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35 | <td><a href="./../../overview.html" title="Overview of library">Overview</a></td> |
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39 | <td >Directory</td> |
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47 | <td><a href="./../../idldoc-index.html" title="Index of files, routines, and parameters">Index</a></td> |
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74 | <a href="a_timecorrelate.html"><<prev file</a> | <a href="skewness_4d.html">next file >></a> <a href="c_timecorrelate.html" target="_TOP">view single page</a> | <a href="./../../index.html" target="_TOP">view frames</a> summary: fields | <a href="#routine_summary">routine</a> details: <a href="#routine_details">routine</a> |
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76 | </div> |
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77 | |
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79 | <div id="container"> |
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80 | |
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81 | <h1 class="directory"><a href="directory-overview.html">ToBeReviewed/STATISTICS/</a></h1> |
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82 | <h2 class="pro_file">c_timecorrelate.pro</h2> |
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83 | |
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84 | <div id="file_attr"> |
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85 | <dl> |
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86 | </dl> |
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87 | </div> |
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88 | |
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89 | <div id="file_comments"> |
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90 | |
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91 | |
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92 | This function computes the "time cross correlation" Pxy(L) or |
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93 | the "time cross covariance" between 2 arrays (this is some |
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94 | kind of <a href="/Applications/itt/idl64/help/online_help/C_CORRELATE.html">C_CORRELATE</a> but for multidimensional arrays) as a |
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95 | function of the lag (L). |
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96 | </div> |
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97 | |
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98 | |
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99 | |
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100 | |
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101 | |
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102 | |
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103 | |
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104 | |
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105 | <div id="routine_summary"> |
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106 | <h2>Routine summary</h2> |
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107 | |
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108 | <dl> |
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109 | |
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110 | <dt><p><a href="#_timecross_cov"><span class="result">result = </span>timecross_cov(<span class="result">xd, yd, m, nt, ndim</span>, DOUBLE=<span class="result">DOUBLE</span>, ZERO2NAN=<span class="result">ZERO2NAN</span>)</a></p><dt> |
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111 | <dd> </dd> |
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112 | |
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113 | <dt><p><a href="#_c_timecorrelate"><span class="result">result = </span>c_timecorrelate(<span class="result">x, y, lag</span>, COVARIANCE=<span class="result">COVARIANCE</span>, DOUBLE=<span class="result">DOUBLE</span>)</a></p><dt> |
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114 | <dd> </dd> |
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115 | |
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116 | </dl> |
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117 | </div> |
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118 | |
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119 | |
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120 | <div id="routine_details"> |
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121 | |
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122 | |
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123 | <div class="routine_details" id="_timecross_cov"> |
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124 | |
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125 | <h2><a class="top" href="#container">top</a>timecross_cov <span class="categories"> |
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126 | Statistics |
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127 | </span></h2> |
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128 | |
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129 | <p class="header"> |
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130 | <span class="result">result = </span>timecross_cov(<span class="result"><a href="#_timecross_cov_param_xd">xd</a>, <a href="#_timecross_cov_param_yd">yd</a>, <a href="#_timecross_cov_param_m">m</a>, <a href="#_timecross_cov_param_nt">nt</a>, <a href="#_timecross_cov_param_ndim">ndim</a></span>, <a href="#_timecross_cov_keyword_DOUBLE">DOUBLE</a>=<span class="result">DOUBLE</span>, <a href="#_timecross_cov_keyword_ZERO2NAN">ZERO2NAN</a>=<span class="result">ZERO2NAN</span>)</p> |
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131 | |
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132 | <div class="comments"> |
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133 | </div> |
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134 | |
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135 | |
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136 | |
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137 | |
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138 | <h3>Parameters</h3> |
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139 | |
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140 | |
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141 | <h4 id="_timecross_cov_param_xd">xd |
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142 | |
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143 | |
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144 | |
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147 | |
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148 | |
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149 | |
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150 | </h4> |
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151 | |
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152 | <div class="comments"> |
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153 | </div> |
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154 | |
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155 | <h4 id="_timecross_cov_param_yd">yd |
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156 | |
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157 | |
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158 | |
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159 | |
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161 | |
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162 | |
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163 | |
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164 | </h4> |
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165 | |
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166 | <div class="comments"> |
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167 | </div> |
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168 | |
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169 | <h4 id="_timecross_cov_param_m">m |
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170 | |
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171 | |
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172 | |
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173 | |
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175 | |
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176 | |
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177 | |
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178 | </h4> |
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179 | |
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180 | <div class="comments"> |
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181 | </div> |
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182 | |
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183 | <h4 id="_timecross_cov_param_nt">nt |
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184 | |
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185 | |
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186 | |
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187 | |
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189 | |
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190 | |
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191 | |
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192 | </h4> |
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193 | |
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194 | <div class="comments"> |
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195 | </div> |
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196 | |
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197 | <h4 id="_timecross_cov_param_ndim">ndim |
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198 | |
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199 | |
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200 | |
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201 | |
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202 | |
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203 | |
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204 | |
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205 | |
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206 | </h4> |
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207 | |
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208 | <div class="comments"> |
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209 | </div> |
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210 | |
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211 | |
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212 | |
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213 | |
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214 | |
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215 | |
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216 | <h3>Keywords</h3> |
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217 | |
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218 | <h4 id="_timecross_cov_keyword_DOUBLE">DOUBLE |
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219 | |
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220 | |
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221 | |
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222 | |
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223 | |
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224 | |
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225 | |
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226 | |
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227 | </h4> |
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228 | |
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229 | <div class="comments"> |
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230 | If set to a non-zero value, computations are done in |
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231 | double precision arithmetic. |
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232 | </div> |
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233 | |
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234 | <h4 id="_timecross_cov_keyword_ZERO2NAN">ZERO2NAN |
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235 | |
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236 | |
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237 | |
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238 | |
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239 | |
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240 | |
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241 | |
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242 | |
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243 | </h4> |
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244 | |
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245 | <div class="comments"> |
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246 | </div> |
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247 | |
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248 | |
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249 | |
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250 | <h3>Examples</h3><div class="preformat"> |
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251 | </div> |
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252 | <h3>Version history</h3> |
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253 | |
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254 | <h4>Version</h4><div class="preformat"> |
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255 | $Id: c_timecorrelate.pro 371 2008-08-07 09:32:02Z pinsard $ |
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256 | </div> |
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257 | <h4>History</h4><div class="preformat"> |
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258 | </div> |
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259 | |
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260 | |
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261 | |
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270 | |
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271 | |
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272 | |
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273 | |
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274 | |
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275 | <h3>Statistics</h3> |
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276 | <table class="statistics"> |
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277 | <tr><td>McCabe cyclic</td><td> 7</td></tr> |
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278 | <tr><td>McCabe essential</td><td> 1</td></tr> |
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279 | <tr><td>McCabe modular design</td><td> 1</td></tr> |
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280 | </table> |
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281 | |
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282 | |
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283 | </div> |
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284 | |
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285 | |
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286 | <div class="routine_details" id="_c_timecorrelate"> |
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287 | |
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288 | <h2><a class="top" href="#container">top</a>c_timecorrelate <span class="categories"> |
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289 | Statistics |
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290 | </span></h2> |
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291 | |
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292 | <p class="header"> |
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293 | <span class="result">result = </span>c_timecorrelate(<span class="result"><a href="#_c_timecorrelate_param_x">x</a>, <a href="#_c_timecorrelate_param_y">y</a>, <a href="#_c_timecorrelate_param_lag">lag</a></span>, <a href="#_c_timecorrelate_keyword_COVARIANCE">COVARIANCE</a>=<span class="result">COVARIANCE</span>, <a href="#_c_timecorrelate_keyword_DOUBLE">DOUBLE</a>=<span class="result">DOUBLE</span>)</p> |
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294 | |
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295 | <div class="comments"> |
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296 | </div> |
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297 | |
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298 | |
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299 | |
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300 | |
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301 | <h3>Parameters</h3> |
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302 | |
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303 | |
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304 | <h4 id="_c_timecorrelate_param_x">x |
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305 | <span class="attr">in</span> |
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306 | |
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307 | |
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308 | <span class="attr">required</span> |
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309 | |
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310 | <span class="attr">type:</span> <span class="value">array</span> |
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311 | |
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312 | |
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313 | </h4> |
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314 | |
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315 | <div class="comments"> |
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316 | An array which last dimension is the time dimension of |
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317 | size n, float or double. |
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318 | </div> |
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319 | |
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320 | <h4 id="_c_timecorrelate_param_y">y |
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321 | <span class="attr">in</span> |
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322 | |
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323 | |
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324 | <span class="attr">required</span> |
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325 | |
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326 | <span class="attr">type:</span> <span class="value">array</span> |
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327 | |
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328 | |
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329 | </h4> |
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330 | |
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331 | <div class="comments"> |
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332 | An array which last dimension is the time dimension of |
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333 | size n, float or double. |
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334 | </div> |
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335 | |
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336 | <h4 id="_c_timecorrelate_param_lag">lag |
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337 | <span class="attr">in</span> |
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338 | |
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339 | |
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340 | <span class="attr">required</span> |
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341 | |
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342 | <span class="attr">type:</span> <span class="value">scalar or vector</span> |
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343 | |
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344 | |
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345 | </h4> |
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346 | |
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347 | <div class="comments"> |
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348 | A scalar or n-elements vector, in the interval [-(n-2),(n-2)], |
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349 | of type integer that specifies the absolute distance(s) between |
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350 | indexed elements of X. |
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351 | </div> |
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352 | |
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353 | |
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354 | |
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355 | |
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356 | |
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357 | |
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358 | <h3>Keywords</h3> |
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359 | |
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360 | <h4 id="_c_timecorrelate_keyword_COVARIANCE">COVARIANCE |
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361 | |
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362 | |
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363 | |
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364 | |
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365 | |
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366 | |
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367 | |
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368 | |
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369 | </h4> |
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370 | |
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371 | <div class="comments"> |
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372 | If set to a non-zero value, the sample cross |
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373 | covariance is computed. |
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374 | </div> |
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375 | |
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376 | <h4 id="_c_timecorrelate_keyword_DOUBLE">DOUBLE |
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377 | |
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378 | |
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379 | |
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380 | |
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381 | |
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382 | |
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383 | |
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384 | |
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385 | </h4> |
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386 | |
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387 | <div class="comments"> |
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388 | If set to a non-zero value, computations are done in |
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389 | double precision arithmetic. |
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390 | </div> |
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391 | |
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392 | |
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393 | |
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394 | <h3>Examples</h3><div class="preformat"> |
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395 | |
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396 | Define two n-elements sample populations. |
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397 | IDL> x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57] |
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398 | IDL> y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95] |
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399 | |
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400 | Compute the cross correlation of X and Y for LAG = -5, 0, 1, 5, 6, 7 |
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401 | IDL> lag = [-5, 0, 1, 5, 6, 7] |
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402 | IDL> result = c_timecorrelate(x, y, lag) |
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403 | |
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404 | The result should be: |
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405 | [-0.428246, 0.914755, 0.674547, -0.405140, -0.403100, -0.339685] |
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406 | </div> |
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407 | <h3>Version history</h3> |
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408 | |
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409 | <h4>Version</h4><div class="preformat"> |
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410 | $Id: c_timecorrelate.pro 371 2008-08-07 09:32:02Z pinsard $ |
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411 | </div> |
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412 | <h4>History</h4><div class="preformat"> |
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413 | - 01/03/2000 Sebastien Masson (smasson@lodyc.jussieu.fr) |
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414 | Based on the C_CORRELATE procedure of IDL |
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415 | - August 2003 Sebastien Masson |
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416 | update according to the update made in C_CORRELATE by |
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417 | W. Biagiotti and available in IDL 5.5 |
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418 | |
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419 | INTRODUCTION TO STATISTICAL TIME SERIES |
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420 | Wayne A. Fuller |
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421 | ISBN 0-471-28715-6 |
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422 | </div> |
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423 | |
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437 | |
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438 | |
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439 | <h3>Statistics</h3> |
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440 | <table class="statistics"> |
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441 | <tr><td>McCabe cyclic</td><td> 33</td></tr> |
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442 | <tr><td>McCabe essential</td><td> 1</td></tr> |
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443 | <tr><td>McCabe modular design</td><td> 1</td></tr> |
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444 | </table> |
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445 | |
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446 | |
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447 | </div> |
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448 | |
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449 | </div> |
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453 | <div id="tagline">Produced by IDLdoc 2.0.</div> |
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