therohk

opted_type	desc
n.	noun
a.	adjective
v. t.	verb transitive
v. i.	verb intransitive
adv.	adverb
pl.	noun plural
n. pl.	noun plural
superl.	adjective superlative

therohk

[{"atomic":"1","symbol":"H","weight":"1.008","electronstring":"1s1","series":"Nonmetal","melt":"14.01","boil":"20.28","electroneg":"2.20","valence":"1","oxidation":"-1c,1c","radius":{"calculated":"53","empirical":"25","covalent":"37","vanderwaals":"120"},"discover":"1766","density":{"stp":"0.0899"},"affinity":"72.8","conductivity":{"thermal":"0.1805"},"abundance":{"universe":"75","solar":"75","meteor":"2.4","crust":"0.15","ocean":"11","human":"10"},"heat":{"specific":"14300","vaporization":"0.452","fusion":"0.558"},"ionize":{"1":"1312.0"},"expandedconfig":"1s1","electrons":[1],"quantum":{"l":0,"m":0,"n":1},"isotopes":7},
{"atomic":"2","symbol":"He","weight":"4.002602","electronstring":"1s2","series":"Noble","boil":"4.22","valence":"0","radius":{"calculated":"31","covalent":"32","vanderwaals":"140"},"discover":"1895","density":{"stp":"0.1785"},"affinity":"0","conductivity":{"thermal":"0.1513"},"abundance":{"universe":"23","solar":"23","crust":"5.5e-7","ocean":"7.2e-10"},"heat":{"specific":"5193.1","vaporizatio

therohk

public static void main(String[] args) {

    DataSet linkSet = new DataSet();
    linkSet.getHeaders().setHeaders("source_node_id", "target_node_id");

    DataSet nodeSet = new DataSet();
    nodeSet.getHeaders().setHeaders("node_id", "node_name", "child_nodes", "leaf_node", "tolorg_link", "extinct", "confidence", "phylesis");

    try {
        Connection connection = HttpConnection.connect("http://tolweb.org/");

therohk

// Version 1.8.1 Copyright 2020 Rohit Kulkarni
(function(global, factory) {
  typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() :
  typeof define === 'function' && define.amd ? define(factory) :
  (global.versor = factory());
}(this, (function() {'use strict';

var acos = Math.acos,
    asin = Math.asin,
    atan2 = Math.atan2,

therohk

package com.therohk.gist;

import java.math.BigInteger;
import java.util.HashSet;
import java.util.Iterator;
import java.util.Set;

public final class BaseCounterGist implements Iterator<String> {
    //-------------------------------------------------------------------------
    private static final String charset26 = "ABCDEFGHIJKLMNOPQRSTUVWXYZ";

therohk

[{"latitude": 23.84, "longitude": 91.27, "city":"agartala" },
{ "latitude": 27.19, "longitude": 78.01, "city":"agra" },
{ "latitude": 23.03, "longitude": 72.58, "city":"ahmedabad" },
{ "latitude": 26.45, "longitude": 74.64, "city":"ajmer" },
{ "latitude": 25.45, "longitude": 81.84, "city":"allahbad" },
{ "latitude": 16.57, "longitude": 80.35, "city":"amaravati" },
{ "latitude": 31.64, "longitude": 74.87, "city":"amritsar" },
{ "latitude": 24.75, "longitude": 84.37, "city":"aurangabad" },
{ "latitude": 28.36, "longitude": 79.41, "city":"bareilly" },
{ "latitude": 12.97, "longitude": 77.56, "city":"bengaluru" },

therohk

plot_slice_freq = function(dfin, start, stend, include=c(), stem_flag=TRUE, floor_unit="halfyear", plot_name="_") {
# ---- publish-date-ungram-hertz
ungram_hz_inc <- dfin %>%
 subset(select=c(ungram,publish_date)) %>%
 mutate(Date = as.Date(substr(publish_date,1,8), format="%Y%m%d")) %>%
 filter(Date>=start & Date<=stend)
if(stem_flag) {
 ungram_hz_inc$ungram <- wordStem(ungram_hz_inc$ungram, language="english")
 include <- wordStem(include, language="english")
}

therohk

plot_ungram_tfidf = function(dfin, start, stend, slice_unit="year", nmin=2, ntop=10, ncol=3) {
# ---- publish-date-ungram-tfidf
ungram_tf_idf <- dfin %>%
 subset(select=c(ungram,publish_date)) %>%
 mutate(Date = as.Date(substr(publish_date,1,8), format="%Y%m%d")) %>%
 filter(Date>=start & Date<=stend) %>%
 mutate(time_slice = floor_date(Date, unit = slice_unit)) %>%
 mutate(time_slice = format(time_slice, "%Y-%m-%d")) %>%
 count(time_slice, ungram) %>%
 filter(between(n,nmin,max(n))) %>%

therohk

# ---- publish-date-bigram-tfidf
plot_bigram_tfidf <- function(dbin, start, stend, slice_unit="year", nmin=5, ntop=10, ncol=3) {
bigram_tf_idf <- dbin %>%
  subset(select=c(bigram,publish_date)) %>%
  mutate(Date = as.Date(substr(publish_date,1,8), format="%Y%m%d")) %>%
  filter(Date>=start & Date<=stend) %>%
  mutate(time_slice = floor_date(Date, unit = slice_unit)) %>%
  mutate(time_slice = format(time_slice, "%Y-%m-%d")) %>%
  count(time_slice, bigram) %>%
  filter(between(n, nmin, 10000)) %>%

therohk

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