Editing Custom Library Parts and Components. As we read through the file, if an object with the name in column1 doesn't exist we create it, if it does exist we add a second vertex and make an edge between the two. I set the angle of view using the focal length which i got by calibrating a real camera e. His key id EA5BBD71 was used to sign all other Python 2. As an example, the surface above could be plotted on a circular domain using polar coordinates. Introduction: Matplotlib is a tool for data visualization and this tool built upon the Numpy and Scipy framework. QGIS plugins web portal. [email protected] Convert Entire Model to 3D Point Cloud. Epipolar Geometry Let’s understand epipolar geometry and epipolar constraint. Remember, a level curve of f(x,y) has the same value z in all the points of x,y that curve passes through. normals % Compute normal vectors of activated points. Point Clouds: Lidar versus 3D Vision F. Demo with Turn table and one static camera. The 3D object detection networks work on the 3D point cloud provided by a range distance sensor. Caligari Corporation's flagship product, trueSpace, uses Python to allow users rapid prototyping with scripting. 5 unit increments: Count the number of points that fall within each bin:. Stanford PLY files visualized in Python Published May 12, 2016 by modern. Now, we can move on to creating and plotting our data. Pirouz Nourian PhD candidate & Instructor, chair of Design Informatics, since 2010 MSc in Architecture 2009 BSc in Control Engineering 2005 Geo1004, Geomatics Master Track Directed by Dr. Has anyone been successful in creating a pdf of a point cloud? I appreciate and look forward to your responses. ListSurfacePlot3D attempts to reconstruct smooth surfaces defined by sets of points. plot % Plot of point cloud. Lidar Momentum. chullLiDAR3D 3D convex hull of the individual tree LiDAR-derived point cloud Description Compute and plot the 3D convex hull (and its surface area and volume) of the individual tree LiDAR-derived point cloud. More Protected Attributes inherited from pcl::PCLBase< PointInT > PointCloudConstPtr input_ The input point cloud dataset. If option "Qc" is not specified, this list is not computed. I created six points in an empty object and then Dupliverted a cube primitive object to the points. It will help you understand the code that will be presented afterwards. Fitting plane to a 3D point cloud using pcfitplane. My issue is this: I have a cloud of 3D points from a CT scan. help pointCloud. 3D CartoPy similar to Matplotlib-Basemap. The same simplices define the triangles on the surface. # ploting the point on a scatter plot for i. You can click and drag the plot to view it from different angles; if you click the plot, hold down the mouse and drag it to the side, then release the mouse, the plot will be set into a spin. The first post - Exporting point clouds from Photosynth - was linked directly from Blaise Aguera y Arcas himself; it linked to another with some more detailed instructions - Photosynth Export Tutorial. from 3D laser scanning (LIDAR). In Recap you can choose to view size of point : 1 to 10. It will be completely retired in October 2019. Open the Point Clouds dialog ( File > Point Clouds ) and attach the Point Cloud file ( File > Attach ) Highlight the attached file in the Point Clouds dialog and select File > Export. RegionPlot3D initially evaluates pred at a 3D grid of equally spaced sample points specified by PlotPoints. In analogy with the more common two-dimensional plots discussed earlier, these can be created using the ax. showPointCloud was renamed to pcshow. Tried to implement Go-ICP, but the results were not good, meybe due to incorrect implementation. These points represent a line in 3D space. PLY file as a cloud of naked vertices, so in order to see them I hit on this method. 6 Ways to Plot Your Time Series Data with Python. Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. While Gnuplot can be used with any language and Matplotlib requires Python to work, R requires you to learn R, the programming language to make it work. I've done some reading about Euler angles but after staring at this GIF for a while I just get diz. I use the api in the offline mode. For this I did not find a simple utility in the internet. Working with point clouds using Kinect, ROS, OpenNI, and PCL A 3D point cloud is a way of representing a 3D environment and 3D objects as collection points along the x, y, and z axes. Point Clouds. I also showed how to visualize them with static 3-D plots. python plot. What is the type of file I need to save the point cloud in QGIS, in order for it to be imported into GRASS? Second, is it possible in GRASS to add multiple layers in order to create a 3D point cloud?. normals % Compute normal vectors of activated points. The point cloud data is stored as an object with the properties listed in Properties. Besides 3D wires, and planes, one of the most popular 3-dimensional graph types is 3D scatter plots. Plotting the coordinates I get a point cloud as expected: However, depending on the mesh, there are huge irregular gaps between the points. Here is the comprehensive glossary of trending AI terms and frameworks that are break down into much simplified words. Convert Entire Model to 3D Point Cloud. Step 2 Creating Data Points to Plot. Computes 3D points from stereo pairs and outputs a point cloud as a set of LAS files. All computations are done in Matlab. ContextCapture Quickly create detailed 3D models using simple photographs and/or point clouds for use in engineering or GIS workflows. python-pcl Overview ; Installation Guide In this tutorial we will learn how to compute normals for an organized point cloud using integral images. of point clouds, meshes, and other representations. How would I calculate the projection of that point on to the line? I'm aware of how to do this in 2D but 3D seems to have bugger all resources. 1) # PythonCaller Script Example (Python 2. The images of the points2D through the surface parameterization are 3D points. it has nothing to do with the capability of technology. Is there a program in python which takes as the input a set of points in 3D and output a mesh? If possible, I'd like the meshing to be uniform. Since 2001, Processing has promoted software literacy within the visual arts and visual literacy within technology. The scatter function plots a scatter plot. How to get the point coordinates as a matrix from a cloud of points in Matlab? How is possible to run point cloud library(PCL) at matlab or python? Question. good ndarray of bool or None. from 3D laser scanning (LIDAR). These are fully independent, compilable examples. I use the Kinect v2 to extract point clouds, and needed a simple code to display and handle point clouds. It takes some time to get used to reading the image, but you should be able to see shapes and the 3D effect should be clear. , collection) of points (usually n = 3) used to represent 3D information about the world. Python is an interpreted, high-level, general-purpose programming language. The key point now is that we have 3 2d arrays, representing x, y and z, held by the variables xv, yv and dem respectively. - plopp/vispy-point-cloud. Iterative closest point (ICP) is an algorithm employed to minimize the difference between two clouds of points. Please redirect your searches to the new ADS modern form or the classic form. One of the methods available in Python to model and predict future points of a time series is known as SARIMAX, which stands for Seasonal AutoRegressive Integrated Moving Averages with eXogenous regressors. I am thoroughly confused about the formation of the 2D Z matrix required by 3D plot surface helper. First, you'll learn about setting up Revit for your scan to BIM conversion. I need to plot a 3D point cloud (number of points: N), then a convex hull (actually a polyhedron with N vertices) from the points. Little past the halfway point. These libraries seamlessly interface with our enterprise-ready Deployment servers for easy collaboration, code-free editing, and deploying of production-ready dashboards and apps. The tiling of the LAS files is based on 1,000 by 1,000 ground spacing. FastICA on 2D point clouds¶ This example illustrates visually in the feature space a comparison by results using two different component analysis techniques. I want to use scipy. How to make a 3D scatter plot in Python? representing a point on the curve? - Alok Singhal Dec 31 We use MayaVi here for all of the 3D plotting and it is. This was my programming battle station for the next two years and proved to be a truly amazing tool that enabled me to learn music and video production, 3D modeling, and a range of different. ly cloud service can publish plots free for public plots. There are quite a few 3D-related libraries available for use with Python, many of them either based on, or extensible with PyOpenGL. e the template/smart_ptr bits) to provide a foundation for someone wishing to carry on. of point clouds, meshes, and other representations. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The lack of such a feature is not due to any difficulty in doing this as. SphericalPlot3D initially evaluates each function at a number of equally spaced sample points specified by PlotPoints. It is saved in form of a very large number of points that cover surfaces of a sensed object. APLpy (the Astronomical Plotting Library in Python) is a Python module aimed at producing publication-quality plots of astronomical imaging data in FITS format. Matplotlib also able to create simple plots with just a few commands and along with limited 3D graphic. The first post - Exporting point clouds from Photosynth - was linked directly from Blaise Aguera y Arcas himself; it linked to another with some more detailed instructions - Photosynth Export Tutorial. Shapely Python bindings for GEOS. PLY file that contains a 3D Point Cloud: I want to plot it and visualize it in Python. The Python code is quite straightforward, and the detailed explanation can be found in Redwood dataset. There are many packages in R (RGL, car, lattice, scatterplot3d, …) for creating 3D graphics. I know that all these points belong to one. Stacked 3D Surface Plots; Multiple Surfaces in Same Layer; 3D Scatter with Colormap; 3D Scatter with Droplines; Surface With Transparent Plane; 3D Bar on Flatten Surface; 3D Bar with Labels; 3D Surface with Point Label; Transparent Parametric Surfaces combined with Scatter Plot; Convert Data from Spherical Coordinate to XYZ and Make a 3D Plot. When plotting/printing the points are diplayed in black only - no colors are plotted for the point cloud. obj files and for them to send a point cloud file to us. However, matplotlib is also a massive library, and getting a plot to look just right is often achieved through trial and. It would be terrific if this program could also compute and display the best fit plane through these points. plot where y = x**2 for x over the interval 1 to 5, properly labelled Create a histogram where the mean = 0, std. In this post we show how to add title and axis label to your python chart using matplotlib. An easy way of creating 3D scatterplots is by using matplotlib. If a level curve is to be drawn for ocean depth where the ocean depth is the same on the places it connects it is called an isobath. "The Point Cloud Library (or PCL) is a large scale, open project for point cloud processing. The point cloud was obtained using multibeam echosounder, which is composed of almost 1 million 3D points (at a density of around 200 points per square metre). Re: Color Point Cloud Plotting Unfortunately it really seems to be that AutoCAD has no option to plot a colored PCG. As we read through the file, if an object with the name in column1 doesn't exist we create it, if it does exist we add a second vertex and make an edge between the two. This entry was posted in Tech and tagged Google Maps API, plot bike data, plot geo data, plot maps with Python, plot sports data, Python, visualization on February 5, 2017 by adamvotava. pkl: pickle of a 3xN numpy matrix of 3D points. It is written in Cython, and implements enough hard bits of the API (from Cythons perspective, i. we can litteraly draw a quiver plot using a single. However, it is possible to create custom extensions to Bokeh, which can be useful for connecting any JS library to Python code. How to make D3. Robert FitzRoy. Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Thanks, Marc. Re: Point Clouds to 3D DWF Cool, We'll have to give that a try. normals % Compute normal vectors of activated points. Normals and feature sizes in point clouds. See LICENSE_FOR_EXAMPLE_PROGRAMS. we can litteraly draw a quiver plot using a single. Qhull n-D approximate convex hulls and triangulations. Generating a 3D Point Cloud. writes: This script, Point Cloud Skinner can skin a cloud of vertices, which means to create a 3D surfaced mesh out of just a cloud of vertices that has no faces. I have a 3D array of points which was generated from an experiment. The order in which , , points are supplied to ListSurfacePlot3D does not affect the results. Instructor Lillian Pierson, P. Plot a 3D wireframe. Point clouds are often aligned with 3D models or with other point clouds, a process known as point set registration. We can get a point cloud from various sources: Either we can create our point cloud by writing a program or we can generate it from depth sensors or laser scanners. The implementation is still in the code, but is not called upon. To get the latest Plotly. A picture is worth a thousand words, and with Python’s matplotlib library, it fortunately takes far less than a thousand words of code to create a production-quality graphic. If it is not detected, maybe your path settings are wrong. The number of K nearest neighbors to use for each point. We are going to click on these three points on the image later. TRS-3D is a three-dimensional multimode naval radar for air and sea surveillance. When I try to plot all I get is a blank pdf. So our X axis is drawn from (0,0,0) to (3,0,0), so for Y axis. Is it possible that I use AWR1243 ADC data from DCA1000 and plot 3D data from point cloud generated. When modeling a Linear-mode detector, the 4th column in the point cloud file is the intensity. 3D point cloud visualization The last step is visualizing the triangulated 3D real-world points. Normally I would do this by plotting polylines for various values of X, Y and Z. But when I try to plot to PDF (via DwgToPdf or PdfCreator) Points in pointcloud have a size of 1 => Point are to small. Robert FitzRoy. This talk will show how a Python program can leverage the PCL interfaces to acquire live point cloud data for processing with SciPy and Numpy. sentdex 94,735 views. Plot 3-D point cloud. PointCloud is a datatype which GH doesn’t know anything about (there are many other types of Rhino object that GH is ignorant of) and as such none of the components can handle it. So to avoid have spikes or deformities in our data we should apply a few methods in eliminating them when possible. You can do this by adding a CNAME record in your DNS server that points to the site URL of the Windows Azure Cloud Service. Axis points are points in 3D space for drawing the axis. Is there a way to "interpolate" between the coordinates to get a regular pointcloud? I found this proposal but couldn't make use of it. 09*10²⁰ array. How can one go about generating a point cloud from the surfaces/faces of a model? Initially the models are going to be fairly simple (just cubes, cylinders, and spheres), but eventually the models will be progressing on to more complicated shapes. I would try Bokeh http://bokeh. First, you'll learn about setting up Revit for your scan to BIM conversion. You have attached a Point Cloud in PCG format in Autodesk® AutoCAD® or a vertical product such as Autodesk® AutoCAD® Civil 3D®. Python's garbage collector runs during program execution and is triggered when an object's reference count reaches zero. This talk will show how a Python program can leverage the PCL interfaces to acquire live point cloud data for processing with SciPy and Numpy. , collection) of points (usually n = 3) used to represent 3D information about the world. This is the upper bookmark in the workspace template. Dash Club is a no-fluff, twice-a-month email with links and notes on the latest Dash developments and community happenings. This viewer is now included as part of a new open-source Python package called the Point Processing Tool Kit (PPTK). Hope this helps. Data Visualization Introduction * Data visualization is the process of converting raw data into easily understandable pictorial representation, that enables fast and effective decisions. If you continue to use the site without changing your cookie settings, we assume you are fine with our cookies and the way we use them. Please try the new VTKExamples website. How can one go about generating a point cloud from the surfaces/faces of a model? Initially the models are going to be fairly simple (just cubes, cylinders, and spheres), but eventually the models will be progressing on to more complicated shapes. def point_cloud(self, depth): """Transform a depth image into a point cloud with one point for each pixel in the image, using the camera transform for a camera centred at cx, cy with field of view fx, fy. Demonstration of a basic scatterplot in 3D. -r estimates the spatial resolution for the model point cloud and afterwards considers the radii used as parameters as if they were given in units of cloud resolution; thus achieving some sort of resolution invariance that might be useful when using this tutorial with the same command line and different point clouds. lør, 20 03 2010 kl. good ndarray of bool or None. 2) Optionally color the points by a property - also read from the file. Python has already made it easy for you - with two exclusive libraries for visualization, commonly known as matplotlib and seaborn. Fit a plane to data points in 3D space This example shows an NLREG program that fits a plane in 3-dimensional space to a set of data points whose X,Y,Z coordinates are specified. Point Cloud is a heavily templated API, and consequently mapping this into python using Cython is challenging. This is the main entry point for people interested in doing 3D plotting à la Matlab or IDL in Python. Shapely Python bindings for GEOS. Technically point cloud is a database containing points in the three-dimensional coordinate system. This can be solved by finding an alpha shape (a concave. cloud draws a 3-D Scatter Plot, while wireframe draws a 3-D surface (usually evaluated on a grid). 0, the Plotly Python package fully supports IPython widgets and exposes additional functionality for interactive exploration of Plotly graphs, like handlers for clicking and hovering on graph data points. Faz a vetorização semiautomática de uma estrada com base em um raster. i/ A rectangular matrix where each cell represents the altitude. Iterative closest point (ICP) is an algorithm employed to minimize the difference between two clouds of points. First project for my Advanced 3D algorithms grad class at the CUNY Graduate Center. (5942479, 3) — our point cloud consists of 5942479 points. they have access to the same. I can plot at different times some points and planes but never at s. We can using that field to drive the point color using the following plot command:. Using the code. So to create an animated point cloud all you have to do is specify an array of points. depth is a 2-D ndarray with shape (rows, cols) containing depths from 1 to 254 inclusive. In some scenarios, such as [3], the input is a point cloud representing a single object, and the goal is to decompose the object into patches. It tries to decode the file based on the extension name. none of them were cut on a haas machine. How do I change a view point ? The view point in the 3-dimensional plot is controlled by set view command. How to cluster points in 3d with alpha shapes in plotly and Python Javascript Note: this page is part of the documentation for version 3 of Plotly. The code calls ICP by default. I have managed to do this with gnuplot and with the python library matplotlib separately. -r estimates the spatial resolution for the model point cloud and afterwards considers the radii used as parameters as if they were given in units of cloud resolution; thus achieving some sort of resolution invariance that might be useful when using this tutorial with the same command line and different point clouds. View, animate, and edit point clouds for reuse in other applications. ly cloud service can publish plots free for public plots. The existing algorithm for convex hull is not able to capture the feature for a set of 3D points. So we're going to be able to take a scanned point cloud from terrestrial. The point cloud data is stored as an object with the properties listed in Properties. ADS Classic is now deprecated. 3D CartoPy similar to Matplotlib-Basemap. For industrial metrology or inspection using industrial computed tomography, the point cloud of a manufactured part can be aligned to an existing model and compared to check for differences. Note that Plotly Express functions take as a first argument a tidy pandas. Point cloud x, y, and z locations, specified as either an M-by-3 or an M-by-N-by-3 numeric matrix. I have a 3D array of points which was generated from an experiment. This parameter is successfully read by AutoCAD, and my point cloud is shown correctly in my layout and in plot preview. One of the things that every Kinect. 2) Optionally color the points by a property - also read from the file. The idea of 3D scatter plots is that you can compare 3 characteristics of a data set instead of two. py, which is not the most recent version. You can view the cloud from different angles and lighting conditions. Therefore, generating colored point clouds is straight-forward. This time, I'm going to focus on how you can make beautiful data visualizations in Python with matplotlib. UR5+velocity control: runaway robot after getting closer to goal pose. point-clouds python 3d-point-clouds 3d-graphics 3d-models 3d python-library deep-learning 3d-deep-learning Good first issues There seems to be a limitation of the angel that we can rotate the point cloud. plot3D and ax. If the data contains RGB information for each point, the scatter plot is colored accordingly. PLY file contains ONLY vertex and NOT faces. PLY file as a cloud of naked vertices, so in order to see them I hit on this method. The electric scooter wars of 2018. This workshop demonstrates the process of working with point cloud data (acquired with the Scanse Sweep 3D LIDAR scanner) in Unity and immersively experience it with an Oculus Rift VR headset. Funnel charts in Python using Plotly Published January 3, 2017 by Pravendra in Business Intelligence , Data Visualization , Python Funnel Charts are often used to represent data in different stages of a business process. Introducing Principal Component Analysis¶ Principal component analysis is a fast and flexible unsupervised method for dimensionality reduction in data, which we saw briefly in Introducing Scikit-Learn. 0 can lead to some very nice plots. I set the angle of view using the focal length which i got by calibrating a real camera e. py'', that takes a color image and a depth map as input, and generates a point cloud file in the PLY format. py, which is not the most recent version. For this I did not find a simple utility in the internet. QGIS plugins web portal. ListPointPlot3D [ { data 1 , data 2 , … plots several collections of points, by default in different colors. EUPDF: Eulerian Monte Carlo Probability Density Function Solver for Applications With Parallel Computing, Unstructured Grids, and Sprays NASA Technical Reports Server (NTRS). Plot3D initially evaluates each function at a grid of equally spaced sample points specified by PlotPoints. Examples (We encourage you to try the examples without installation launching Binder. Noah has 34 jobs listed on their profile. This is the point of no. Great for mobile and airborn point clouds. Faz a vetorização semiautomática de uma estrada com base em um raster. Point Cloud Library I PCL is a large scale, open project for 2D/3D image and point cloud processing (in C++, w/ new python bindings). This R tutorial describes how to perform an interactive 3d graphics using R software and the function scatter3d from the package car. SphericalPlot3D initially evaluates each function at a number of equally spaced sample points specified by PlotPoints. I've done some reading about Euler angles but after staring at this GIF for a while I just get diz. In some scenarios, such as [3], the input is a point cloud representing a single object, and the goal is to decompose the object into patches. It would be appreciated if there are any Python VTK experts who could convert any of the c++ examples to Python!. Hugh Morrison. You don’t have to use 2 though, you can tweak it a little to get a better outlier detection formula for your data. 3D Point Cloud to 2D depth image. I'm rotating points from one coordinate system to the other, but drawing a blank how to do this. NNT, the author of the book — Black Swan, calls our (current) world…. The image below the point cloud captured from the Microsoft Kinect (of a human chest – side view) and it has points that are not apart of the actual object we want to creat a 3D model of. conversion between point cloud types. If either is 0 the input data in not sampled along this direction producing a 3D line plot rather than a wireframe plot. The sequence of images will be generated using CGI to. • Python is a major tool for scientific computing, accounting for a rapidly rising share of scientific work around the globe. As we read through the file, if an object with the name in column1 doesn't exist we create it, if it does exist we add a second vertex and make an edge between the two. addProductionJob ( CCMasterKernelPy. I've gotten the function to work perfectly, but it's way too slow! (takes like 2 seconds per image to process). Provide downloads for product application notes, development kit, SDK references, firmware, ROS packages of SLAMTEC products including RPLIDAR A1/A2/A3, SLAMWARE, ZEUS, Apollo, SDP, SDP Mini and etc. I love how plotly will export the generated graph into html and saves a temp file.