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Copy

Sort a temporary ordering and then replace m_index when done: success.

    template <typename Compare>
    void stableSort(Compare compare)
    {
        auto order = m_index;
        std::stable_sort(

connormanning

using StringMap = std::map<std::string, std::string>;

// From null: [json.exception.type_error.302] type must be object, but is null
try { StringMap m = json(); }
catch (std::exception& e) { std::cout << "From null: " << e.what() << std::endl; }

// From non-object: [json.exception.type_error.302] type must be object, but is number
try { StringMap m = json(42); }
catch (std::exception& e) { std::cout << "From number: " << e.what() << std::endl; }

connormanning

using StringMap = std::map<std::string, std::string>;

// From null: [json.exception.type_error.302] type must be object, but is null
try { StringMap m = json(); }
catch (std::exception& e) { std::cout << "From null: " << e.what() << std::endl; }

// From non-object: [json.exception.type_error.302] type must be object, but is number
try { StringMap m = json(42); }
catch (std::exception& e) { std::cout << "From number: " << e.what() << std::endl; }

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About

Areas of interest from the recently published Geiger mode LiDAR dataset by USGS around Chicago. Data comes from the USGS 3D Elevation Program, computation and data hosting in partnership with AWS Public Datasets, and processed as EPT with Entwine software by Hobu Inc.

See the rest of the data (over 13 trillion points) at usgs.entwine.io.

Query and manipulate with PDAL's EPT reader using the EPT endpoint.

Links

• [Sears Tower & skyscraper heights](https://usgs.entwine.io/data/view.html?r=%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_IL_4County_Cook_2017_LAS_2019%22&pb=6713000&m=3&ir=%5B2628,65536

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Description

https://entwine.io/data/red-rocks.laz and https://entwine.io/data/red-rocks.bpf contain the same point cloud data and the same SRS info. The SRS is UTM zone 13N (EPSG:26913).

In this sample program, the following pipeline behaviors are run in order:

1. reproject the BPF file to EPSG:3857
2. reproject the LAZ file to EPSG:3857
3. reproject the BPF file to EPSG:3857 with readers.bpf.spatialreference set to EPSG:26912
4. reproject the LAZ file to EPSG:3857 with readers.laz.spatialreference set to EPSG:26912

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set lines=65
set columns=175
set nocompatible
set number
set expandtab
set tabstop=4
set shiftwidth=4
set hlsearch
set ignorecase
set smartcase

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{
  "partitions": [
    {
      "defaults": {
        "hostname": "{service}.{region}.{dnsSuffix}",
        "protocols": [
          "https"
        ],
        "signatureVersions": [
          "v4"

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#include <iostream>
#include <pdal/util/Utils.hpp>

int main()
{
    const auto bt(pdal::Utils::backtrace());
    if (bt.empty()) std::cout << "No backtrace!" << std::endl;
    else
    {
        std::cout << "Backtrace:" << std::endl;

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Assuming ~/data will be the greyhound data directory.

Index data:

docker run -it -v ~/data:/opt/data connormanning/entwine build \
    -i https://entwine.io/sample-data/red-rocks.laz \
    -o /opt/data/red-rocks

Create ~/data/config.json to allow the /write greyhound endpoint:

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docker run -d \
    --name gdb \
    --security-opt seccomp=unconfined \
    --cap-add=SYS_PTRACE \
    -p 80:80 \
    -v /whatever/volume/mappings:/something \
    -v `pwd`:/opt/home \
    connormanning/greyhound:dev \
    -c "(nohup greyhound -c /opt/home/config.json > /var/log/greyhound.txt &) && tail -f /var/log/greyhound.txt"