Category: Blog

CAMELS dataset in NetCDF/Feather formats

Motivation

The CAMELS datasets are not provided in an ideal format and takes a bit of data processing to convert them to useful and convenient forms for geospatial analyses. So, I decided to use the beloved netcdf and feather formats to make the dataset more accessible while taking care of some small annoyances! The generated files are hosted on Hydroshare.

Usage

First make sure that h5netcdf, geopandas, xarray, and requests Python packages are installed, then load the files directly like so:

import io

import geopandas as gpd
import requests
import xarray as xr

r = requests.get("https://www.hydroshare.org/resource/658c359b8c83494aac0f58145b1b04e6/data/contents/camels_attributes_v2.0.feather")
attrs = gpd.read_feather(io.BytesIO(r.content))

r = requests.get("https://www.hydroshare.org/resource/658c359b8c83494aac0f58145b1b04e6/data/contents/camels_attrs_v2_streamflow_v1p2.nc")
qobs = xr.open_dataset(io.BytesIO(r.content), engine="h5netcdf")

Methodology

This repo contains the code that I used to generate the datasets. Three data sources are available from the CAMELS dataset:

Observed Flow: Streamflow observations for all 671 stations.
Basin Geometries: Polygons representing basins’ boundaries for all 671 stations.
Basin Attributes: 60 Basin-level attributes for all 671 stations.

The camel_netcdf.py generates two files:

camels_attributes_v2.0.feather: Includes basin geometries and 60 basin-level attributes that are available in CAMELS.
camels_attrs_v2_streamflow_v1p2.nc: Includes observed flows for all 671 stations, as well as the 60 basin-level attributes. It has two dimensions (station_id and time) and 60 data variables.

Additionally, the script takes care of some small annoyances:

Station names didn’t have a consistent format and there were some missing commas and extra periods! Now, the names have a consistent format (title) and there is comma before the states.
Station IDs and HUC 02 are strings with leading zeros if needed.

You can recreate the generated files locally using mambaforge (or conda) like so:

git clone https://github.com/cheginit/camels_netcdf
cd camels_netcdf
mamba env create -f environment.yml
conda activate camels
chmod +x ./camels_netcdf.py
./camels_netcdf.py

Example Plots

Snow fraction using camels_attributes_v2.0.feather: $camels_snow_fraction$

The dataset camels_attrs_v2_streamflow_v1p2.nc:

Streamflow observations for USGS-01013500:

Contributions

Contributions are welcome! Please feel free to open an issue/PR if you have any suggestions that can improve the database.

stwo-brainfuck

stwo-brainfuck is a ZK-VM for the Brainfuck language¹, based on Stwo².

CLI – Installation

Here are the steps to get the Brainfuck ZK-VM up and running.

You can either download the binaries from the
releases, or build them
from source.

Build from Source

Clone the repository

git clone git@github.com:kkrt-labs/stwo-brainfuck.git

Build the brainfuck_prover

The brainfuck_prover has a feature flag which enables the CPU parallelization
feature of Stwo.

No feature flags:

cargo build --package brainfuck_prover --release

Parallel feature flag:

cargo build --package brainfuck_prover --features parallel --release

CLI – Usage

The brainfuck_prover CLI has two subcommands:

prove, which generates a CSTARK proof from a given Brainfuck program file or
code string.
verify, which verify a CSTARK proof from a given Brainfuck proof file.

For more information, try brainfuck_prover --help,
brainfuck_prover prove --help and brainfuck_prover verify --help.

Example usage

Consider this Brainfuck program which, given an ASCII character from Stdin,
outputs the following two characters in the ASCII table:

++>,<[>+.<-]

Prove

To generate a proof of this program, you can provide the Brainfuck program as a
string, with the --code argument, or store it in a file my_program.bf and
provide the path to it with the --file argument.

Here, the proof will be serialized to a JSON file my_program_proof.json. You
can also print the proof to stdout with the --print flag.

Proof from a Brainfuck program given in the command

brainfuck_prover prove --code "++>,<[>+.<-]" --output my_program_proof.json

Or if you built from source,

./target/release/brainfuck_prover prove --code "++>,<[>+.<-]" --output my_program_proof.json

Proof from program file

brainfuck_prover prove --file my_program.bf --output my_program_proof.json

Or if you built from source,

./target/release/brainfuck_prover prove --file ./brainfuck_programs/hello_kakarot.bf --output hello_kakarot_proof.json

Verify

To verify a proof, the proof must be stored in a JSON file (--output flag from
the prove subcommand).

brainfuck_prover verify my_program_proof.json

Or if you built from source and previously generated the proof of the
hello_kakarot example:

./target/release/brainfuck_prover verify hello_kakarot_proof.json

Visualizing the memory

To visualize the memory of the Brainfuck VM, use the --memory flag of the
brainfuck_prover, and reduce the RAM size to avoid printing too much memory
cells to your terminal with the --ram-size flag.

Let’s try it with a Brainfuck program that yields the 19th Fibonacci number.
Note that it is a bit more resource intensive than the other example programs.

./target/release/brainfuck_prover prove --file ./brainfuck_programs/fib19.bf --output fib19_proof.json --memory --ram-size 5

You should be able to see:

[M31(0), M31(2584), M31(4181), M31(0), M31(0)]

The third memory cell contains the desired output: Fibonacci(19) = 4181.

Project Objectives

Capacity of generating and verifying a proof for arbitrary Brainfuck programs.
Understanding of using Stwo for building ZK-VMs
Understanding of modern AIR (RAP) design for (C)STARK-based systems.

Design choices

Brainfuck VM

The Brainfuck language has a very loose specification, though, a
general specification has
been established as a minimal base. We try to follow these guidelines.

The memory cells take values in the Mersenne31 (M31) field: $[0..2^{31} – 1)$
Memory is fixed at 30,000 cells by default, but is configurable.
Memory wraps on overflow/underflow.
- It can be used for memory value mv and memory pointer mp, but it will
  usually panic for mp as the memory size will be much smaller than
  $2^{31} – 1$.
Inputs are line-buffered (ends with the linefeed ASCII character 10).
CLI uses Stdin and Stdout for IO.
For library use, input can be simulated by any reader (e.g. Cursor) and
output with any writer (e.g. a custom writer).

Acknowledgements

The constraints used here rely on work made by Alan Szepieniec³ and sibling
article from Neptune Cash⁴. The Brainfuck compiler and interpreter have been
adapted from rkdud007⁵

Museum Site

Motivation

Artist and artifacts are more praised but less explored This project is an effort to preserve the art and craft o the history

why?

This project was actually build to learn React js and Material UI this is the first project of mine based on react js. This whole project to the last semi-colon belongs to me

overview

Frontend:

React js
Hover js
Swiper js
Material Ui
THREE js
cloudinary

Frontend Folder structure

📦src
┣ 📂components
┃ ┣ 📜AnnouncementBar.jsx
┃ ┣ 📜Artist.jsx
┃ ┣ 📜Backdrop.jsx
┃ ┣ 📜Banner.jsx
┃ ┣ 📜Card.jsx
┃ ┣ 📜CardComponent.jsx
┃ ┣ 📜CollectionHighlight.jsx
┃ ┣ 📜Details.jsx
┃ ┣ 📜Events.jsx
┃ ┣ 📜footer.jsx
┃ ┣ 📜Gallery.jsx
┃ ┣ 📜Genre.jsx
┃ ┣ 📜GenreItem.jsx
┃ ┣ 📜header.jsx
┃ ┣ 📜HeroSlide.jsx
┃ ┣ 📜Highlights.jsx
┃ ┣ 📜History.jsx
┃ ┣ 📜loading.jsx
┃ ┣ 📜Medium.jsx
┃ ┣ 📜MediumItem.jsx
┃ ┣ 📜MockUp.jsx
┃ ┣ 📜MoreArtifacts.jsx
┃ ┣ 📜Podcast.jsx
┃ ┣ 📜Search.jsx
┃ ┣ 📜SearchedItem.jsx
┃ ┗ 📜VIdeo.jsx
┣ 📂Context
┃ ┗ 📜AuthContext.js
┣ 📂Pages
┃ ┣ 📜Artifact.jsx
┃ ┣ 📜Artists.jsx
┃ ┣ 📜Artwork.jsx
┃ ┣ 📜Collections.jsx
┃ ┣ 📜Home.jsx
┃ ┣ 📜Login.jsx
┃ ┣ 📜Medium.jsx
┃ ┣ 📜Profile.jsx
┃ ┗ 📜Register.jsx
┣ 📂utils
┃ ┣ 📜fetchArtistBanner.js
┃ ┣ 📜ProtectedRoute.js
┃ ┗ 📜server.js
┣ 📜App.css
┣ 📜App.js
┣ 📜index.js

Frontend Routes ( with Images )

/ Home Route

/profile User Profile Route

/artists Major artists route

/artist/:id Individual artist route

/explore Route to display explorable artifacts /explore/:id individual explore page /artifact/:id individual artifact and details

Other component

Loading Screen display

Login and Sign up

Backend

folder structure

📦server
┣ 📂controller
┃ ┗ 📜authController.js
┣ 📂middleware
┃ ┣ 📜authMiddleware.js
┃ ┗ 📜uploadMiddleWare.js
┣ 📂models
┃ ┗ 📜User.js
┣ 📂routes
┃ ┗ 📜authRoutes.js
┣ 📂utils
┃ ┗ 📜db.js
┗ 📜server.js

hosting platform

Heroku ( backend )
Netlify (Frontend)

Contribution?

Available Scripts

In the project directory, you can run:

`npm start`

Runs the app in the development mode.\

Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.\

You will also see any lint errors in the console.

`npm test`

Launches the test runner in the interactive watch mode.\

See the section about running tests for more information.

`npm run build`

@gmod/gff

Read and write GFF3 data performantly. This module aims to be a complete implementation of the GFF3 specification.

NOTE: this module uses the NPM stream package, which requires node.js polyfills for use on the web. We also created the https://github.com/cmdcolin/gff-nostream package to allow a non-streaming version that does not require polyfills

streaming parsing and streaming formatting
proper escaping and unescaping of attribute and column values
supports features with multiple locations and features with multiple parents
reconstructs feature hierarchies of both Parent and Derives_from relationships
parses FASTA sections
does no validation except for referential integrity of Parent and Derives_from relationships (can disable Derives_from reference checking with disableDerivesFromReferences)
only compatible with GFF3

Install

$ npm install --save @gmod/gff

Usage

const gff = require('@gmod/gff').default
// or in ES6 (recommended)
import gff from '@gmod/gff'

const fs = require('fs')

// parse a file from a file name
// parses only features and sequences by default,
// set options to parse directives and/or comments
fs.createReadStream('path/to/my/file.gff3')
  .pipe(gff.parseStream({ parseAll: true }))
  .on('data', (data) => {
    if (data.directive) {
      console.log('got a directive', data)
    } else if (data.comment) {
      console.log('got a comment', data)
    } else if (data.sequence) {
      console.log('got a sequence from a FASTA section')
    } else {
      console.log('got a feature', data)
    }
  })

// parse a string of gff3 synchronously
const stringOfGFF3 = fs.readFileSync('my_annotations.gff3').toString()
const arrayOfThings = gff.parseStringSync(stringOfGFF3)

// format an array of items to a string
const newStringOfGFF3 = gff.formatSync(arrayOfThings)

// format a stream of things to a stream of text.
// inserts sync marks automatically.
myStreamOfGFF3Objects
  .pipe(gff.formatStream())
  .pipe(fs.createWriteStream('my_new.gff3'))

// format a stream of things and write it to
// a gff3 file. inserts sync marks and a
// '##gff-version 3' header if one is not
// already present
gff.formatFile(
  myStreamOfGFF3Objects,
  fs.createWriteStream('my_new_2.gff3', { encoding: 'utf8' }),
)

Object format

features

In GFF3, features can have more than one location. We parse features as arrayrefs of all the lines that share that feature’s ID. Values that are . in the GFF3 are null in the output.

A simple feature that’s located in just one place:

[
  {
    "seq_id": "ctg123",
    "source": null,
    "type": "gene",
    "start": 1000,
    "end": 9000,
    "score": null,
    "strand": "+",
    "phase": null,
    "attributes": {
      "ID": ["gene00001"],
      "Name": ["EDEN"]
    },
    "child_features": [],
    "derived_features": []
  }
]

A CDS called cds00001 located in two places:

[
  {
    "seq_id": "ctg123",
    "source": null,
    "type": "CDS",
    "start": 1201,
    "end": 1500,
    "score": null,
    "strand": "+",
    "phase": "0",
    "attributes": {
      "ID": ["cds00001"],
      "Parent": ["mRNA00001"]
    },
    "child_features": [],
    "derived_features": []
  },
  {
    "seq_id": "ctg123",
    "source": null,
    "type": "CDS",
    "start": 3000,
    "end": 3902,
    "score": null,
    "strand": "+",
    "phase": "0",
    "attributes": {
      "ID": ["cds00001"],
      "Parent": ["mRNA00001"]
    },
    "child_features": [],
    "derived_features": []
  }
]

directives

parseDirective("##gff-version 3\n")
// returns
{
  "directive": "gff-version",
  "value": "3"
}

parseDirective('##sequence-region ctg123 1 1497228\n')
// returns
{
  "directive": "sequence-region",
  "value": "ctg123 1 1497228",
  "seq_id": "ctg123",
  "start": "1",
  "end": "1497228"
}

comments

parseComment('# hi this is a comment\n')
// returns
{
  "comment": "hi this is a comment"
}

sequences

These come from any embedded ##FASTA section in the GFF3 file.

parseSequences(`##FASTA
>ctgA test contig
ACTGACTAGCTAGCATCAGCGTCGTAGCTATTATATTACGGTAGCCA`)[
  // returns
  {
    id: 'ctgA',
    description: 'test contig',
    sequence: 'ACTGACTAGCTAGCATCAGCGTCGTAGCTATTATATTACGGTAGCCA',
  }
]

API

ParseOptions

Parser options

disableDerivesFromReferences

Whether to resolve references to derives from features

Type: boolean

encoding

Text encoding of the input GFF3. default ‘utf8’

Type: BufferEncoding

parseFeatures

Whether to parse features, default true

Type: boolean

parseDirectives

Whether to parse directives, default false

Type: boolean

parseComments

Whether to parse comments, default false

Type: boolean

parseSequences

Whether to parse sequences, default true

Type: boolean

parseAll

Parse all features, directives, comments, and sequences. Overrides other parsing options. Default false.

Type: boolean

bufferSize

Maximum number of GFF3 lines to buffer, default 1000

Type: number

parseStream

Parse a stream of text data into a stream of feature, directive, comment, an sequence objects.

Parameters

options ParseOptions Parsing options (optional, default {})

Returns GFFTransform stream (in objectMode) of parsed items

parseStringSync

Synchronously parse a string containing GFF3 and return an array of the parsed items.

Parameters

str string GFF3 string
inputOptions ({disableDerivesFromReferences: boolean?, encoding: BufferEncoding?, bufferSize: number?} | undefined)? Parsing options

Returns Array<(GFF3Feature | GFF3Sequence)> array of parsed features, directives, comments and/or sequences

formatSync

Format an array of GFF3 items (features,directives,comments) into string of GFF3. Does not insert synchronization (###) marks.

Parameters

items Array<GFF3Item> Array of features, directives, comments and/or sequences

Returns string the formatted GFF3

formatStream

Format a stream of features, directives, comments and/or sequences into a stream of GFF3 text.

Inserts synchronization (###) marks automatically.

Parameters

options FormatOptions parser options (optional, default {})

Returns FormattingTransform

formatFile

Format a stream of features, directives, comments and/or sequences into a GFF3 file and write it to the filesystem.

Inserts synchronization (###) marks and a ##gff-version directive automatically (if one is not already present).

Parameters

stream Readable the stream to write to the file
writeStream Writable
options FormatOptions parser options (optional, default {})
filename the file path to write to

Returns Promise<null> promise for null that resolves when the stream has been written

About `util`

There is also a util module that contains super-low-level functions for dealing with lines and parts of lines.

// non-ES6
const util = require('@gmod/gff').default.util
// or, with ES6
import gff from '@gmod/gff'
const util = gff.util

const gff3Lines = util.formatItem({
  seq_id: 'ctgA',
  ...
}))

util

unescape
- Parameters
escape
- Parameters
escapeColumn
- Parameters
parseAttributes
- Parameters
parseFeature
- Parameters
parseDirective
- Parameters
formatAttributes
- Parameters
formatFeature
- Parameters
formatDirective
- Parameters
formatComment
- Parameters
formatSequence
- Parameters
formatItem
- Parameters
GFF3Attributes
GFF3FeatureLine
- seq_id
- source
- type
- start
- end
- score
- strand
- phase
- attributes
GFF3FeatureLineWithRefs
- child_features
- derived_features
GFF3Feature
GFF3Directive
- directive
- value
GFF3SequenceRegionDirective
- value
- seq_id
- start
- end
GFF3GenomeBuildDirective
- value
- source
- buildName
GFF3Comment
- comment
GFF3Sequence
- id
- description
- sequence

unescape

Unescape a string value used in a GFF3 attribute.

Parameters

stringVal string Escaped GFF3 string value

Returns string An unescaped string value

escape

Escape a value for use in a GFF3 attribute value.

Parameters

rawVal (string | number) Raw GFF3 attribute value

Returns string An escaped string value

escapeColumn

Escape a value for use in a GFF3 column value.

Parameters

rawVal (string | number) Raw GFF3 column value

Returns string An escaped column value

parseAttributes

Parse the 9th column (attributes) of a GFF3 feature line.

Parameters

attrString string String of GFF3 9th column

Returns GFF3Attributes Parsed attributes

parseFeature

Parse a GFF3 feature line

Parameters

line string GFF3 feature line

Returns GFF3FeatureLine The parsed feature

parseDirective

Parse a GFF3 directive line.

Parameters

line string GFF3 directive line

Returns (GFF3Directive | GFF3SequenceRegionDirective | GFF3GenomeBuildDirective | null) The parsed directive

formatAttributes

Format an attributes object into a string suitable for the 9th column of GFF3.

Parameters

attrs GFF3Attributes Attributes

Returns string GFF3 9th column string

formatFeature

Format a feature object or array of feature objects into one or more lines of GFF3.

Parameters

featureOrFeatures (GFF3FeatureLine | GFF3FeatureLineWithRefs | Array<(GFF3FeatureLine | GFF3FeatureLineWithRefs)>) A feature object or array of feature objects

Returns string A string of one or more GFF3 lines

formatDirective

Format a directive into a line of GFF3.

Parameters

directive GFF3Directive A directive object

Returns string A directive line string

formatComment

Format a comment into a GFF3 comment. Yes I know this is just adding a # and a newline.

Parameters

comment GFF3Comment A comment object

Returns string A comment line string

formatSequence

Format a sequence object as FASTA

Parameters

seq GFF3Sequence A sequence object

Returns string Formatted single FASTA sequence string

formatItem

Format a directive, comment, sequence, or feature, or array of such items, into one or more lines of GFF3.

Parameters

itemOrItems (GFF3FeatureLineWithRefs | GFF3Directive | GFF3Comment | GFF3Sequence | Array<(GFF3FeatureLineWithRefs | GFF3Directive | GFF3Comment | GFF3Sequence)>) A comment, sequence, or feature, or array of such items

Returns (string | Array<string>) A formatted string or array of strings

GFF3Attributes

A record of GFF3 attribute identifiers and the values of those identifiers

Type: Record<string, (Array<string> | undefined)>

GFF3FeatureLine

A representation of a single line of a GFF3 file

seq_id

The ID of the landmark used to establish the coordinate system for the current feature

Type: (string | null)

source

A free text qualifier intended to describe the algorithm or operating procedure that generated this feature

Type: (string | null)

type

The type of the feature

Type: (string | null)

start

The start coordinates of the feature

Type: (number | null)

end

The end coordinates of the feature

Type: (number | null)

score

The score of the feature

Type: (number | null)

strand

The strand of the feature

Type: (string | null)

phase

For features of type “CDS”, the phase indicates where the next codon begins relative to the 5′ end of the current CDS feature

Type: (string | null)

attributes

Feature attributes

Type: (GFF3Attributes | null)

GFF3FeatureLineWithRefs

Extends GFF3FeatureLine

A GFF3 Feature line that includes references to other features defined in their “Parent” or “Derives_from” attributes

child_features

An array of child features

Type: Array<GFF3Feature>

derived_features

An array of features derived from this feature

Type: Array<GFF3Feature>

GFF3Feature

A GFF3 feature, which may include multiple individual feature lines

Type: Array<GFF3FeatureLineWithRefs>

GFF3Directive

A GFF3 directive

directive

The name of the directive

Type: string

value

The string value of the directive

Type: string

GFF3SequenceRegionDirective

Extends GFF3Directive

A GFF3 sequence-region directive

value

The string value of the directive

Type: string

seq_id

The sequence ID parsed from the directive

Type: string

start

The sequence start parsed from the directive

Type: string

end

The sequence end parsed from the directive

Type: string

GFF3GenomeBuildDirective

Extends GFF3Directive

A GFF3 genome-build directive

value

The string value of the directive

Type: string

source

The genome build source parsed from the directive

Type: string

buildName

The genome build name parsed from the directive

Type: string

GFF3Comment

A GFF3 comment

comment

The text of the comment

Type: string

GFF3Sequence

A GFF3 FASTA single sequence

id

The ID of the sequence

Type: string

description

The description of the sequence

Type: string

sequence

The sequence

Type: string

License

MIT © Robert Buels

React Native FusionCharts

Welcome to the official GitHub repository for the React Native FusionCharts component! This component provides seamless bindings for the FusionCharts JavaScript Charting Library, allowing you to effortlessly integrate rich and interactive charts into your React Native projects.

Enhance your applications with our diverse range of charts designed to meet all your data visualization needs. Get started today and bring your data to life!

Important Links

Introduction

React Native FusionCharts version 6.0.0 is compatible with the following versions of Expo and React Native. While it is possible that version 6.0.0 may function with newer versions of React Native and Expo, it has only been tested up to React Native 74.5.

Expo SDK Versions	React Native Versions
47, 48, 49, 50 & 51	>=0.70.8 & <=0.74.5

Overview

To quickly integrate React Native FusionCharts, follow these essential steps. This process installs all required dependencies, allowing those already familiar with FusionCharts to get up and running quickly. If you are new to FusionCharts, referring the Getting Started section will be more helpful.

Initial Dependencies Installation: Begin by running the following command in your project directory to install the necessary dependencies:
```
npm i react-native-webview @notifee/react-native @react-native-camera-roll/camera-roll react-native-fs react-native-share
```
Installing React Native FusionCharts: Next, install the react-native-fusioncharts package:
```
npm install react-native-fusioncharts
```
iOS Setup: For iOS applications, navigate to your ios directory and execute:
```
pod install
```
Enabling Chart Export Functionality on iOS: To add export functionality for your charts in iOS, modify your info.plist file by adding the following code to request photo library access:
```
<key>NSPhotoLibraryUsageDescription</key>
<string>Photo Library Access for downloading the chart</string>
```

Now that you have all essential components integrated into your project. You can now check the the quick start guide to render a chart or explore the APIs.

Getting Started

Requirements

Node.js, NPM/Yarn installed globally in your OS.

Installation

React Native FusionCharts can be integrated into applications using Expo tools or bare React Native environments.

Developing Applications with FusionCharts and Expo

Make sure you have Node.js and Git installed in your environment. Check the official Expo’s documentation for more details.
Run the following command in terminal to create a new application and navigate in the project directory. You can check here for more details on creating an new expo app.

npx create-expo-app FusionApp --template blank && cd FusionApp

Install React Native FusionCharts:

npm i react-native-fusioncharts

Install dependencies for React Native FusionCharts:

npm i react-native-webview @notifee/react-native @react-native-camera-roll/camera-roll react-native-fs react-native-share

Replace the code in the “App.js” file and replace it with the example here
Run the npx expo start in the project directory and expo should generate a QR-code that you can scan from your iOS camera app to open Expo Go or directly from the Expo Go app in an android device. Make sure your device and system is on the same network.
If everything went well so far then you should be able to see FusionCharts sample column2D chart on the app.

Creating an App with FusionCharts using React Native CLI

This guide is for building an app from scratch using React Native without any framework. If you already have an existing app, then please check the overview section and examples to setup FusionCharts.

The initial steps(1-5) to setup the React Native app is taken from the official React Native guide to setup a new app. Please refer to the React Native documentation in case you encounter an issue setting up your app.

If you previously installed a global react-native-cli package, please remove it as it may cause unexpected issues:

npm uninstall -g react-native-cli @react-native-community/cli

Use React Native Community CLI to generate a new project.

npx @react-native-community/cli@latest init FusionApp && cd FusionApp

Install React Native FusionCharts:

npm i react-native-fusioncharts

Install dependencies for React Native FusionCharts:

npm i react-native-webview @notifee/react-native @react-native-camera-roll/camera-roll react-native-fs react-native-share

Start Metro (Metro is the JavaScript build tool for React Native. To start the Metro development server, run the following from your project folder)

npm start

Start your application. Let Metro Bundler run in its own terminal. Open a new terminal inside your React Native project folder. Run the following:

npm run android
# or
npm run ios

If everything is set up correctly, you should see your new app running in your Android/iOS emulator shortly.
Now open App.tsx in your text editor of choice and add chart samples from the quick start section to render FusionCharts in your app. You can find more chart samples in our official documentation

Quick Start

Include the react-native-fusioncharts library as follows:

The App.js file:

import React from "react";
import { Text, View } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

const Chart = () => {
  const chartData = [
    { label: "Venezuela", value: "250" },
    { label: "Saudi", value: "260" },
    { label: "Canada", value: "180" },
    { label: "Iran", value: "140" },
    { label: "Russia", value: "115" },
    { label: "UAE", value: "100" },
    { label: "US", value: "30" },
    { label: "China", value: "30" },
  ];
  const chartConfig = {
    type: "column2D",
    width: "300",
    height: "400",
    dataFormat: "json",
    dataSource: {
      chart: {
        caption: "Countries With Most Oil Reserves [2017-18]",
        subCaption: "In MMbbl = One Million barrels",
        xAxisName: "Country",
        yAxisName: "Reserves (MMbbl)",
        numberSuffix: "K",
        theme: "fusion",
        exportEnabled: 1, // to enable the export chart functionality
      },
      data: chartData,
    },
  };
  return (
    <View
      style={{
        flex: 1,
        justifyContent: "center",
        alignItems: "center",
        marginTop: 50,
      }}
    >
      <Text>Fusioncharts</Text>
      <ReactNativeFusionCharts chartConfig={chartConfig} />
    </View>
  );
};
export default Chart;

Event Handling

In this sample we are attaching dataplotclick event in the chart.

import { StatusBar } from "expo-status-bar";
import { StyleSheet, Text, View, Alert } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

export default function App() {
  const chartData = [
    { label: "Venezuela", value: "250" },
    { label: "Saudi", value: "260" },
    { label: "Canada", value: "180" },
    { label: "Iran", value: "140" },
    { label: "Russia", value: "115" },
    { label: "UAE", value: "100" },
    { label: "US", value: "30" },
    { label: "China", value: "30" },
  ];
  const chartConfig = {
    type: "column2D",
    width: "300",
    height: "400",
    dataFormat: "json",
    dataSource: {
      chart: {
        caption: "Countries With Most Oil Reserves [2017-18]",
        subCaption: "In MMbbl = One Million barrels",
        xAxisName: "Country",
        yAxisName: "Reserves (MMbbl)",
        numberSuffix: "K",
        theme: "fusion",
        exportEnabled: 1, // to enable the export chart functionality
      },
      data: chartData,
    },
  };
  const events = {
    // Add your events method here:
    // Event name should be in small letters.
    dataplotclick: (e, a) => {
      Alert.alert(`You clicked on ${e.data.categoryLabel}`);
    },
  };
  return (
    <View style={styles.container}>
      <Text>Fusioncharts</Text>
      <ReactNativeFusionCharts chartConfig={chartConfig} events={events} />
      <StatusBar style="auto" />
    </View>
  );
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    backgroundColor: "#fff",
    alignItems: "center",
    justifyContent: "center",
    marginTop: 50,
  },
});

API Integration

In this sample we can change the chart type dynamically using chart APIs.

import React, { Component } from "react";
import { Platform, StyleSheet, Text, View, Button, Alert } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

export default class ChartRunTime extends Component {
  constructor(props) {
    super(props);
    // Create a property(e.g: apiCaller) which will get attached to a function
    // where you can pass Chart API methods you want to run.
    this.apiCaller = null;
    const chartConfig = {
      type: "column2d",
      width: "100%",
      height: "100%",
      dataFormat: "json",
      dataSource: {
        chart: {
          caption: "Recommended Portfolio Split",
          subCaption: "For a net-worth of $1M",
          showValues: "1",
          showPercentInTooltip: "0",
          numberPrefix: "$",
          enableMultiSlicing: "1",
          theme: "fusion",
          exportEnabled: 1,
        },
        data: [
          {
            label: "Equity",
            value: "300000",
          },
          {
            label: "Debt",
            value: "230000",
          },
          {
            label: "Bullion",
            value: "180000",
          },
          {
            label: "Real-estate",
            value: "270000",
          },
          {
            label: "Insurance",
            value: "20000",
          },
        ],
      },
    };

    this.state = {
      chartConfig,
      chartType: "",
    };
  }

  changeType(type) {
    this.setState({ chartType: type }, () => {
      // Chart instance is available here.
      // Passing js code to run chart api method.
      this.apiCaller(`chartType('${type}')`); // This method accepts js code in string.
    });
  }

  // Bind the argument from onInitialized with the property you created in your constructor
  bindApiCaller(caller) {
    // Now this.apiCaller will be a function where you can pass js code for the WebView
    // to access the chart Object. See the method changeType.
    this.apiCaller = caller;
    if (this.state.chartType === "") this.setState({ chartType: this.state.type });
  }

  render() {
    return (
      <View style={styles.container}>
        <Text style={styles.header}>Change chart type at runtime</Text>
        <View style={styles.chartContainer}>
          <ReactNativeFusionCharts
            chartConfig={this.state.chartConfig}
            onInitialized={(caller) => {
              this.bindApiCaller(caller);
            }}
          />
        </View>
        <Text style={styles.info}>Press button to change chart type</Text>
        <View style={styles.buttonContainer}>
          <Button
            disabled={this.state.chartType === "" || this.state.chartType == "column2d"}
            style={{ margin: 8 }}
            title="Column2D"
            onPress={() => this.changeType("column2d")}
          />
          <Button
            disabled={this.state.chartType === "" || this.state.chartType == "pie2d"}
            title="Pie2D"
            onPress={() => this.changeType("pie2d")}
          />
          <Button
            disabled={this.state.chartType === "" || this.state.chartType == "bar2d"}
            title="Bar2D"
            onPress={() => this.changeType("bar2d")}
          />
        </View>
      </View>
    );
  }
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 10,
  },
  header: {
    fontWeight: "bold",
    fontSize: 20,
    textAlign: "center",
    paddingBottom: 10,
  },
  chartContainer: {
    height: 400,
    borderColor: "#000",
    borderWidth: 1,
  },
  buttonContainer: {
    padding: 10,
    display: "flex",
    justifyContent: "space-around",
    flexDirection: "row",
    alignItems: "center",
  },
  info: {
    fontSize: 16,
    textAlign: "center",
    marginTop: 5,
  },
});

Module Management

In this sample we can add the modules dynamically e.g gantt, timeseries, powercharts etc

import React, { Component } from "react";
import { StyleSheet, View } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

export default class App extends Component {
  constructor(props) {
    super(props);

    const chartConfig = {
      type: "gantt", // your chart type goes here
      width: "100%",
      height: "400",
      dataFormat: "json",
      dataSource: {
        // your data goes here
        // for gantt chart data please visit https://www.fusioncharts.com/dev/chart-attributes/gantt
      },
    };
    this.state = {
      chartConfig,
    };
  }

  render() {
    const modules = ["gantt"]; // module names goes here
    return (
      <View style={styles.container}>
        <View style={styles.chartContainer}>
          <ReactNativeFusionCharts chartConfig={this.state.chartConfig} modules={modules} />
        </View>
      </View>
    );
  }
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 10,
  },

  chartContainer: {
    height: "60%",
    borderColor: "#000",
    borderWidth: 1,
  },
});

In this sample we can add the theme modules dynamically e.g candy, carbon, gammel etc

import React, { Component } from "react";
import { Platform, StyleSheet, Text, View, Alert } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

export default class ListenEvents extends Component {
  constructor(props) {
    super(props);

    const chartConfig = {
      type: "column2d",
      width: "100%",
      height: "100%",
      dataFormat: "json",
      dataSource: {
        chart: {
          caption: "Countries With Most Oil Reserves [2017-18]",
          subCaption: "In MMbbl = One Million barrels",
          xAxisName: "Country",
          yAxisName: "Reserves (MMbbl)",
          numberSuffix: "K",
          theme: "carbon", // your theme name goes here
          exportEnabled: 1,
        },
        data: [
          { label: "Venezuela", value: "290" },
          { label: "Saudi", value: "260" },
          { label: "Canada", value: "180" },
          { label: "Iran", value: "140" },
          { label: "Russia", value: "115" },
          { label: "UAE", value: "100" },
          { label: "US", value: "30" },
          { label: "China", value: "30" },
        ],
      },
    };

    this.state = {
      chartConfig,
    };
  }

  render() {
    const modules = ["carbon"]; // theme module name
    return (
      <View style={styles.container}>
        <Text style={styles.header}>Listen to events from chart</Text>
        <View style={styles.chartContainer}>
          <ReactNativeFusionCharts chartConfig={this.state.chartConfig} modules={modules} />
        </View>
      </View>
    );
  }
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 10,
  },
  header: {
    fontWeight: "bold",
    fontSize: 20,
    textAlign: "center",
    paddingBottom: 10,
  },
  chartContainer: {
    height: 400,
    borderColor: "#000",
    borderWidth: 1,
  },
});

Setting Up Licenses

If you are using a licensed verison of fusioncharts and have a valid license key, add the license object by either creating a new file with your license configuration inside it and import it in app.js or add ‘global.licenseConfig’ object to the app.js file as shown below

import React, { Component } from "react";
import { StyleSheet, View } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

global.licenseConfig = {
  key: "your key goes here",
  creditLabel: false, // true/false to show/hide watermark respectively
};
export default class App extends Component {
  constructor(props) {
    super(props);

    const chartConfig = {
      type: "column2D",
      width: "100%",
      height: "400",
      dataFormat: "json",
      dataSource: {
        chart: {
          caption: "Countries With Most Oil Reserves [2017-18]",
          subCaption: "In MMbbl = One Million barrels",
          xAxisName: "Country",
          yAxisName: "Reserves (MMbbl)",
          numberSuffix: "K",
          theme: "fusion",
          exportEnabled: 1,
        },
        data: [
          { label: "Venezuela", value: "250" },
          { label: "Saudi", value: "260" },
          { label: "Canada", value: "180" },
          { label: "Iran", value: "140" },
          { label: "Russia", value: "115" },
          { label: "UAE", value: "100" },
          { label: "US", value: "30" },
          { label: "China", value: "30" },
        ],
      },
    };
    this.state = {
      chartConfig,
    };
  }

  render() {
    return (
      <View style={styles.container}>
        <View style={styles.chartContainer}>
          <ReactNativeFusionCharts chartConfig={this.state.chartConfig} />
        </View>
      </View>
    );
  }
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 10,
  },

  chartContainer: {
    height: "60%",
    borderColor: "#000",
    borderWidth: 1,
  },
});

FusionTime Integration

From fusioncharts@3.13.3-sr.1 and react-native-fusioncharts@3.0.0, You can visualize timeseries data easily on react.

Learn more about FusionTime here.

Example Integration

// In App.js
import React, { Component } from "react";
import { AppRegistry, StyleSheet, Text, View, Platform } from "react-native";
import ReactNativeFusionCharts from "react-native-fusioncharts";

export default class App extends Component {
  constructor(props) {
    super(props);

    const chartConfig = {
      type: "timeseries",
      width: "100%",
      height: "100%",
      dataFormat: "json",
      dataSource: {
        data: null,
        caption: {
          text: "Sales Analysis",
        },
        subcaption: {
          text: "Grocery",
        },
        yAxis: [
          {
            plot: {
              value: "Grocery Sales Value",
              type: "line",
            },
            format: {
              prefix: "$",
            },
            title: "Sale Value",
          },
        ],
      },
      schemaJson: null,
      dataJson: null,
    };

    this.state = {
      chartConfig,
    };
  }

  componentDidMount() {
    this.fetchDataAndSchema();
  }

  fetchDataAndSchema() {
    const jsonify = (res) => res.json();
    const dFetch = fetch(
      "https://s3.eu-central-1.amazonaws.com/fusion.store/ft/data/line-chart-with-time-axis-data.json"
    ).then(jsonify);
    // This is the remote url to fetch the schema.
    const sFetch = fetch(
      "https://s3.eu-central-1.amazonaws.com/fusion.store/ft/schema/line-chart-with-time-axis-schema.json"
    ).then(jsonify);
    Promise.all([dFetch, sFetch]).then((res) => {
      const data = res[0];
      const schema = res[1];
      const updatedChartConfig = { ...this.state.chartConfig, dataJson: data, schemaJson: schema };
      this.setState({ chartConfig: updatedChartConfig });
    });
  }

  render() {
    const modules = ["timeseries"];

    return (
      <View style={styles.container}>
        <Text style={styles.heading}>FusionCharts Integration with React Native</Text>
        <View style={styles.chartContainer}>
          <ReactNativeFusionCharts chartConfig={this.state.chartConfig} modules={modules} />
        </View>
      </View>
    );
  }
}

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 10,
  },
  heading: {
    fontSize: 20,
    textAlign: "center",
    marginBottom: 10,
  },
  chartContainer: {
    height: 500,
  },
});

Going Beyond Charts

Explore 20+ pre-built business specific dashboards for different industries like energy and manufacturing to business functions like sales, marketing and operations here.
See Data Stories built using FusionCharts’ interactive JavaScript visualizations and learn how to communicate real-world narratives through underlying data to tell compelling stories.

Contributor Guidelines

#  Clone repo
git clone git@github.com:fusioncharts/react-native-fusioncharts.git
cd react-native-fusioncharts

# Install dependencies
npm install

# Run
npm run start

# Build
npm run build

# Publish
npm publish

License Information

The FusionCharts React Native integration component is open-source and distributed under the terms of the MIT/X11 License. However, you will need to download and include FusionCharts library in your page separately, which has a separate license.

Depreciated

Project is no longer able to grab home data from Redfin.

Real Estate Heat Map /Historic Price Trend Indicator.

This is an individual project for nation wide heat map of the U.S. by county, and can be viewed downed to the city for more accurate representation and details on a city level.

Currently a working progress. Main issue is the amount of data to be process (CT alone has 1015948 known addresses) ,and as of right now after modifying Redfin unofficial api (https://pypi.org/project/redfin/) and running the code in parallel give us about 40-60 address computed per second. This is after removing several duplicate addresses and addresses that are likely to be apartments. Without a backing of an organization to use Zillow API for faster request time or more request it is feasibly impossible to run the code alone on a personal computer for a nation wide scale.

A more likely option is to only keep track of a city or state instead of the entire U.S. if used for personal reasons.

Tech Stack: Python3, SQLite3, Node.js, Express.js

Prequiste

Anaconda
Vscode
Python3
Node.js
some kind of Zip file unpacker
Npm
Pip

Everything should be installed in an Anaconda env.

Install libraries

npm install express sqlite3 body-parser child_process gridstack  tablefilter

pip install requests aiohttp tqdm pandas numpy tensorflow scikit-learn

Intial Setup

Download the region of realestate to look at from openAddress.io; this will reguire you to have an account with openAddress.io. Would recommend only downloading the files for the region you want to look at as the files downloaded are quite large and with file processing and creation the code size will be quite large (rough estimate with all states/regions ~150gb).

Unpack the downloaded files and drop them in \Realestae\downloads folder. Run the following command in the root directory. This will start collecting data from state you want to look at, depending on the state this will take a while. A 100,000 address takes about 42 minutes this is with 32gb ram. The code can be ran in chunks so if you are not able to run the code for several hours you can run the code in increments of 100,000(more or less) untill you have grab all the address from the state. If ran with 100,000 the first time, then to grab the next 100,000 you will need to modify the -i flag to be “-i 200000”.

python3 setup.py -i 1000 -n ct -f

-i flag for how many address to be proccess(Required). The value after is the number of addresses to be processed.

-n flag for the state to be proccess(Required). The value after is the state name abbreviation of addresses to be processed.

-f flag to convert the file and remove unnecessary addresses. Only need to use the flag once for the first run of a new state(Optional).

Dispaly Web App

Will start the webpage with all the data collected and display the chart.

npm run start

Price Prediction

It is recommended that you have collected all the addresses from setup.py before executing the code below as the model will perform better with more data.

python3 ml_setup.py [city_name]

Replace [city_name] with a name of a city from the data you have collected.

To be implemented

Add assets and restructure webpage from/with Figma
Hosting the code at Vercel with a demo database to grab property data
Containarize code
Add feature for process_geojson_data() to write in batches while collecting data instead of after
Connect front end to back end machine learning price prediction
Create enviroment file
Testing modules

Ionic 2 Conference Application

This is purely a demo of Ionic 2 with TypeScript. It is still in development.

Important!

There is not an actual Ionic Conference at this time. This project is just to show off Ionic 2 components in a real-world application. Please go through the steps in CONTRIBUTING.md before submitting an issue.

Getting Started

Clone this repository.
Want to use TypeScript? Both the master branch and the typescript branch now use TypeScript.
Run npm install from the project root.
Install the ionic CLI (npm install -g ionic)
Run ionic serve in a terminal from the project root.
Profit

Note: Is your build slow? Update npm to 3.x: npm install -g npm.

Contributing

See CONTRIBUTING.md 🎉👍

Use Cases

Action Sheet – [ template | code ]
Alert – [ code ]
Cards – [ template ]
Datetime – [ template ]
Grid – [ template ]
Inputs – [ template ]
Items (Sliding) – [ template | code ]
Menu – [ template | code ]
Modal – [ template | code ]
Searchbar – [ template | code ]
Segment – [ template | code ]
Slides – [ template |
Sticky headers – [ template ]
Tabs – [ template | code ]
Toggle – [ template ] code ]
Using Angular HTTP for JSON – [ code | usage ]

App Preview

All app preview screenshots were taken by running ionic serve --lab on a retina display.

Schedule Page
About Page
To see more images of the app, check out the screenshots directory!

File Structure of App

ionic-conference-app/
├-- .github/                            * GitHub files
│   ├── CONTRIBUTING.md                 * Documentation on contributing to this repo
│   └── ISSUE_TEMPLATE.md               * Template used to populate issues in this repo
|
|-- resources/
|
|-- src/
|    |-- app/
|    |    ├── app.component.ts
|    |    └── app.module.ts
|    |    └── app.template.html
|    |    └── main.dev.ts
|    |    └── main.prod.ts
|    |
|    |-- assests/
|    |    ├── data/
|    |    |    └── data.json
|    |    |
|    |    ├── fonts/
|    |    |     ├── ionicons.eot
|    |    |     └── ionicons.svg
|    |    |     └── ionicons.ttf
|    |    |     └── ionicons.woff
|    |    |     └── ionicons.woff2
|    |    |
|    |    ├── img/
|    |
|    |-- pages/                          * Contains all of our pages
│    │    ├── about/                     * About tab page
│    │    │    ├── about.html            * AboutPage template
│    │    │    └── about.ts              * AboutPage code
│    │    │    └── about.scss            * AboutPage stylesheet
│    │    │
│    │    ├── account/                   * Account page
│    │    │    ├── account.html          * AccountPage template
│    │    │    └── account.ts            * AccountPage code
│    │    │    └── account.scss          * AccountPage stylesheet
│    │    │
│    │    │── login/                     * Login page
│    │    │    ├── login.html            * LoginPage template
│    │    │    └── login.ts              * LoginPage code
│    │    │    └── login.scss            * LoginPage stylesheet
│    │    │
│    │    │── map/                       * Map tab page
│    │    │    ├── map.html              * MapPage template
│    │    │    └── map.ts                * MapPage code
│    │    │    └── map.scss              * MapPage stylesheet
│    │    │
│    │    │── schedule/                  * Schedule tab page
│    │    │    ├── schedule.html         * SchedulePage template
│    │    │    └── schedule.ts           * SchedulePage code
│    │    │    └── schedule.scss         * SchedulePage stylesheet
│    │    │
│    │    │── schedule-filter/            * Schedule Filter page
│    │    │    ├── schedule-filter.html   * ScheduleFilterPage template
│    │    │    └── schedule-filter.ts     * ScheduleFilterPage code
│    │    │    └── schedule-filter.scss   * ScheduleFilterPage stylesheet
│    │    │
│    │    │── session-detail/            * Session Detail page
│    │    │    ├── session-detail.html   * SessionDetailPage template
│    │    │    └── session-detail.ts     * SessionDetailPage code
│    │    │
│    │    │── signup/                    * Signup page
│    │    │    ├── signup.html           * SignupPage template
│    │    │    └── signup.ts             * SignupPage code
│    │    │
│    │    │── speaker-detail/            * Speaker Detail page
│    │    │    ├── speaker-detail.html   * SpeakerDetailPage template
│    │    │    └── speaker-detail.ts     * SpeakerDetailPage code
│    │    │    └── speaker-detail.scss   * SpeakerDetailPage stylesheet
│    │    │
│    │    │── speaker-list/              * Speakers tab page
│    │    │    ├── speaker-list.html     * SpeakerListPage template
│    │    │    └── speaker-list.ts       * SpeakerListPage code
│    │    │    └── speaker-list.scss     * SpeakerListPage stylesheet
│    │    │
│    │    │── tabs/                      * Tabs page
│    │    │    ├── tabs.html             * TabsPage template
│    │    │    └── tabs.ts               * TabsPage code
│    │    │
│    │    └── tutorial/                  * Tutorial Intro page
│    │         ├── tutorial.html         * TutorialPage template
│    │         └── tutorial.ts           * TutorialPage code
│    │         └── tutorial.scss         * TutorialPage stylesheet
|    |
│    ├── providers/                      * Contains all Injectables
│    │     ├── conference-data.ts        * ConferenceData code
│    │     └── user-data.ts              * UserData code
│    ├── theme/                          * App theme files
|    |     ├── variables.scss            * App Shared Sass Variables
|    |
|    |-- index.html
|
|-- www/
|    ├── assets/
|    |    ├── data/
|    |    |    └── data.json
|    |    |
|    |    ├── fonts/
|    |    |     ├── ionicons.eot
|    |    |     └── ionicons.svg
|    |    |     └── ionicons.ttf
|    |    |     └── ionicons.woff
|    |    |     └── ionicons.woff2
|    |    |
|    |    ├── img/
|    |
|    └── build/
|    └── index.html
|
├── .editorconfig                       * Defines coding styles between editors
├── .gitignore                          * Example git ignore file
├── LICENSE                             * Apache License
├── README.md                           * This file
├── config.xml                          * Cordova configuration file
├── ionic.config.json                   * Ionic configuration file
├── package.json                        * Defines our JavaScript dependencies
├── tsconfig.json                       * Defines the root files and the compiler options
├── tslint.json                         * Defines the rules for the TypeScript linter

EARNET Project

The ICO contracts of EARNET project.
If you have any questions, please connect with us on our social channels.

Contracts

EarnetToken
- The contract of the standard token.
Earnet1stPresale
- The contract of the 1st pre sale, non lock up time.
Earnet1st1mPresale
- The contract of the 1st pre sale, lock up for one month from the exchange listing.
Earnet1st3mPresale
- The contract of the 1st pre sale, lock up for three months from the exchange listing.
Earnet1st6mPresale
- The contract of the 1st pre sale, lock up for six months from the exchange listing.
Earnet2ndPresale
- The contract of the 2nd pre sale, non lock up time.
Earnet2nd1mPresale
- The contract of the 2nd pre sale, lock up for one month from the exchange listing.
Earnet2nd3mPresale
- The contract of the 2nd pre sale, lock up for three months from the exchange listing.
Earnet2nd6mPresale
- The contract of the 2nd pre sale, lock up for six months from the exchange listing.
EarnetCrowdsale
- The contract of the crowd sale, non lock up time.
Earnet1mCrowdsale
- The contract of the crowd sale, lock up for one month from the exchange listing.
Earnet3mCrowdsale
- The contract of the crowd sale, lock up for three months from the exchange listing.
Earnet6mCrowdsale
- The contract of the crowd sale, lock up for six months from the exchange listing.
EarnetTokwnPool
- The contract of the lock up token for one month.
Earnet3mTokwnPool
- The contract of the lock up token for three months.
Earnet6mTokwnPool
- The contract of the lock up token for six months.
EarnetWhitelist
- The contract that records whitelist into the storage.
EarnetWhitelistedCrowdsale
- The contract which extends in the sale contract in order to use the whitelist.

Methods

EarnetToken

ID	Name	Scope	param	return value	Note
1	name	public	–	–	ERC20
2	symbol	public	–	–	ERC20
3	decimals	public	–	–	ERC20
4	totalSupply	public	–	int	ERC20
5	balanceOf	public	address	int	ERC20
6	transfer	public	to_address, int	bool	ERC20
7	transferFrom	public	to_address, from_adress, int	bool	ERC20
8	approve	public	–	–	ERC20
9	allowance	public	–	–	ERC20
10	mint	public	–	–	Zeppelin-solidity
11	burn	public	–	–	Zeppelin-solidity

Earnet1stPresale, Earnet1st1mPresale, Earnet1st3mPresale, Earnet1st6mPresale, Earnet2ndPresale, Earnet2nd1mPresale, Earnet2nd3mPresale, Earnet2nd6mPresale, EarnetCrowdsale, Earnet1mCrowdsale, Earnet3mCrowdsale, Earnet6mCrowdsale

ID	Name	Scope	param	return value	Note
1	crowdsale	public	–	–
2	buyTokens	public	address	int
3	pause	public	–	–	Zeppelin-solidity
4	unpause	public	–	–	Zeppelin-solidity
5	hasClosed	public	–	bool	Zeppelin-solidity
6	setVolume	external	_weiAmount, _rate

EarnetTokenPool, Earnet3mTokenPool, Earnet6mTokenPool,

ID	Name	Scope	param	return value
1	deposit	public	address, amount	bool
2	contributable	public	address	bool
3	checkdeposit	public		bool
4	withdraw	public	address, wallet	bool
5	unlock	public
6	managerble	public	address

EarnetWhitelist

ID	Name	Scope	param	return value
1	addToWhitelist	public	address
2	addManyToWhitelist	public	address
3	removeFromWhitelist	public	address
4	removeManyFromWhitelist	public	address
5	isWhitelisted	public	address	bool

Prerequisite

Language

solidity 0.4.23

Framework

truffle 4.1.1

Library

zeppelin-solidity 1.9.0

Package manager

npm 6.1.0

Test tool

ropsten
ganache 1.1.0-beta.0

Ethereum client

Geth 1.8.3

Version manager

Github

License

GPL-3.0

Code audit

Code audit company
- Tecotec Co.Ltd.
Code audit date
- 05 Nov, 2018
- Earnet Token Contract Code Audit Report

restaurant-location-search-api 🍔🍹

A Node.js package that serves as an unofficial API wrapper, providing a unified interface to fetch restaurant locations from various chains without the need for Google Maps API, making it a cost-free solution. This package leverages the specific, unofficial APIs of supported restaurants such as McDonald’s, Wendy’s, Chipotle, Burger King, Popeyes, and Taco Bell, offering a simplified way to retrieve locations based on latitude and longitude. It’s designed for developers who need to integrate restaurant location functionalities into their applications seamlessly, with plans to expand support to more restaurant chains in the future.

Features

Fetch the nearest or a list of restaurant locations based on coordinates.
Supports multiple restaurant chains.
Option to specify search radius and maximum number of results.
Handles responses in various formats, including JSON and XML, automatically decoding compressed responses.
Search sites for more info ( coming soon )

Installation

Use npm to install restaurant-location-search-api:

npm install restaurant-location-search-api

Usage

After installation, require the package in your Node.js project and use the functions provided to fetch restaurant locations.

const getLocations = require('restaurant-location-search-api');

// Fetch nearest McDonald's location
getLocations('tacoBell', { lat: 40.712776, long: -74.005974 }, '1000', '1', true)
  .then(fetchedLocations => { console.log( fetchedLocations ) } )
  .catch(console.error);

// Fetch locations for other supported restaurants
getLocations('burgerKing', { lat: 40.712776, long: -74.005974 }, '5000', '5')
  .then(fetchedLocations => { console.log( fetchedLocations ) } )
  .catch(console.error);

API

`getLocations(spotName, geoObject, radius, maxResults, nearbyOnly=false)`

Fetches restaurant locations based on the specified parameters.

spotName: Name of the restaurant chain (e.g., ‘mcdonalds’, ‘wendys’).
geoObject: Object with lat (latitude) and long (longitude) properties.
radius: Search radius in kilometers.
maxResults: Maximum number of results to return.
nearbyOnly (optional): Set to true to fetch only the nearest location. ( might not work for all restuarants )

Example JSON Response

Below is an example of the JSON response returned by the getLocations function for Taco Bell locations:

{
  "nearByStores": [
    {
      "storeStatus": "openNow",
      "pickupStoreStatusForLocation": "Activated",
      "phoneNumber": "+12122330848",
      "storeNumber": "035336",
      "timeZone": "GMT-05:00",
      "roundUpFlag": true,
      "todayBusinessHours": {
        "openTime": "07:00",
        "closeTime": "23:00"
      },
      "delivery": true,
      "address": {
        "streetAddress": "123 Example St",
        "city": "New York",
        "state": "NY",
        "zipCode": "10001"
      },
      "geoPoint": {
        "latitude": 40.712776,
        "longitude": -74.005974
      },
      "formattedDistance": "0.30 Miles"
    },
    {
      "storeStatus": "openNow",
      "pickupStoreStatusForLocation": "Activated",
      "phoneNumber": "+16468239315",
      "storeNumber": "035828",
      "timeZone": "GMT-05:00",
      "roundUpFlag": true,
      "todayBusinessHours": {
        "openTime": "07:00",
        "closeTime": "22:00"
      },
      "delivery": true,
      "address": {
        "streetAddress": "456 Another Rd",
        "city": "New York",
        "state": "NY",
        "zipCode": "10002"
      },
      "geoPoint": {
        "latitude": 40.715776,
        "longitude": -74.015974
      },
      "formattedDistance": "1.1 Miles"
    }
    // Additional stores omitted for brevity
  ]
}

Supported Restaurants

McDonald’s
Wendy’s
Chipotle
Burger King
Popeyes
Taco Bell

More coming soon!

Contributing

Contributions are welcome! If you’d like to add support for more restaurant chains or improve the package, please open a pull request.

Category: Blog

camels_netcdf

CAMELS dataset in NetCDF/Feather formats

Motivation

Usage

Methodology

Example Plots

Contributions

stwo-brainfuck

stwo-brainfuck

CLI – Installation

Build from Source

CLI – Usage

Example usage

Prove

Verify

Visualizing the memory

Project Objectives

Design choices

Brainfuck VM

Acknowledgements

Footnotes

Museum-mui

Museum Site

Motivation

why?

overview

Frontend:

Frontend Folder structure

Frontend Routes ( with Images )

Other component

Loading Screen display

Login and Sign up

Backend

folder structure

hosting platform

Contribution?

Available Scripts

npm start

npm test

npm run build

MiniPacket

gff-js

@gmod/gff

Install

Usage

Object format

features

directives

comments

sequences

API

Table of Contents

ParseOptions

disableDerivesFromReferences

encoding

parseFeatures

parseDirectives

parseComments

parseSequences

parseAll

bufferSize

parseStream

Parameters

parseStringSync

Parameters

formatSync

Parameters

formatStream

Parameters

formatFile

Parameters

About util

util

Table of Contents

unescape

Parameters

escape

Parameters

escapeColumn

`npm start`

`npm test`

`npm run build`

About `util`