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| <pre><span class="sourceLineNo">001</span>/*-<a name="line.1"></a> |
| <span class="sourceLineNo">002</span> *******************************************************************************<a name="line.2"></a> |
| <span class="sourceLineNo">003</span> * Copyright (c) 2011, 2016 Diamond Light Source Ltd.<a name="line.3"></a> |
| <span class="sourceLineNo">004</span> * All rights reserved. This program and the accompanying materials<a name="line.4"></a> |
| <span class="sourceLineNo">005</span> * are made available under the terms of the Eclipse Public License v1.0<a name="line.5"></a> |
| <span class="sourceLineNo">006</span> * which accompanies this distribution, and is available at<a name="line.6"></a> |
| <span class="sourceLineNo">007</span> * http://www.eclipse.org/legal/epl-v10.html<a name="line.7"></a> |
| <span class="sourceLineNo">008</span> *<a name="line.8"></a> |
| <span class="sourceLineNo">009</span> * Contributors:<a name="line.9"></a> |
| <span class="sourceLineNo">010</span> * Peter Chang - initial API and implementation and/or initial documentation<a name="line.10"></a> |
| <span class="sourceLineNo">011</span> *******************************************************************************/<a name="line.11"></a> |
| <span class="sourceLineNo">012</span><a name="line.12"></a> |
| <span class="sourceLineNo">013</span>package org.eclipse.january.dataset;<a name="line.13"></a> |
| <span class="sourceLineNo">014</span><a name="line.14"></a> |
| <span class="sourceLineNo">015</span>import java.lang.ref.SoftReference;<a name="line.15"></a> |
| <span class="sourceLineNo">016</span>import java.util.ArrayList;<a name="line.16"></a> |
| <span class="sourceLineNo">017</span>import java.util.Collections;<a name="line.17"></a> |
| <span class="sourceLineNo">018</span>import java.util.HashMap;<a name="line.18"></a> |
| <span class="sourceLineNo">019</span>import java.util.List;<a name="line.19"></a> |
| <span class="sourceLineNo">020</span>import java.util.Map;<a name="line.20"></a> |
| <span class="sourceLineNo">021</span>import java.util.TreeMap;<a name="line.21"></a> |
| <span class="sourceLineNo">022</span><a name="line.22"></a> |
| <span class="sourceLineNo">023</span>import org.apache.commons.math3.complex.Complex;<a name="line.23"></a> |
| <span class="sourceLineNo">024</span>import org.apache.commons.math3.stat.descriptive.moment.Kurtosis;<a name="line.24"></a> |
| <span class="sourceLineNo">025</span>import org.apache.commons.math3.stat.descriptive.moment.Skewness;<a name="line.25"></a> |
| <span class="sourceLineNo">026</span>import org.eclipse.january.metadata.Dirtiable;<a name="line.26"></a> |
| <span class="sourceLineNo">027</span>import org.eclipse.january.metadata.MetadataType;<a name="line.27"></a> |
| <span class="sourceLineNo">028</span><a name="line.28"></a> |
| <span class="sourceLineNo">029</span><a name="line.29"></a> |
| <span class="sourceLineNo">030</span>/**<a name="line.30"></a> |
| <span class="sourceLineNo">031</span> * Statistics class<a name="line.31"></a> |
| <span class="sourceLineNo">032</span> * <a name="line.32"></a> |
| <span class="sourceLineNo">033</span> * TODO Where is mode? http://en.wikipedia.org/wiki/Mode_(statistics)<a name="line.33"></a> |
| <span class="sourceLineNo">034</span> * <a name="line.34"></a> |
| <span class="sourceLineNo">035</span> */<a name="line.35"></a> |
| <span class="sourceLineNo">036</span>public class Stats {<a name="line.36"></a> |
| <span class="sourceLineNo">037</span><a name="line.37"></a> |
| <span class="sourceLineNo">038</span> private static class ReferencedDataset extends SoftReference<Dataset> {<a name="line.38"></a> |
| <span class="sourceLineNo">039</span> public ReferencedDataset(Dataset d) {<a name="line.39"></a> |
| <span class="sourceLineNo">040</span> super(d);<a name="line.40"></a> |
| <span class="sourceLineNo">041</span> }<a name="line.41"></a> |
| <span class="sourceLineNo">042</span> }<a name="line.42"></a> |
| <span class="sourceLineNo">043</span><a name="line.43"></a> |
| <span class="sourceLineNo">044</span> private static class QStatisticsImpl<T> implements MetadataType {<a name="line.44"></a> |
| <span class="sourceLineNo">045</span> private static final long serialVersionUID = -3296671666463190388L;<a name="line.45"></a> |
| <span class="sourceLineNo">046</span> final static Double Q1 = 0.25;<a name="line.46"></a> |
| <span class="sourceLineNo">047</span> final static Double Q2 = 0.5;<a name="line.47"></a> |
| <span class="sourceLineNo">048</span> final static Double Q3 = 0.75;<a name="line.48"></a> |
| <span class="sourceLineNo">049</span> Map<Double, T> qmap = new HashMap<Double, T>();<a name="line.49"></a> |
| <span class="sourceLineNo">050</span> transient Map<Integer, Map<Double, ReferencedDataset>> aqmap = new HashMap<Integer, Map<Double, ReferencedDataset>>();<a name="line.50"></a> |
| <span class="sourceLineNo">051</span> transient ReferencedDataset s; // store 0th element<a name="line.51"></a> |
| <span class="sourceLineNo">052</span> transient Map<Integer, ReferencedDataset> smap = new HashMap<>();<a name="line.52"></a> |
| <span class="sourceLineNo">053</span><a name="line.53"></a> |
| <span class="sourceLineNo">054</span> @Dirtiable<a name="line.54"></a> |
| <span class="sourceLineNo">055</span> private boolean isDirty = true;<a name="line.55"></a> |
| <span class="sourceLineNo">056</span><a name="line.56"></a> |
| <span class="sourceLineNo">057</span> @Override<a name="line.57"></a> |
| <span class="sourceLineNo">058</span> public QStatisticsImpl<T> clone() {<a name="line.58"></a> |
| <span class="sourceLineNo">059</span> return new QStatisticsImpl<T>(this);<a name="line.59"></a> |
| <span class="sourceLineNo">060</span> }<a name="line.60"></a> |
| <span class="sourceLineNo">061</span><a name="line.61"></a> |
| <span class="sourceLineNo">062</span> public QStatisticsImpl() {<a name="line.62"></a> |
| <span class="sourceLineNo">063</span> }<a name="line.63"></a> |
| <span class="sourceLineNo">064</span><a name="line.64"></a> |
| <span class="sourceLineNo">065</span> private QStatisticsImpl(QStatisticsImpl<T> qstats) {<a name="line.65"></a> |
| <span class="sourceLineNo">066</span> if (qstats.s != null && qstats.s.get() != null) {<a name="line.66"></a> |
| <span class="sourceLineNo">067</span> s = new ReferencedDataset(qstats.s.get().getView(false));<a name="line.67"></a> |
| <span class="sourceLineNo">068</span> }<a name="line.68"></a> |
| <span class="sourceLineNo">069</span> qmap.putAll(qstats.qmap);<a name="line.69"></a> |
| <span class="sourceLineNo">070</span> for (Integer i : qstats.aqmap.keySet()) {<a name="line.70"></a> |
| <span class="sourceLineNo">071</span> aqmap.put(i, new HashMap<>(qstats.aqmap.get(i)));<a name="line.71"></a> |
| <span class="sourceLineNo">072</span> }<a name="line.72"></a> |
| <span class="sourceLineNo">073</span> smap.putAll(qstats.smap);<a name="line.73"></a> |
| <span class="sourceLineNo">074</span> isDirty = qstats.isDirty;<a name="line.74"></a> |
| <span class="sourceLineNo">075</span> }<a name="line.75"></a> |
| <span class="sourceLineNo">076</span><a name="line.76"></a> |
| <span class="sourceLineNo">077</span> public void setQuantile(double q, T v) {<a name="line.77"></a> |
| <span class="sourceLineNo">078</span> qmap.put(q, v);<a name="line.78"></a> |
| <span class="sourceLineNo">079</span> }<a name="line.79"></a> |
| <span class="sourceLineNo">080</span><a name="line.80"></a> |
| <span class="sourceLineNo">081</span> public T getQuantile(double q) {<a name="line.81"></a> |
| <span class="sourceLineNo">082</span> return qmap.get(q);<a name="line.82"></a> |
| <span class="sourceLineNo">083</span> }<a name="line.83"></a> |
| <span class="sourceLineNo">084</span><a name="line.84"></a> |
| <span class="sourceLineNo">085</span> private Map<Double, ReferencedDataset> getMap(int axis) {<a name="line.85"></a> |
| <span class="sourceLineNo">086</span> Map<Double, ReferencedDataset> qm = aqmap.get(axis);<a name="line.86"></a> |
| <span class="sourceLineNo">087</span> if (qm == null) {<a name="line.87"></a> |
| <span class="sourceLineNo">088</span> qm = new HashMap<>();<a name="line.88"></a> |
| <span class="sourceLineNo">089</span> aqmap.put(axis, qm);<a name="line.89"></a> |
| <span class="sourceLineNo">090</span> }<a name="line.90"></a> |
| <span class="sourceLineNo">091</span> return qm;<a name="line.91"></a> |
| <span class="sourceLineNo">092</span> }<a name="line.92"></a> |
| <span class="sourceLineNo">093</span><a name="line.93"></a> |
| <span class="sourceLineNo">094</span> public void setQuantile(int axis, double q, Dataset v) {<a name="line.94"></a> |
| <span class="sourceLineNo">095</span> Map<Double, ReferencedDataset> qm = getMap(axis);<a name="line.95"></a> |
| <span class="sourceLineNo">096</span> qm.put(q, new ReferencedDataset(v));<a name="line.96"></a> |
| <span class="sourceLineNo">097</span> }<a name="line.97"></a> |
| <span class="sourceLineNo">098</span><a name="line.98"></a> |
| <span class="sourceLineNo">099</span> public Dataset getQuantile(int axis, double q) {<a name="line.99"></a> |
| <span class="sourceLineNo">100</span> Map<Double, ReferencedDataset> qm = getMap(axis);<a name="line.100"></a> |
| <span class="sourceLineNo">101</span> ReferencedDataset rd = qm.get(q);<a name="line.101"></a> |
| <span class="sourceLineNo">102</span> return rd == null ? null : rd.get();<a name="line.102"></a> |
| <span class="sourceLineNo">103</span> }<a name="line.103"></a> |
| <span class="sourceLineNo">104</span><a name="line.104"></a> |
| <span class="sourceLineNo">105</span> Dataset getSortedDataset(int axis) {<a name="line.105"></a> |
| <span class="sourceLineNo">106</span> return smap.containsKey(axis) ? smap.get(axis).get() : null;<a name="line.106"></a> |
| <span class="sourceLineNo">107</span> }<a name="line.107"></a> |
| <span class="sourceLineNo">108</span><a name="line.108"></a> |
| <span class="sourceLineNo">109</span> void setSortedDataset(int axis, Dataset v) {<a name="line.109"></a> |
| <span class="sourceLineNo">110</span> smap.put(axis, new ReferencedDataset(v));<a name="line.110"></a> |
| <span class="sourceLineNo">111</span> }<a name="line.111"></a> |
| <span class="sourceLineNo">112</span> }<a name="line.112"></a> |
| <span class="sourceLineNo">113</span><a name="line.113"></a> |
| <span class="sourceLineNo">114</span> // calculates statistics and returns sorted dataset (0th element if compound)<a name="line.114"></a> |
| <span class="sourceLineNo">115</span> private static QStatisticsImpl<?> calcQuartileStats(final Dataset a) {<a name="line.115"></a> |
| <span class="sourceLineNo">116</span> Dataset s = null;<a name="line.116"></a> |
| <span class="sourceLineNo">117</span> final int is = a.getElementsPerItem();<a name="line.117"></a> |
| <span class="sourceLineNo">118</span><a name="line.118"></a> |
| <span class="sourceLineNo">119</span> if (is == 1) {<a name="line.119"></a> |
| <span class="sourceLineNo">120</span> s = DatasetUtils.sort(a);<a name="line.120"></a> |
| <span class="sourceLineNo">121</span><a name="line.121"></a> |
| <span class="sourceLineNo">122</span> QStatisticsImpl<Double> qstats = new QStatisticsImpl<Double>();<a name="line.122"></a> |
| <span class="sourceLineNo">123</span><a name="line.123"></a> |
| <span class="sourceLineNo">124</span> qstats.setQuantile(QStatisticsImpl.Q1, pQuantile(s, QStatisticsImpl.Q1));<a name="line.124"></a> |
| <span class="sourceLineNo">125</span> qstats.setQuantile(QStatisticsImpl.Q2, pQuantile(s, QStatisticsImpl.Q2));<a name="line.125"></a> |
| <span class="sourceLineNo">126</span> qstats.setQuantile(QStatisticsImpl.Q3, pQuantile(s, QStatisticsImpl.Q3));<a name="line.126"></a> |
| <span class="sourceLineNo">127</span> qstats.s = new ReferencedDataset(s);<a name="line.127"></a> |
| <span class="sourceLineNo">128</span> return qstats;<a name="line.128"></a> |
| <span class="sourceLineNo">129</span> }<a name="line.129"></a> |
| <span class="sourceLineNo">130</span><a name="line.130"></a> |
| <span class="sourceLineNo">131</span> QStatisticsImpl<double[]> qstats = new QStatisticsImpl<double[]>();<a name="line.131"></a> |
| <span class="sourceLineNo">132</span><a name="line.132"></a> |
| <span class="sourceLineNo">133</span> Dataset w = DatasetFactory.zeros(1, a.getClass(), a.getShapeRef());<a name="line.133"></a> |
| <span class="sourceLineNo">134</span> double[] q1 = new double[is];<a name="line.134"></a> |
| <span class="sourceLineNo">135</span> double[] q2 = new double[is];<a name="line.135"></a> |
| <span class="sourceLineNo">136</span> double[] q3 = new double[is];<a name="line.136"></a> |
| <span class="sourceLineNo">137</span> qstats.setQuantile(QStatisticsImpl.Q1, q1);<a name="line.137"></a> |
| <span class="sourceLineNo">138</span> qstats.setQuantile(QStatisticsImpl.Q2, q2);<a name="line.138"></a> |
| <span class="sourceLineNo">139</span> qstats.setQuantile(QStatisticsImpl.Q3, q3);<a name="line.139"></a> |
| <span class="sourceLineNo">140</span> for (int j = 0; j < is; j++) {<a name="line.140"></a> |
| <span class="sourceLineNo">141</span> ((CompoundDataset) a).copyElements(w, j);<a name="line.141"></a> |
| <span class="sourceLineNo">142</span> w.sort(null);<a name="line.142"></a> |
| <span class="sourceLineNo">143</span><a name="line.143"></a> |
| <span class="sourceLineNo">144</span> q1[j] = pQuantile(w, QStatisticsImpl.Q1);<a name="line.144"></a> |
| <span class="sourceLineNo">145</span> q2[j] = pQuantile(w, QStatisticsImpl.Q2);<a name="line.145"></a> |
| <span class="sourceLineNo">146</span> q3[j] = pQuantile(w, QStatisticsImpl.Q3);<a name="line.146"></a> |
| <span class="sourceLineNo">147</span> if (j == 0)<a name="line.147"></a> |
| <span class="sourceLineNo">148</span> s = w.clone();<a name="line.148"></a> |
| <span class="sourceLineNo">149</span> }<a name="line.149"></a> |
| <span class="sourceLineNo">150</span> qstats.s = new ReferencedDataset(s);<a name="line.150"></a> |
| <span class="sourceLineNo">151</span><a name="line.151"></a> |
| <span class="sourceLineNo">152</span> return qstats;<a name="line.152"></a> |
| <span class="sourceLineNo">153</span> }<a name="line.153"></a> |
| <span class="sourceLineNo">154</span><a name="line.154"></a> |
| <span class="sourceLineNo">155</span> static private QStatisticsImpl<?> getQStatistics(final Dataset a) {<a name="line.155"></a> |
| <span class="sourceLineNo">156</span> QStatisticsImpl<?> m = a.getFirstMetadata(QStatisticsImpl.class);<a name="line.156"></a> |
| <span class="sourceLineNo">157</span> if (m == null || m.isDirty) {<a name="line.157"></a> |
| <span class="sourceLineNo">158</span> m = calcQuartileStats(a);<a name="line.158"></a> |
| <span class="sourceLineNo">159</span> a.setMetadata(m);<a name="line.159"></a> |
| <span class="sourceLineNo">160</span> }<a name="line.160"></a> |
| <span class="sourceLineNo">161</span> return m;<a name="line.161"></a> |
| <span class="sourceLineNo">162</span> }<a name="line.162"></a> |
| <span class="sourceLineNo">163</span><a name="line.163"></a> |
| <span class="sourceLineNo">164</span> static private QStatisticsImpl<?> getQStatistics(final Dataset a, final int axis) {<a name="line.164"></a> |
| <span class="sourceLineNo">165</span> final int is = a.getElementsPerItem();<a name="line.165"></a> |
| <span class="sourceLineNo">166</span> QStatisticsImpl<?> qstats = a.getFirstMetadata(QStatisticsImpl.class);<a name="line.166"></a> |
| <span class="sourceLineNo">167</span><a name="line.167"></a> |
| <span class="sourceLineNo">168</span> if (qstats == null || qstats.isDirty) {<a name="line.168"></a> |
| <span class="sourceLineNo">169</span> if (is == 1) {<a name="line.169"></a> |
| <span class="sourceLineNo">170</span> qstats = new QStatisticsImpl<Double>();<a name="line.170"></a> |
| <span class="sourceLineNo">171</span> } else {<a name="line.171"></a> |
| <span class="sourceLineNo">172</span> qstats = new QStatisticsImpl<double[]>();<a name="line.172"></a> |
| <span class="sourceLineNo">173</span> }<a name="line.173"></a> |
| <span class="sourceLineNo">174</span> a.setMetadata(qstats);<a name="line.174"></a> |
| <span class="sourceLineNo">175</span> }<a name="line.175"></a> |
| <span class="sourceLineNo">176</span><a name="line.176"></a> |
| <span class="sourceLineNo">177</span> if (qstats.getQuantile(axis, QStatisticsImpl.Q2) == null) {<a name="line.177"></a> |
| <span class="sourceLineNo">178</span> if (is == 1) {<a name="line.178"></a> |
| <span class="sourceLineNo">179</span> Dataset s = DatasetUtils.sort(a, axis);<a name="line.179"></a> |
| <span class="sourceLineNo">180</span><a name="line.180"></a> |
| <span class="sourceLineNo">181</span> qstats.setQuantile(axis, QStatisticsImpl.Q1, pQuantile(s, axis, QStatisticsImpl.Q1));<a name="line.181"></a> |
| <span class="sourceLineNo">182</span> qstats.setQuantile(axis, QStatisticsImpl.Q2, pQuantile(s, axis, QStatisticsImpl.Q2));<a name="line.182"></a> |
| <span class="sourceLineNo">183</span> qstats.setQuantile(axis, QStatisticsImpl.Q3, pQuantile(s, axis, QStatisticsImpl.Q3));<a name="line.183"></a> |
| <span class="sourceLineNo">184</span> qstats.setSortedDataset(axis, s);<a name="line.184"></a> |
| <span class="sourceLineNo">185</span> } else {<a name="line.185"></a> |
| <span class="sourceLineNo">186</span> Dataset w = DatasetFactory.zeros(1, a.getClass(), a.getShapeRef());<a name="line.186"></a> |
| <span class="sourceLineNo">187</span> CompoundDoubleDataset q1 = null, q2 = null, q3 = null;<a name="line.187"></a> |
| <span class="sourceLineNo">188</span> for (int j = 0; j < is; j++) {<a name="line.188"></a> |
| <span class="sourceLineNo">189</span> ((CompoundDataset) a).copyElements(w, j);<a name="line.189"></a> |
| <span class="sourceLineNo">190</span> w.sort(axis);<a name="line.190"></a> |
| <span class="sourceLineNo">191</span> <a name="line.191"></a> |
| <span class="sourceLineNo">192</span> final Dataset c = pQuantile(w, axis, QStatisticsImpl.Q1);<a name="line.192"></a> |
| <span class="sourceLineNo">193</span> if (j == 0) {<a name="line.193"></a> |
| <span class="sourceLineNo">194</span> q1 = DatasetFactory.zeros(is, CompoundDoubleDataset.class, c.getShapeRef());<a name="line.194"></a> |
| <span class="sourceLineNo">195</span> q2 = DatasetFactory.zeros(is, CompoundDoubleDataset.class, c.getShapeRef());<a name="line.195"></a> |
| <span class="sourceLineNo">196</span> q3 = DatasetFactory.zeros(is, CompoundDoubleDataset.class, c.getShapeRef());<a name="line.196"></a> |
| <span class="sourceLineNo">197</span> }<a name="line.197"></a> |
| <span class="sourceLineNo">198</span> q1.setElements(c, j);<a name="line.198"></a> |
| <span class="sourceLineNo">199</span> <a name="line.199"></a> |
| <span class="sourceLineNo">200</span> q2.setElements(pQuantile(w, axis, QStatisticsImpl.Q2), j);<a name="line.200"></a> |
| <span class="sourceLineNo">201</span> <a name="line.201"></a> |
| <span class="sourceLineNo">202</span> q3.setElements(pQuantile(w, axis, QStatisticsImpl.Q3), j);<a name="line.202"></a> |
| <span class="sourceLineNo">203</span> }<a name="line.203"></a> |
| <span class="sourceLineNo">204</span> qstats.setQuantile(axis, QStatisticsImpl.Q1, q1);<a name="line.204"></a> |
| <span class="sourceLineNo">205</span> qstats.setQuantile(axis, QStatisticsImpl.Q2, q2);<a name="line.205"></a> |
| <span class="sourceLineNo">206</span> qstats.setQuantile(axis, QStatisticsImpl.Q3, q3);<a name="line.206"></a> |
| <span class="sourceLineNo">207</span> }<a name="line.207"></a> |
| <span class="sourceLineNo">208</span> }<a name="line.208"></a> |
| <span class="sourceLineNo">209</span><a name="line.209"></a> |
| <span class="sourceLineNo">210</span> return qstats;<a name="line.210"></a> |
| <span class="sourceLineNo">211</span> }<a name="line.211"></a> |
| <span class="sourceLineNo">212</span><a name="line.212"></a> |
| <span class="sourceLineNo">213</span> // process a sorted dataset<a name="line.213"></a> |
| <span class="sourceLineNo">214</span> private static double pQuantile(final Dataset s, final double q) {<a name="line.214"></a> |
| <span class="sourceLineNo">215</span> double f = (s.getSize() - 1) * q; // fraction of sample number<a name="line.215"></a> |
| <span class="sourceLineNo">216</span> if (f < 0)<a name="line.216"></a> |
| <span class="sourceLineNo">217</span> return Double.NaN;<a name="line.217"></a> |
| <span class="sourceLineNo">218</span> int qpt = (int) Math.floor(f); // quantile point<a name="line.218"></a> |
| <span class="sourceLineNo">219</span> f -= qpt;<a name="line.219"></a> |
| <span class="sourceLineNo">220</span><a name="line.220"></a> |
| <span class="sourceLineNo">221</span> double quantile = s.getElementDoubleAbs(qpt);<a name="line.221"></a> |
| <span class="sourceLineNo">222</span> if (f > 0) {<a name="line.222"></a> |
| <span class="sourceLineNo">223</span> quantile = (1-f)*quantile + f*s.getElementDoubleAbs(qpt+1);<a name="line.223"></a> |
| <span class="sourceLineNo">224</span> }<a name="line.224"></a> |
| <span class="sourceLineNo">225</span> return quantile;<a name="line.225"></a> |
| <span class="sourceLineNo">226</span> }<a name="line.226"></a> |
| <span class="sourceLineNo">227</span><a name="line.227"></a> |
| <span class="sourceLineNo">228</span> // process a sorted dataset and returns a double or compound double dataset<a name="line.228"></a> |
| <span class="sourceLineNo">229</span> private static Dataset pQuantile(final Dataset s, final int axis, final double q) {<a name="line.229"></a> |
| <span class="sourceLineNo">230</span> final int rank = s.getRank();<a name="line.230"></a> |
| <span class="sourceLineNo">231</span> final int is = s.getElementsPerItem();<a name="line.231"></a> |
| <span class="sourceLineNo">232</span><a name="line.232"></a> |
| <span class="sourceLineNo">233</span> int[] oshape = s.getShape();<a name="line.233"></a> |
| <span class="sourceLineNo">234</span><a name="line.234"></a> |
| <span class="sourceLineNo">235</span> double f = (oshape[axis] - 1) * q; // fraction of sample number<a name="line.235"></a> |
| <span class="sourceLineNo">236</span> int qpt = (int) Math.floor(f); // quantile point<a name="line.236"></a> |
| <span class="sourceLineNo">237</span> f -= qpt;<a name="line.237"></a> |
| <span class="sourceLineNo">238</span><a name="line.238"></a> |
| <span class="sourceLineNo">239</span> oshape[axis] = 1;<a name="line.239"></a> |
| <span class="sourceLineNo">240</span> int[] qshape = ShapeUtils.squeezeShape(oshape, false);<a name="line.240"></a> |
| <span class="sourceLineNo">241</span> Dataset qds = DatasetFactory.zeros(is, CompoundDoubleDataset.class, qshape);<a name="line.241"></a> |
| <span class="sourceLineNo">242</span><a name="line.242"></a> |
| <span class="sourceLineNo">243</span> IndexIterator qiter = qds.getIterator(true);<a name="line.243"></a> |
| <span class="sourceLineNo">244</span> int[] qpos = qiter.getPos();<a name="line.244"></a> |
| <span class="sourceLineNo">245</span> int[] spos = oshape;<a name="line.245"></a> |
| <span class="sourceLineNo">246</span><a name="line.246"></a> |
| <span class="sourceLineNo">247</span> while (qiter.hasNext()) {<a name="line.247"></a> |
| <span class="sourceLineNo">248</span> int i = 0;<a name="line.248"></a> |
| <span class="sourceLineNo">249</span> for (; i < axis; i++) {<a name="line.249"></a> |
| <span class="sourceLineNo">250</span> spos[i] = qpos[i];<a name="line.250"></a> |
| <span class="sourceLineNo">251</span> }<a name="line.251"></a> |
| <span class="sourceLineNo">252</span> spos[i++] = qpt;<a name="line.252"></a> |
| <span class="sourceLineNo">253</span> for (; i < rank; i++) {<a name="line.253"></a> |
| <span class="sourceLineNo">254</span> spos[i] = qpos[i-1];<a name="line.254"></a> |
| <span class="sourceLineNo">255</span> }<a name="line.255"></a> |
| <span class="sourceLineNo">256</span><a name="line.256"></a> |
| <span class="sourceLineNo">257</span> Object obj = s.getObject(spos);<a name="line.257"></a> |
| <span class="sourceLineNo">258</span> qds.set(obj, qpos);<a name="line.258"></a> |
| <span class="sourceLineNo">259</span> }<a name="line.259"></a> |
| <span class="sourceLineNo">260</span><a name="line.260"></a> |
| <span class="sourceLineNo">261</span> if (f > 0) {<a name="line.261"></a> |
| <span class="sourceLineNo">262</span> qiter = qds.getIterator(true);<a name="line.262"></a> |
| <span class="sourceLineNo">263</span> qpos = qiter.getPos();<a name="line.263"></a> |
| <span class="sourceLineNo">264</span> qpt++;<a name="line.264"></a> |
| <span class="sourceLineNo">265</span> Dataset rds = DatasetFactory.zeros(is, CompoundDoubleDataset.class, qshape);<a name="line.265"></a> |
| <span class="sourceLineNo">266</span> <a name="line.266"></a> |
| <span class="sourceLineNo">267</span> while (qiter.hasNext()) {<a name="line.267"></a> |
| <span class="sourceLineNo">268</span> int i = 0;<a name="line.268"></a> |
| <span class="sourceLineNo">269</span> for (; i < axis; i++) {<a name="line.269"></a> |
| <span class="sourceLineNo">270</span> spos[i] = qpos[i];<a name="line.270"></a> |
| <span class="sourceLineNo">271</span> }<a name="line.271"></a> |
| <span class="sourceLineNo">272</span> spos[i++] = qpt;<a name="line.272"></a> |
| <span class="sourceLineNo">273</span> for (; i < rank; i++) {<a name="line.273"></a> |
| <span class="sourceLineNo">274</span> spos[i] = qpos[i-1];<a name="line.274"></a> |
| <span class="sourceLineNo">275</span> }<a name="line.275"></a> |
| <span class="sourceLineNo">276</span><a name="line.276"></a> |
| <span class="sourceLineNo">277</span> Object obj = s.getObject(spos);<a name="line.277"></a> |
| <span class="sourceLineNo">278</span> rds.set(obj, qpos);<a name="line.278"></a> |
| <span class="sourceLineNo">279</span> }<a name="line.279"></a> |
| <span class="sourceLineNo">280</span> rds.imultiply(f);<a name="line.280"></a> |
| <span class="sourceLineNo">281</span> qds.imultiply(1-f);<a name="line.281"></a> |
| <span class="sourceLineNo">282</span> qds.iadd(rds);<a name="line.282"></a> |
| <span class="sourceLineNo">283</span> }<a name="line.283"></a> |
| <span class="sourceLineNo">284</span><a name="line.284"></a> |
| <span class="sourceLineNo">285</span> return qds;<a name="line.285"></a> |
| <span class="sourceLineNo">286</span> }<a name="line.286"></a> |
| <span class="sourceLineNo">287</span><a name="line.287"></a> |
| <span class="sourceLineNo">288</span> /**<a name="line.288"></a> |
| <span class="sourceLineNo">289</span> * Calculate quantile of dataset which is defined as the inverse of the cumulative distribution function (CDF)<a name="line.289"></a> |
| <span class="sourceLineNo">290</span> * @param a<a name="line.290"></a> |
| <span class="sourceLineNo">291</span> * @param q<a name="line.291"></a> |
| <span class="sourceLineNo">292</span> * @return point at which CDF has value q<a name="line.292"></a> |
| <span class="sourceLineNo">293</span> */<a name="line.293"></a> |
| <span class="sourceLineNo">294</span> @SuppressWarnings("unchecked")<a name="line.294"></a> |
| <span class="sourceLineNo">295</span> public static double quantile(final Dataset a, final double q) {<a name="line.295"></a> |
| <span class="sourceLineNo">296</span> if (q < 0 || q > 1) {<a name="line.296"></a> |
| <span class="sourceLineNo">297</span> throw new IllegalArgumentException("Quantile requested is outside [0,1]");<a name="line.297"></a> |
| <span class="sourceLineNo">298</span> }<a name="line.298"></a> |
| <span class="sourceLineNo">299</span> QStatisticsImpl<Double> qs = (QStatisticsImpl<Double>) getQStatistics(a);<a name="line.299"></a> |
| <span class="sourceLineNo">300</span> Double qv = qs.getQuantile(q);<a name="line.300"></a> |
| <span class="sourceLineNo">301</span> if (qv == null) {<a name="line.301"></a> |
| <span class="sourceLineNo">302</span> qv = pQuantile(qs.s.get(), q);<a name="line.302"></a> |
| <span class="sourceLineNo">303</span> qs.setQuantile(q, qv);<a name="line.303"></a> |
| <span class="sourceLineNo">304</span> }<a name="line.304"></a> |
| <span class="sourceLineNo">305</span> return qv;<a name="line.305"></a> |
| <span class="sourceLineNo">306</span> }<a name="line.306"></a> |
| <span class="sourceLineNo">307</span><a name="line.307"></a> |
| <span class="sourceLineNo">308</span> /**<a name="line.308"></a> |
| <span class="sourceLineNo">309</span> * Calculate quantiles of dataset which is defined as the inverse of the cumulative distribution function (CDF)<a name="line.309"></a> |
| <span class="sourceLineNo">310</span> * @param a<a name="line.310"></a> |
| <span class="sourceLineNo">311</span> * @param values<a name="line.311"></a> |
| <span class="sourceLineNo">312</span> * @return points at which CDF has given values<a name="line.312"></a> |
| <span class="sourceLineNo">313</span> */<a name="line.313"></a> |
| <span class="sourceLineNo">314</span> @SuppressWarnings("unchecked")<a name="line.314"></a> |
| <span class="sourceLineNo">315</span> public static double[] quantile(final Dataset a, final double... values) {<a name="line.315"></a> |
| <span class="sourceLineNo">316</span> final double[] points = new double[values.length];<a name="line.316"></a> |
| <span class="sourceLineNo">317</span> QStatisticsImpl<Double> qs = (QStatisticsImpl<Double>) getQStatistics(a);<a name="line.317"></a> |
| <span class="sourceLineNo">318</span> for (int i = 0; i < points.length; i++) {<a name="line.318"></a> |
| <span class="sourceLineNo">319</span> final double q = values[i];<a name="line.319"></a> |
| <span class="sourceLineNo">320</span> if (q < 0 || q > 1) {<a name="line.320"></a> |
| <span class="sourceLineNo">321</span> throw new IllegalArgumentException("Quantile requested is outside [0,1]");<a name="line.321"></a> |
| <span class="sourceLineNo">322</span> }<a name="line.322"></a> |
| <span class="sourceLineNo">323</span> Double qv = qs.getQuantile(q);<a name="line.323"></a> |
| <span class="sourceLineNo">324</span> if (qv == null) {<a name="line.324"></a> |
| <span class="sourceLineNo">325</span> qv = pQuantile(qs.s.get(), q);<a name="line.325"></a> |
| <span class="sourceLineNo">326</span> qs.setQuantile(q, qv);<a name="line.326"></a> |
| <span class="sourceLineNo">327</span> }<a name="line.327"></a> |
| <span class="sourceLineNo">328</span> points[i] = qv;<a name="line.328"></a> |
| <span class="sourceLineNo">329</span> }<a name="line.329"></a> |
| <span class="sourceLineNo">330</span><a name="line.330"></a> |
| <span class="sourceLineNo">331</span> return points;<a name="line.331"></a> |
| <span class="sourceLineNo">332</span> }<a name="line.332"></a> |
| <span class="sourceLineNo">333</span><a name="line.333"></a> |
| <span class="sourceLineNo">334</span> /**<a name="line.334"></a> |
| <span class="sourceLineNo">335</span> * Calculate quantiles of dataset which is defined as the inverse of the cumulative distribution function (CDF)<a name="line.335"></a> |
| <span class="sourceLineNo">336</span> * @param a<a name="line.336"></a> |
| <span class="sourceLineNo">337</span> * @param axis<a name="line.337"></a> |
| <span class="sourceLineNo">338</span> * @param values<a name="line.338"></a> |
| <span class="sourceLineNo">339</span> * @return points at which CDF has given values<a name="line.339"></a> |
| <span class="sourceLineNo">340</span> */<a name="line.340"></a> |
| <span class="sourceLineNo">341</span> @SuppressWarnings({ "unchecked" })<a name="line.341"></a> |
| <span class="sourceLineNo">342</span> public static Dataset[] quantile(final Dataset a, int axis, final double... values) {<a name="line.342"></a> |
| <span class="sourceLineNo">343</span> final Dataset[] points = new Dataset[values.length];<a name="line.343"></a> |
| <span class="sourceLineNo">344</span> final int is = a.getElementsPerItem();<a name="line.344"></a> |
| <span class="sourceLineNo">345</span> axis = a.checkAxis(axis);<a name="line.345"></a> |
| <span class="sourceLineNo">346</span><a name="line.346"></a> |
| <span class="sourceLineNo">347</span> if (is == 1) {<a name="line.347"></a> |
| <span class="sourceLineNo">348</span> QStatisticsImpl<Double> qs = (QStatisticsImpl<Double>) getQStatistics(a, axis);<a name="line.348"></a> |
| <span class="sourceLineNo">349</span> for (int i = 0; i < points.length; i++) {<a name="line.349"></a> |
| <span class="sourceLineNo">350</span> final double q = values[i];<a name="line.350"></a> |
| <span class="sourceLineNo">351</span> if (q < 0 || q > 1) {<a name="line.351"></a> |
| <span class="sourceLineNo">352</span> throw new IllegalArgumentException("Quantile requested is outside [0,1]");<a name="line.352"></a> |
| <span class="sourceLineNo">353</span> }<a name="line.353"></a> |
| <span class="sourceLineNo">354</span> Dataset qv = qs.getQuantile(axis, q);<a name="line.354"></a> |
| <span class="sourceLineNo">355</span> if (qv == null) {<a name="line.355"></a> |
| <span class="sourceLineNo">356</span> qv = pQuantile(qs.getSortedDataset(axis), axis, q);<a name="line.356"></a> |
| <span class="sourceLineNo">357</span> qs.setQuantile(axis, q, qv);<a name="line.357"></a> |
| <span class="sourceLineNo">358</span> }<a name="line.358"></a> |
| <span class="sourceLineNo">359</span> points[i] = qv;<a name="line.359"></a> |
| <span class="sourceLineNo">360</span> }<a name="line.360"></a> |
| <span class="sourceLineNo">361</span> } else {<a name="line.361"></a> |
| <span class="sourceLineNo">362</span> QStatisticsImpl<double[]> qs = (QStatisticsImpl<double[]>) getQStatistics(a);<a name="line.362"></a> |
| <span class="sourceLineNo">363</span> Dataset w = DatasetFactory.zeros(1, a.getClass(), a.getShapeRef());<a name="line.363"></a> |
| <span class="sourceLineNo">364</span> for (int j = 0; j < is; j++) {<a name="line.364"></a> |
| <span class="sourceLineNo">365</span> boolean copied = false;<a name="line.365"></a> |
| <span class="sourceLineNo">366</span><a name="line.366"></a> |
| <span class="sourceLineNo">367</span> for (int i = 0; i < points.length; i++) {<a name="line.367"></a> |
| <span class="sourceLineNo">368</span> final double q = values[i];<a name="line.368"></a> |
| <span class="sourceLineNo">369</span> if (q < 0 || q > 1) {<a name="line.369"></a> |
| <span class="sourceLineNo">370</span> throw new IllegalArgumentException("Quantile requested is outside [0,1]");<a name="line.370"></a> |
| <span class="sourceLineNo">371</span> }<a name="line.371"></a> |
| <span class="sourceLineNo">372</span> Dataset qv = qs.getQuantile(axis, q);<a name="line.372"></a> |
| <span class="sourceLineNo">373</span> if (qv == null) {<a name="line.373"></a> |
| <span class="sourceLineNo">374</span> if (!copied) {<a name="line.374"></a> |
| <span class="sourceLineNo">375</span> copied = true;<a name="line.375"></a> |
| <span class="sourceLineNo">376</span> ((CompoundDataset) a).copyElements(w, j);<a name="line.376"></a> |
| <span class="sourceLineNo">377</span> w.sort(axis);<a name="line.377"></a> |
| <span class="sourceLineNo">378</span> }<a name="line.378"></a> |
| <span class="sourceLineNo">379</span> qv = pQuantile(w, axis, q);<a name="line.379"></a> |
| <span class="sourceLineNo">380</span> qs.setQuantile(axis, q, qv);<a name="line.380"></a> |
| <span class="sourceLineNo">381</span> if (j == 0) {<a name="line.381"></a> |
| <span class="sourceLineNo">382</span> points[i] = DatasetFactory.zeros(is, qv.getClass(), qv.getShapeRef());<a name="line.382"></a> |
| <span class="sourceLineNo">383</span> }<a name="line.383"></a> |
| <span class="sourceLineNo">384</span> ((CompoundDoubleDataset) points[i]).setElements(qv, j);<a name="line.384"></a> |
| <span class="sourceLineNo">385</span> }<a name="line.385"></a> |
| <span class="sourceLineNo">386</span> }<a name="line.386"></a> |
| <span class="sourceLineNo">387</span> }<a name="line.387"></a> |
| <span class="sourceLineNo">388</span> }<a name="line.388"></a> |
| <span class="sourceLineNo">389</span><a name="line.389"></a> |
| <span class="sourceLineNo">390</span> return points;<a name="line.390"></a> |
| <span class="sourceLineNo">391</span> }<a name="line.391"></a> |
| <span class="sourceLineNo">392</span><a name="line.392"></a> |
| <span class="sourceLineNo">393</span> /**<a name="line.393"></a> |
| <span class="sourceLineNo">394</span> * @param a dataset<a name="line.394"></a> |
| <span class="sourceLineNo">395</span> * @param axis<a name="line.395"></a> |
| <span class="sourceLineNo">396</span> * @return median<a name="line.396"></a> |
| <span class="sourceLineNo">397</span> */<a name="line.397"></a> |
| <span class="sourceLineNo">398</span> public static Dataset median(final Dataset a, int axis) {<a name="line.398"></a> |
| <span class="sourceLineNo">399</span> axis = a.checkAxis(axis);<a name="line.399"></a> |
| <span class="sourceLineNo">400</span> return getQStatistics(a, axis).getQuantile(axis, QStatisticsImpl.Q2);<a name="line.400"></a> |
| <span class="sourceLineNo">401</span> }<a name="line.401"></a> |
| <span class="sourceLineNo">402</span><a name="line.402"></a> |
| <span class="sourceLineNo">403</span> /**<a name="line.403"></a> |
| <span class="sourceLineNo">404</span> * @param a dataset<a name="line.404"></a> |
| <span class="sourceLineNo">405</span> * @return median<a name="line.405"></a> |
| <span class="sourceLineNo">406</span> */<a name="line.406"></a> |
| <span class="sourceLineNo">407</span> public static Object median(final Dataset a) {<a name="line.407"></a> |
| <span class="sourceLineNo">408</span> return getQStatistics(a).getQuantile(QStatisticsImpl.Q2);<a name="line.408"></a> |
| <span class="sourceLineNo">409</span> }<a name="line.409"></a> |
| <span class="sourceLineNo">410</span><a name="line.410"></a> |
| <span class="sourceLineNo">411</span> /**<a name="line.411"></a> |
| <span class="sourceLineNo">412</span> * Interquartile range: Q3 - Q1<a name="line.412"></a> |
| <span class="sourceLineNo">413</span> * @param a<a name="line.413"></a> |
| <span class="sourceLineNo">414</span> * @return range<a name="line.414"></a> |
| <span class="sourceLineNo">415</span> */<a name="line.415"></a> |
| <span class="sourceLineNo">416</span> @SuppressWarnings("unchecked")<a name="line.416"></a> |
| <span class="sourceLineNo">417</span> public static Object iqr(final Dataset a) {<a name="line.417"></a> |
| <span class="sourceLineNo">418</span> final int is = a.getElementsPerItem();<a name="line.418"></a> |
| <span class="sourceLineNo">419</span> if (is == 1) {<a name="line.419"></a> |
| <span class="sourceLineNo">420</span> QStatisticsImpl<Double> qs = (QStatisticsImpl<Double>) getQStatistics(a);<a name="line.420"></a> |
| <span class="sourceLineNo">421</span> return qs.getQuantile(QStatisticsImpl.Q3) - qs.getQuantile(QStatisticsImpl.Q1);<a name="line.421"></a> |
| <span class="sourceLineNo">422</span> }<a name="line.422"></a> |
| <span class="sourceLineNo">423</span><a name="line.423"></a> |
| <span class="sourceLineNo">424</span> QStatisticsImpl<double[]> qs = (QStatisticsImpl<double[]>) getQStatistics(a);<a name="line.424"></a> |
| <span class="sourceLineNo">425</span> double[] q1 = (double[]) qs.getQuantile(QStatisticsImpl.Q1);<a name="line.425"></a> |
| <span class="sourceLineNo">426</span> double[] q3 = ((double[]) qs.getQuantile(QStatisticsImpl.Q3)).clone();<a name="line.426"></a> |
| <span class="sourceLineNo">427</span> for (int j = 0; j < is; j++) {<a name="line.427"></a> |
| <span class="sourceLineNo">428</span> q3[j] -= q1[j];<a name="line.428"></a> |
| <span class="sourceLineNo">429</span> }<a name="line.429"></a> |
| <span class="sourceLineNo">430</span> return q3;<a name="line.430"></a> |
| <span class="sourceLineNo">431</span> }<a name="line.431"></a> |
| <span class="sourceLineNo">432</span><a name="line.432"></a> |
| <span class="sourceLineNo">433</span> /**<a name="line.433"></a> |
| <span class="sourceLineNo">434</span> * Interquartile range: Q3 - Q1<a name="line.434"></a> |
| <span class="sourceLineNo">435</span> * @param a<a name="line.435"></a> |
| <span class="sourceLineNo">436</span> * @param axis<a name="line.436"></a> |
| <span class="sourceLineNo">437</span> * @return range<a name="line.437"></a> |
| <span class="sourceLineNo">438</span> */<a name="line.438"></a> |
| <span class="sourceLineNo">439</span> public static Dataset iqr(final Dataset a, int axis) {<a name="line.439"></a> |
| <span class="sourceLineNo">440</span> axis = a.checkAxis(axis);<a name="line.440"></a> |
| <span class="sourceLineNo">441</span> QStatisticsImpl<?> qs = getQStatistics(a, axis);<a name="line.441"></a> |
| <span class="sourceLineNo">442</span> Dataset q3 = qs.getQuantile(axis, QStatisticsImpl.Q3);<a name="line.442"></a> |
| <span class="sourceLineNo">443</span><a name="line.443"></a> |
| <span class="sourceLineNo">444</span> return Maths.subtract(q3, qs.getQuantile(axis, QStatisticsImpl.Q1));<a name="line.444"></a> |
| <span class="sourceLineNo">445</span> }<a name="line.445"></a> |
| <span class="sourceLineNo">446</span><a name="line.446"></a> |
| <span class="sourceLineNo">447</span> static private HigherStatisticsImpl<?> getHigherStatistic(final Dataset a, boolean[] ignoreInvalids) {<a name="line.447"></a> |
| <span class="sourceLineNo">448</span> boolean ignoreNaNs = false;<a name="line.448"></a> |
| <span class="sourceLineNo">449</span> boolean ignoreInfs = false;<a name="line.449"></a> |
| <span class="sourceLineNo">450</span> if (a.hasFloatingPointElements()) {<a name="line.450"></a> |
| <span class="sourceLineNo">451</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.451"></a> |
| <span class="sourceLineNo">452</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.452"></a> |
| <span class="sourceLineNo">453</span> }<a name="line.453"></a> |
| <span class="sourceLineNo">454</span><a name="line.454"></a> |
| <span class="sourceLineNo">455</span> HigherStatisticsImpl<?> stats = a.getFirstMetadata(HigherStatisticsImpl.class);<a name="line.455"></a> |
| <span class="sourceLineNo">456</span> if (stats == null || stats.isDirty) {<a name="line.456"></a> |
| <span class="sourceLineNo">457</span> stats = calculateHigherMoments(a, ignoreNaNs, ignoreInfs);<a name="line.457"></a> |
| <span class="sourceLineNo">458</span> a.setMetadata(stats);<a name="line.458"></a> |
| <span class="sourceLineNo">459</span> }<a name="line.459"></a> |
| <span class="sourceLineNo">460</span> <a name="line.460"></a> |
| <span class="sourceLineNo">461</span> return stats;<a name="line.461"></a> |
| <span class="sourceLineNo">462</span> }<a name="line.462"></a> |
| <span class="sourceLineNo">463</span><a name="line.463"></a> |
| <span class="sourceLineNo">464</span> static private HigherStatisticsImpl<?> getHigherStatistic(final Dataset a, final boolean[] ignoreInvalids, final int axis) {<a name="line.464"></a> |
| <span class="sourceLineNo">465</span> boolean ignoreNaNs = false;<a name="line.465"></a> |
| <span class="sourceLineNo">466</span> boolean ignoreInfs = false;<a name="line.466"></a> |
| <span class="sourceLineNo">467</span> if (a.hasFloatingPointElements()) {<a name="line.467"></a> |
| <span class="sourceLineNo">468</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.468"></a> |
| <span class="sourceLineNo">469</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.469"></a> |
| <span class="sourceLineNo">470</span> }<a name="line.470"></a> |
| <span class="sourceLineNo">471</span> <a name="line.471"></a> |
| <span class="sourceLineNo">472</span> HigherStatisticsImpl<?> stats = a.getFirstMetadata(HigherStatisticsImpl.class);<a name="line.472"></a> |
| <span class="sourceLineNo">473</span> if (stats == null || stats.getSkewness(axis) == null || stats.isDirty) {<a name="line.473"></a> |
| <span class="sourceLineNo">474</span> stats = calculateHigherMoments(a, ignoreNaNs, ignoreInfs, axis);<a name="line.474"></a> |
| <span class="sourceLineNo">475</span> a.setMetadata(stats);<a name="line.475"></a> |
| <span class="sourceLineNo">476</span> }<a name="line.476"></a> |
| <span class="sourceLineNo">477</span> <a name="line.477"></a> |
| <span class="sourceLineNo">478</span> return stats;<a name="line.478"></a> |
| <span class="sourceLineNo">479</span> }<a name="line.479"></a> |
| <span class="sourceLineNo">480</span><a name="line.480"></a> |
| <span class="sourceLineNo">481</span> private static class HigherStatisticsImpl<T> implements MetadataType {<a name="line.481"></a> |
| <span class="sourceLineNo">482</span> private static final long serialVersionUID = -6587974784104116792L;<a name="line.482"></a> |
| <span class="sourceLineNo">483</span> T skewness;<a name="line.483"></a> |
| <span class="sourceLineNo">484</span> T kurtosis;<a name="line.484"></a> |
| <span class="sourceLineNo">485</span> transient Map<Integer, ReferencedDataset> smap = new HashMap<>();<a name="line.485"></a> |
| <span class="sourceLineNo">486</span> transient Map<Integer, ReferencedDataset> kmap = new HashMap<>();<a name="line.486"></a> |
| <span class="sourceLineNo">487</span><a name="line.487"></a> |
| <span class="sourceLineNo">488</span> @Dirtiable<a name="line.488"></a> |
| <span class="sourceLineNo">489</span> private boolean isDirty = true;<a name="line.489"></a> |
| <span class="sourceLineNo">490</span><a name="line.490"></a> |
| <span class="sourceLineNo">491</span> @Override<a name="line.491"></a> |
| <span class="sourceLineNo">492</span> public HigherStatisticsImpl<T> clone() {<a name="line.492"></a> |
| <span class="sourceLineNo">493</span> return new HigherStatisticsImpl<>(this);<a name="line.493"></a> |
| <span class="sourceLineNo">494</span> }<a name="line.494"></a> |
| <span class="sourceLineNo">495</span><a name="line.495"></a> |
| <span class="sourceLineNo">496</span> public HigherStatisticsImpl() {<a name="line.496"></a> |
| <span class="sourceLineNo">497</span> }<a name="line.497"></a> |
| <span class="sourceLineNo">498</span><a name="line.498"></a> |
| <span class="sourceLineNo">499</span> private HigherStatisticsImpl(HigherStatisticsImpl<T> hstats) {<a name="line.499"></a> |
| <span class="sourceLineNo">500</span> skewness = hstats.skewness;<a name="line.500"></a> |
| <span class="sourceLineNo">501</span> kurtosis = hstats.kurtosis;<a name="line.501"></a> |
| <span class="sourceLineNo">502</span> smap.putAll(hstats.smap);<a name="line.502"></a> |
| <span class="sourceLineNo">503</span> kmap.putAll(hstats.kmap);<a name="line.503"></a> |
| <span class="sourceLineNo">504</span> isDirty = hstats.isDirty;<a name="line.504"></a> |
| <span class="sourceLineNo">505</span> }<a name="line.505"></a> |
| <span class="sourceLineNo">506</span><a name="line.506"></a> |
| <span class="sourceLineNo">507</span>// public void setSkewness(T skewness) {<a name="line.507"></a> |
| <span class="sourceLineNo">508</span>// this.skewness = skewness;<a name="line.508"></a> |
| <span class="sourceLineNo">509</span>// }<a name="line.509"></a> |
| <span class="sourceLineNo">510</span>//<a name="line.510"></a> |
| <span class="sourceLineNo">511</span>// public void setKurtosis(T kurtosis) {<a name="line.511"></a> |
| <span class="sourceLineNo">512</span>// this.kurtosis = kurtosis;<a name="line.512"></a> |
| <span class="sourceLineNo">513</span>// }<a name="line.513"></a> |
| <span class="sourceLineNo">514</span>//<a name="line.514"></a> |
| <span class="sourceLineNo">515</span>// public T getSkewness() {<a name="line.515"></a> |
| <span class="sourceLineNo">516</span>// return skewness;<a name="line.516"></a> |
| <span class="sourceLineNo">517</span>// }<a name="line.517"></a> |
| <span class="sourceLineNo">518</span>//<a name="line.518"></a> |
| <span class="sourceLineNo">519</span>// public T getKurtosis() {<a name="line.519"></a> |
| <span class="sourceLineNo">520</span>// return kurtosis;<a name="line.520"></a> |
| <span class="sourceLineNo">521</span>// }<a name="line.521"></a> |
| <span class="sourceLineNo">522</span><a name="line.522"></a> |
| <span class="sourceLineNo">523</span> public Dataset getSkewness(int axis) {<a name="line.523"></a> |
| <span class="sourceLineNo">524</span> ReferencedDataset rd = smap.get(axis);<a name="line.524"></a> |
| <span class="sourceLineNo">525</span> return rd == null ? null : rd.get();<a name="line.525"></a> |
| <span class="sourceLineNo">526</span> }<a name="line.526"></a> |
| <span class="sourceLineNo">527</span><a name="line.527"></a> |
| <span class="sourceLineNo">528</span> public Dataset getKurtosis(int axis) {<a name="line.528"></a> |
| <span class="sourceLineNo">529</span> ReferencedDataset rd = kmap.get(axis);<a name="line.529"></a> |
| <span class="sourceLineNo">530</span> return rd == null ? null : rd.get();<a name="line.530"></a> |
| <span class="sourceLineNo">531</span> }<a name="line.531"></a> |
| <span class="sourceLineNo">532</span><a name="line.532"></a> |
| <span class="sourceLineNo">533</span> public void setSkewness(int axis, Dataset s) {<a name="line.533"></a> |
| <span class="sourceLineNo">534</span> smap.put(axis, new ReferencedDataset(s));<a name="line.534"></a> |
| <span class="sourceLineNo">535</span> }<a name="line.535"></a> |
| <span class="sourceLineNo">536</span><a name="line.536"></a> |
| <span class="sourceLineNo">537</span> public void setKurtosis(int axis, Dataset k) {<a name="line.537"></a> |
| <span class="sourceLineNo">538</span> kmap.put(axis, new ReferencedDataset(k));<a name="line.538"></a> |
| <span class="sourceLineNo">539</span> }<a name="line.539"></a> |
| <span class="sourceLineNo">540</span> }<a name="line.540"></a> |
| <span class="sourceLineNo">541</span><a name="line.541"></a> |
| <span class="sourceLineNo">542</span> static private HigherStatisticsImpl<?> calculateHigherMoments(final Dataset a, final boolean ignoreNaNs, final boolean ignoreInfs) {<a name="line.542"></a> |
| <span class="sourceLineNo">543</span> final int is = a.getElementsPerItem();<a name="line.543"></a> |
| <span class="sourceLineNo">544</span> final IndexIterator iter = a.getIterator();<a name="line.544"></a> |
| <span class="sourceLineNo">545</span><a name="line.545"></a> |
| <span class="sourceLineNo">546</span> if (is == 1) {<a name="line.546"></a> |
| <span class="sourceLineNo">547</span> Skewness s = new Skewness();<a name="line.547"></a> |
| <span class="sourceLineNo">548</span> Kurtosis k = new Kurtosis();<a name="line.548"></a> |
| <span class="sourceLineNo">549</span> if (ignoreNaNs) {<a name="line.549"></a> |
| <span class="sourceLineNo">550</span> while (iter.hasNext()) {<a name="line.550"></a> |
| <span class="sourceLineNo">551</span> final double x = a.getElementDoubleAbs(iter.index);<a name="line.551"></a> |
| <span class="sourceLineNo">552</span> if (Double.isNaN(x))<a name="line.552"></a> |
| <span class="sourceLineNo">553</span> continue;<a name="line.553"></a> |
| <span class="sourceLineNo">554</span> s.increment(x);<a name="line.554"></a> |
| <span class="sourceLineNo">555</span> k.increment(x);<a name="line.555"></a> |
| <span class="sourceLineNo">556</span> }<a name="line.556"></a> |
| <span class="sourceLineNo">557</span> } else {<a name="line.557"></a> |
| <span class="sourceLineNo">558</span> while (iter.hasNext()) {<a name="line.558"></a> |
| <span class="sourceLineNo">559</span> final double x = a.getElementDoubleAbs(iter.index);<a name="line.559"></a> |
| <span class="sourceLineNo">560</span> s.increment(x);<a name="line.560"></a> |
| <span class="sourceLineNo">561</span> k.increment(x);<a name="line.561"></a> |
| <span class="sourceLineNo">562</span> }<a name="line.562"></a> |
| <span class="sourceLineNo">563</span> }<a name="line.563"></a> |
| <span class="sourceLineNo">564</span><a name="line.564"></a> |
| <span class="sourceLineNo">565</span> HigherStatisticsImpl<Double> stats = new HigherStatisticsImpl<Double>();<a name="line.565"></a> |
| <span class="sourceLineNo">566</span> stats.skewness = s.getResult();<a name="line.566"></a> |
| <span class="sourceLineNo">567</span> stats.kurtosis = k.getResult();<a name="line.567"></a> |
| <span class="sourceLineNo">568</span> return stats;<a name="line.568"></a> |
| <span class="sourceLineNo">569</span> }<a name="line.569"></a> |
| <span class="sourceLineNo">570</span> final Skewness[] s = new Skewness[is];<a name="line.570"></a> |
| <span class="sourceLineNo">571</span> final Kurtosis[] k = new Kurtosis[is];<a name="line.571"></a> |
| <span class="sourceLineNo">572</span><a name="line.572"></a> |
| <span class="sourceLineNo">573</span> for (int j = 0; j < is; j++) {<a name="line.573"></a> |
| <span class="sourceLineNo">574</span> s[j] = new Skewness();<a name="line.574"></a> |
| <span class="sourceLineNo">575</span> k[j] = new Kurtosis();<a name="line.575"></a> |
| <span class="sourceLineNo">576</span> }<a name="line.576"></a> |
| <span class="sourceLineNo">577</span> if (ignoreNaNs) {<a name="line.577"></a> |
| <span class="sourceLineNo">578</span> while (iter.hasNext()) {<a name="line.578"></a> |
| <span class="sourceLineNo">579</span> boolean skip = false;<a name="line.579"></a> |
| <span class="sourceLineNo">580</span> for (int j = 0; j < is; j++) {<a name="line.580"></a> |
| <span class="sourceLineNo">581</span> if (Double.isNaN(a.getElementDoubleAbs(iter.index + j))) {<a name="line.581"></a> |
| <span class="sourceLineNo">582</span> skip = true;<a name="line.582"></a> |
| <span class="sourceLineNo">583</span> break;<a name="line.583"></a> |
| <span class="sourceLineNo">584</span> }<a name="line.584"></a> |
| <span class="sourceLineNo">585</span> }<a name="line.585"></a> |
| <span class="sourceLineNo">586</span> if (!skip)<a name="line.586"></a> |
| <span class="sourceLineNo">587</span> for (int j = 0; j < is; j++) {<a name="line.587"></a> |
| <span class="sourceLineNo">588</span> final double val = a.getElementDoubleAbs(iter.index + j);<a name="line.588"></a> |
| <span class="sourceLineNo">589</span> s[j].increment(val);<a name="line.589"></a> |
| <span class="sourceLineNo">590</span> k[j].increment(val);<a name="line.590"></a> |
| <span class="sourceLineNo">591</span> }<a name="line.591"></a> |
| <span class="sourceLineNo">592</span> }<a name="line.592"></a> |
| <span class="sourceLineNo">593</span> } else {<a name="line.593"></a> |
| <span class="sourceLineNo">594</span> while (iter.hasNext()) {<a name="line.594"></a> |
| <span class="sourceLineNo">595</span> for (int j = 0; j < is; j++) {<a name="line.595"></a> |
| <span class="sourceLineNo">596</span> final double val = a.getElementDoubleAbs(iter.index + j);<a name="line.596"></a> |
| <span class="sourceLineNo">597</span> s[j].increment(val);<a name="line.597"></a> |
| <span class="sourceLineNo">598</span> k[j].increment(val);<a name="line.598"></a> |
| <span class="sourceLineNo">599</span> }<a name="line.599"></a> |
| <span class="sourceLineNo">600</span> }<a name="line.600"></a> |
| <span class="sourceLineNo">601</span> }<a name="line.601"></a> |
| <span class="sourceLineNo">602</span> final double[] ts = new double[is];<a name="line.602"></a> |
| <span class="sourceLineNo">603</span> final double[] tk = new double[is];<a name="line.603"></a> |
| <span class="sourceLineNo">604</span> for (int j = 0; j < is; j++) {<a name="line.604"></a> |
| <span class="sourceLineNo">605</span> ts[j] = s[j].getResult();<a name="line.605"></a> |
| <span class="sourceLineNo">606</span> tk[j] = k[j].getResult();<a name="line.606"></a> |
| <span class="sourceLineNo">607</span> }<a name="line.607"></a> |
| <span class="sourceLineNo">608</span><a name="line.608"></a> |
| <span class="sourceLineNo">609</span> HigherStatisticsImpl<double[]> stats = new HigherStatisticsImpl<double[]>();<a name="line.609"></a> |
| <span class="sourceLineNo">610</span> stats.skewness = ts;<a name="line.610"></a> |
| <span class="sourceLineNo">611</span> stats.kurtosis = tk;<a name="line.611"></a> |
| <span class="sourceLineNo">612</span> return stats;<a name="line.612"></a> |
| <span class="sourceLineNo">613</span> }<a name="line.613"></a> |
| <span class="sourceLineNo">614</span><a name="line.614"></a> |
| <span class="sourceLineNo">615</span> static private HigherStatisticsImpl<?> calculateHigherMoments(final Dataset a, final boolean ignoreNaNs, final boolean ignoreInfs, final int axis) {<a name="line.615"></a> |
| <span class="sourceLineNo">616</span> final int rank = a.getRank();<a name="line.616"></a> |
| <span class="sourceLineNo">617</span> final int is = a.getElementsPerItem();<a name="line.617"></a> |
| <span class="sourceLineNo">618</span> final int[] oshape = a.getShape();<a name="line.618"></a> |
| <span class="sourceLineNo">619</span> final int alen = oshape[axis];<a name="line.619"></a> |
| <span class="sourceLineNo">620</span> oshape[axis] = 1;<a name="line.620"></a> |
| <span class="sourceLineNo">621</span> <a name="line.621"></a> |
| <span class="sourceLineNo">622</span> final int[] nshape = ShapeUtils.squeezeShape(oshape, false);<a name="line.622"></a> |
| <span class="sourceLineNo">623</span> final Dataset sk;<a name="line.623"></a> |
| <span class="sourceLineNo">624</span> final Dataset ku;<a name="line.624"></a> |
| <span class="sourceLineNo">625</span> HigherStatisticsImpl<?> stats = null;<a name="line.625"></a> |
| <span class="sourceLineNo">626</span> <a name="line.626"></a> |
| <span class="sourceLineNo">627</span> if (is == 1) {<a name="line.627"></a> |
| <span class="sourceLineNo">628</span> if (stats == null) {<a name="line.628"></a> |
| <span class="sourceLineNo">629</span> stats = new HigherStatisticsImpl<Double>();<a name="line.629"></a> |
| <span class="sourceLineNo">630</span> a.setMetadata(stats);<a name="line.630"></a> |
| <span class="sourceLineNo">631</span> }<a name="line.631"></a> |
| <span class="sourceLineNo">632</span> sk = DatasetFactory.zeros(DoubleDataset.class, nshape);<a name="line.632"></a> |
| <span class="sourceLineNo">633</span> ku = DatasetFactory.zeros(DoubleDataset.class, nshape);<a name="line.633"></a> |
| <span class="sourceLineNo">634</span> final IndexIterator qiter = sk.getIterator(true);<a name="line.634"></a> |
| <span class="sourceLineNo">635</span> final int[] qpos = qiter.getPos();<a name="line.635"></a> |
| <span class="sourceLineNo">636</span> final int[] spos = oshape;<a name="line.636"></a> |
| <span class="sourceLineNo">637</span> <a name="line.637"></a> |
| <span class="sourceLineNo">638</span> while (qiter.hasNext()) {<a name="line.638"></a> |
| <span class="sourceLineNo">639</span> int i = 0;<a name="line.639"></a> |
| <span class="sourceLineNo">640</span> for (; i < axis; i++) {<a name="line.640"></a> |
| <span class="sourceLineNo">641</span> spos[i] = qpos[i];<a name="line.641"></a> |
| <span class="sourceLineNo">642</span> }<a name="line.642"></a> |
| <span class="sourceLineNo">643</span> spos[i++] = 0;<a name="line.643"></a> |
| <span class="sourceLineNo">644</span> for (; i < rank; i++) {<a name="line.644"></a> |
| <span class="sourceLineNo">645</span> spos[i] = qpos[i - 1];<a name="line.645"></a> |
| <span class="sourceLineNo">646</span> }<a name="line.646"></a> |
| <span class="sourceLineNo">647</span> <a name="line.647"></a> |
| <span class="sourceLineNo">648</span> Skewness s = new Skewness();<a name="line.648"></a> |
| <span class="sourceLineNo">649</span> Kurtosis k = new Kurtosis();<a name="line.649"></a> |
| <span class="sourceLineNo">650</span> if (ignoreNaNs) {<a name="line.650"></a> |
| <span class="sourceLineNo">651</span> for (int j = 0; j < alen; j++) {<a name="line.651"></a> |
| <span class="sourceLineNo">652</span> spos[axis] = j;<a name="line.652"></a> |
| <span class="sourceLineNo">653</span> final double val = a.getDouble(spos);<a name="line.653"></a> |
| <span class="sourceLineNo">654</span> if (Double.isNaN(val))<a name="line.654"></a> |
| <span class="sourceLineNo">655</span> continue;<a name="line.655"></a> |
| <span class="sourceLineNo">656</span> <a name="line.656"></a> |
| <span class="sourceLineNo">657</span> s.increment(val);<a name="line.657"></a> |
| <span class="sourceLineNo">658</span> k.increment(val);<a name="line.658"></a> |
| <span class="sourceLineNo">659</span> }<a name="line.659"></a> |
| <span class="sourceLineNo">660</span> } else {<a name="line.660"></a> |
| <span class="sourceLineNo">661</span> for (int j = 0; j < alen; j++) {<a name="line.661"></a> |
| <span class="sourceLineNo">662</span> spos[axis] = j;<a name="line.662"></a> |
| <span class="sourceLineNo">663</span> final double val = a.getDouble(spos);<a name="line.663"></a> |
| <span class="sourceLineNo">664</span> s.increment(val);<a name="line.664"></a> |
| <span class="sourceLineNo">665</span> k.increment(val);<a name="line.665"></a> |
| <span class="sourceLineNo">666</span> }<a name="line.666"></a> |
| <span class="sourceLineNo">667</span> }<a name="line.667"></a> |
| <span class="sourceLineNo">668</span> sk.set(s.getResult(), qpos);<a name="line.668"></a> |
| <span class="sourceLineNo">669</span> ku.set(k.getResult(), qpos);<a name="line.669"></a> |
| <span class="sourceLineNo">670</span> }<a name="line.670"></a> |
| <span class="sourceLineNo">671</span> } else {<a name="line.671"></a> |
| <span class="sourceLineNo">672</span> if (stats == null) {<a name="line.672"></a> |
| <span class="sourceLineNo">673</span> stats = new HigherStatisticsImpl<double[]>();<a name="line.673"></a> |
| <span class="sourceLineNo">674</span> a.setMetadata(stats);<a name="line.674"></a> |
| <span class="sourceLineNo">675</span> }<a name="line.675"></a> |
| <span class="sourceLineNo">676</span> sk = DatasetFactory.zeros(is, CompoundDoubleDataset.class, nshape);<a name="line.676"></a> |
| <span class="sourceLineNo">677</span> ku = DatasetFactory.zeros(is, CompoundDoubleDataset.class, nshape);<a name="line.677"></a> |
| <span class="sourceLineNo">678</span> final IndexIterator qiter = sk.getIterator(true);<a name="line.678"></a> |
| <span class="sourceLineNo">679</span> final int[] qpos = qiter.getPos();<a name="line.679"></a> |
| <span class="sourceLineNo">680</span> final int[] spos = oshape;<a name="line.680"></a> |
| <span class="sourceLineNo">681</span> final Skewness[] s = new Skewness[is];<a name="line.681"></a> |
| <span class="sourceLineNo">682</span> final Kurtosis[] k = new Kurtosis[is];<a name="line.682"></a> |
| <span class="sourceLineNo">683</span> final double[] ts = new double[is];<a name="line.683"></a> |
| <span class="sourceLineNo">684</span> final double[] tk = new double[is];<a name="line.684"></a> |
| <span class="sourceLineNo">685</span> <a name="line.685"></a> |
| <span class="sourceLineNo">686</span> for (int j = 0; j < is; j++) {<a name="line.686"></a> |
| <span class="sourceLineNo">687</span> s[j] = new Skewness();<a name="line.687"></a> |
| <span class="sourceLineNo">688</span> k[j] = new Kurtosis();<a name="line.688"></a> |
| <span class="sourceLineNo">689</span> }<a name="line.689"></a> |
| <span class="sourceLineNo">690</span> while (qiter.hasNext()) {<a name="line.690"></a> |
| <span class="sourceLineNo">691</span> int i = 0;<a name="line.691"></a> |
| <span class="sourceLineNo">692</span> for (; i < axis; i++) {<a name="line.692"></a> |
| <span class="sourceLineNo">693</span> spos[i] = qpos[i];<a name="line.693"></a> |
| <span class="sourceLineNo">694</span> }<a name="line.694"></a> |
| <span class="sourceLineNo">695</span> spos[i++] = 0;<a name="line.695"></a> |
| <span class="sourceLineNo">696</span> for (; i < rank; i++) {<a name="line.696"></a> |
| <span class="sourceLineNo">697</span> spos[i] = qpos[i-1];<a name="line.697"></a> |
| <span class="sourceLineNo">698</span> }<a name="line.698"></a> |
| <span class="sourceLineNo">699</span> <a name="line.699"></a> |
| <span class="sourceLineNo">700</span> for (int j = 0; j < is; j++) {<a name="line.700"></a> |
| <span class="sourceLineNo">701</span> s[j].clear();<a name="line.701"></a> |
| <span class="sourceLineNo">702</span> k[j].clear();<a name="line.702"></a> |
| <span class="sourceLineNo">703</span> }<a name="line.703"></a> |
| <span class="sourceLineNo">704</span> int index = a.get1DIndex(spos);<a name="line.704"></a> |
| <span class="sourceLineNo">705</span> if (ignoreNaNs) {<a name="line.705"></a> |
| <span class="sourceLineNo">706</span> boolean skip = false;<a name="line.706"></a> |
| <span class="sourceLineNo">707</span> for (int j = 0; j < is; j++) {<a name="line.707"></a> |
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| <span class="sourceLineNo">714</span> for (int j = 0; j < is; j++) {<a name="line.714"></a> |
| <span class="sourceLineNo">715</span> final double val = a.getElementDoubleAbs(index + j);<a name="line.715"></a> |
| <span class="sourceLineNo">716</span> s[j].increment(val);<a name="line.716"></a> |
| <span class="sourceLineNo">717</span> k[j].increment(val);<a name="line.717"></a> |
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| <span class="sourceLineNo">719</span> } else {<a name="line.719"></a> |
| <span class="sourceLineNo">720</span> for (int j = 0; j < is; j++) {<a name="line.720"></a> |
| <span class="sourceLineNo">721</span> final double val = a.getElementDoubleAbs(index + j);<a name="line.721"></a> |
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| <span class="sourceLineNo">723</span> k[j].increment(val);<a name="line.723"></a> |
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| <span class="sourceLineNo">725</span> }<a name="line.725"></a> |
| <span class="sourceLineNo">726</span> for (int j = 0; j < is; j++) {<a name="line.726"></a> |
| <span class="sourceLineNo">727</span> ts[j] = s[j].getResult(); <a name="line.727"></a> |
| <span class="sourceLineNo">728</span> tk[j] = k[j].getResult(); <a name="line.728"></a> |
| <span class="sourceLineNo">729</span> }<a name="line.729"></a> |
| <span class="sourceLineNo">730</span> sk.set(ts, qpos);<a name="line.730"></a> |
| <span class="sourceLineNo">731</span> ku.set(tk, qpos);<a name="line.731"></a> |
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| <span class="sourceLineNo">733</span> }<a name="line.733"></a> |
| <span class="sourceLineNo">734</span><a name="line.734"></a> |
| <span class="sourceLineNo">735</span> stats.setSkewness(axis, sk);<a name="line.735"></a> |
| <span class="sourceLineNo">736</span> stats.setKurtosis(axis, ku);<a name="line.736"></a> |
| <span class="sourceLineNo">737</span> return stats;<a name="line.737"></a> |
| <span class="sourceLineNo">738</span> }<a name="line.738"></a> |
| <span class="sourceLineNo">739</span><a name="line.739"></a> |
| <span class="sourceLineNo">740</span> /**<a name="line.740"></a> |
| <span class="sourceLineNo">741</span> * @param a dataset<a name="line.741"></a> |
| <span class="sourceLineNo">742</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.742"></a> |
| <span class="sourceLineNo">743</span> * @return skewness<a name="line.743"></a> |
| <span class="sourceLineNo">744</span> * @since 2.0<a name="line.744"></a> |
| <span class="sourceLineNo">745</span> */<a name="line.745"></a> |
| <span class="sourceLineNo">746</span> public static Object skewness(final Dataset a, final boolean... ignoreInvalids) {<a name="line.746"></a> |
| <span class="sourceLineNo">747</span> return getHigherStatistic(a, ignoreInvalids).skewness;<a name="line.747"></a> |
| <span class="sourceLineNo">748</span> }<a name="line.748"></a> |
| <span class="sourceLineNo">749</span><a name="line.749"></a> |
| <span class="sourceLineNo">750</span> /**<a name="line.750"></a> |
| <span class="sourceLineNo">751</span> * @param a dataset<a name="line.751"></a> |
| <span class="sourceLineNo">752</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.752"></a> |
| <span class="sourceLineNo">753</span> * @return kurtosis<a name="line.753"></a> |
| <span class="sourceLineNo">754</span> * @since 2.0<a name="line.754"></a> |
| <span class="sourceLineNo">755</span> */<a name="line.755"></a> |
| <span class="sourceLineNo">756</span> public static Object kurtosis(final Dataset a, final boolean... ignoreInvalids) {<a name="line.756"></a> |
| <span class="sourceLineNo">757</span> return getHigherStatistic(a, ignoreInvalids).kurtosis;<a name="line.757"></a> |
| <span class="sourceLineNo">758</span> }<a name="line.758"></a> |
| <span class="sourceLineNo">759</span><a name="line.759"></a> |
| <span class="sourceLineNo">760</span> /**<a name="line.760"></a> |
| <span class="sourceLineNo">761</span> * @param a dataset<a name="line.761"></a> |
| <span class="sourceLineNo">762</span> * @param axis<a name="line.762"></a> |
| <span class="sourceLineNo">763</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.763"></a> |
| <span class="sourceLineNo">764</span> * @return skewness along axis in dataset<a name="line.764"></a> |
| <span class="sourceLineNo">765</span> * @since 2.0<a name="line.765"></a> |
| <span class="sourceLineNo">766</span> */<a name="line.766"></a> |
| <span class="sourceLineNo">767</span> public static Dataset skewness(final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.767"></a> |
| <span class="sourceLineNo">768</span> axis = a.checkAxis(axis);<a name="line.768"></a> |
| <span class="sourceLineNo">769</span> return getHigherStatistic(a, ignoreInvalids, axis).getSkewness(axis);<a name="line.769"></a> |
| <span class="sourceLineNo">770</span> }<a name="line.770"></a> |
| <span class="sourceLineNo">771</span><a name="line.771"></a> |
| <span class="sourceLineNo">772</span> /**<a name="line.772"></a> |
| <span class="sourceLineNo">773</span> * @param a dataset<a name="line.773"></a> |
| <span class="sourceLineNo">774</span> * @param axis<a name="line.774"></a> |
| <span class="sourceLineNo">775</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.775"></a> |
| <span class="sourceLineNo">776</span> * @return kurtosis along axis in dataset<a name="line.776"></a> |
| <span class="sourceLineNo">777</span> * @since 2.0<a name="line.777"></a> |
| <span class="sourceLineNo">778</span> */<a name="line.778"></a> |
| <span class="sourceLineNo">779</span> public static Dataset kurtosis(final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.779"></a> |
| <span class="sourceLineNo">780</span> axis = a.checkAxis(axis);<a name="line.780"></a> |
| <span class="sourceLineNo">781</span> return getHigherStatistic(a, ignoreInvalids, axis).getKurtosis(axis);<a name="line.781"></a> |
| <span class="sourceLineNo">782</span> }<a name="line.782"></a> |
| <span class="sourceLineNo">783</span><a name="line.783"></a> |
| <span class="sourceLineNo">784</span> /**<a name="line.784"></a> |
| <span class="sourceLineNo">785</span> * @param a dataset<a name="line.785"></a> |
| <span class="sourceLineNo">786</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.786"></a> |
| <span class="sourceLineNo">787</span> * @return sum of dataset<a name="line.787"></a> |
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| <span class="sourceLineNo">789</span> */<a name="line.789"></a> |
| <span class="sourceLineNo">790</span> public static Object sum(final Dataset a, final boolean... ignoreInvalids) {<a name="line.790"></a> |
| <span class="sourceLineNo">791</span> return a.sum(ignoreInvalids);<a name="line.791"></a> |
| <span class="sourceLineNo">792</span> }<a name="line.792"></a> |
| <span class="sourceLineNo">793</span><a name="line.793"></a> |
| <span class="sourceLineNo">794</span> /**<a name="line.794"></a> |
| <span class="sourceLineNo">795</span> * @param clazz dataset class<a name="line.795"></a> |
| <span class="sourceLineNo">796</span> * @param a dataset<a name="line.796"></a> |
| <span class="sourceLineNo">797</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.797"></a> |
| <span class="sourceLineNo">798</span> * @return typed sum of dataset<a name="line.798"></a> |
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| <span class="sourceLineNo">801</span> public static Object typedSum(final Class<? extends Dataset> clazz, final Dataset a, final boolean... ignoreInvalids) {<a name="line.801"></a> |
| <span class="sourceLineNo">802</span> if (a.isComplex()) {<a name="line.802"></a> |
| <span class="sourceLineNo">803</span> Complex m = (Complex) a.sum(ignoreInvalids);<a name="line.803"></a> |
| <span class="sourceLineNo">804</span> return m;<a name="line.804"></a> |
| <span class="sourceLineNo">805</span> } else if (a instanceof CompoundDataset) {<a name="line.805"></a> |
| <span class="sourceLineNo">806</span> return InterfaceUtils.fromDoublesToBiggestPrimitives(clazz, (double[]) a.sum(ignoreInvalids));<a name="line.806"></a> |
| <span class="sourceLineNo">807</span> }<a name="line.807"></a> |
| <span class="sourceLineNo">808</span> return InterfaceUtils.fromDoubleToBiggestNumber(clazz, DTypeUtils.toReal(a.sum(ignoreInvalids)));<a name="line.808"></a> |
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| <span class="sourceLineNo">810</span><a name="line.810"></a> |
| <span class="sourceLineNo">811</span> /**<a name="line.811"></a> |
| <span class="sourceLineNo">812</span> * @param a dataset<a name="line.812"></a> |
| <span class="sourceLineNo">813</span> * @param dtype<a name="line.813"></a> |
| <span class="sourceLineNo">814</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.814"></a> |
| <span class="sourceLineNo">815</span> * @return typed sum of dataset<a name="line.815"></a> |
| <span class="sourceLineNo">816</span> * @since 2.0<a name="line.816"></a> |
| <span class="sourceLineNo">817</span> * @deprecated Please use the class-based method {@link #typedSum(Class, Dataset, boolean...)}<a name="line.817"></a> |
| <span class="sourceLineNo">818</span> */<a name="line.818"></a> |
| <span class="sourceLineNo">819</span> @Deprecated<a name="line.819"></a> |
| <span class="sourceLineNo">820</span> public static Object typedSum(final Dataset a, int dtype, final boolean... ignoreInvalids) {<a name="line.820"></a> |
| <span class="sourceLineNo">821</span> return typedSum(DTypeUtils.getInterface(dtype), a, ignoreInvalids);<a name="line.821"></a> |
| <span class="sourceLineNo">822</span> }<a name="line.822"></a> |
| <span class="sourceLineNo">823</span><a name="line.823"></a> |
| <span class="sourceLineNo">824</span> /**<a name="line.824"></a> |
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| <span class="sourceLineNo">826</span> * @param a dataset<a name="line.826"></a> |
| <span class="sourceLineNo">827</span> * @param axis<a name="line.827"></a> |
| <span class="sourceLineNo">828</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.828"></a> |
| <span class="sourceLineNo">829</span> * @return typed sum of items along axis in dataset<a name="line.829"></a> |
| <span class="sourceLineNo">830</span> * @since 2.3<a name="line.830"></a> |
| <span class="sourceLineNo">831</span> */<a name="line.831"></a> |
| <span class="sourceLineNo">832</span> public static <T extends Dataset> T typedSum(final Class<T> clazz, final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.832"></a> |
| <span class="sourceLineNo">833</span> return a.sum(axis, ignoreInvalids).cast(clazz);<a name="line.833"></a> |
| <span class="sourceLineNo">834</span> }<a name="line.834"></a> |
| <span class="sourceLineNo">835</span><a name="line.835"></a> |
| <span class="sourceLineNo">836</span> /**<a name="line.836"></a> |
| <span class="sourceLineNo">837</span> * @param clazz dataset class<a name="line.837"></a> |
| <span class="sourceLineNo">838</span> * @param a dataset<a name="line.838"></a> |
| <span class="sourceLineNo">839</span> * @param axes<a name="line.839"></a> |
| <span class="sourceLineNo">840</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.840"></a> |
| <span class="sourceLineNo">841</span> * @return typed sum of items along axes in dataset<a name="line.841"></a> |
| <span class="sourceLineNo">842</span> * @since 2.3<a name="line.842"></a> |
| <span class="sourceLineNo">843</span> */<a name="line.843"></a> |
| <span class="sourceLineNo">844</span> public static <T extends Dataset> T typedSum(final Class<T> clazz, final Dataset a, int[] axes, final boolean... ignoreInvalids) {<a name="line.844"></a> |
| <span class="sourceLineNo">845</span> return a.sum(axes, ignoreInvalids).cast(clazz);<a name="line.845"></a> |
| <span class="sourceLineNo">846</span> }<a name="line.846"></a> |
| <span class="sourceLineNo">847</span><a name="line.847"></a> |
| <span class="sourceLineNo">848</span> /**<a name="line.848"></a> |
| <span class="sourceLineNo">849</span> * @param a dataset<a name="line.849"></a> |
| <span class="sourceLineNo">850</span> * @param dtype<a name="line.850"></a> |
| <span class="sourceLineNo">851</span> * @param axis<a name="line.851"></a> |
| <span class="sourceLineNo">852</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.852"></a> |
| <span class="sourceLineNo">853</span> * @return typed sum of items along axis in dataset<a name="line.853"></a> |
| <span class="sourceLineNo">854</span> * @since 2.0<a name="line.854"></a> |
| <span class="sourceLineNo">855</span> * @deprecated Please use the class-based method {@link #typedSum(Class, Dataset, axis, boolean...)}<a name="line.855"></a> |
| <span class="sourceLineNo">856</span> */<a name="line.856"></a> |
| <span class="sourceLineNo">857</span> @Deprecated<a name="line.857"></a> |
| <span class="sourceLineNo">858</span> public static Dataset typedSum(final Dataset a, int dtype, int axis, final boolean... ignoreInvalids) {<a name="line.858"></a> |
| <span class="sourceLineNo">859</span> return DatasetUtils.cast(a.sum(axis, ignoreInvalids), dtype);<a name="line.859"></a> |
| <span class="sourceLineNo">860</span> }<a name="line.860"></a> |
| <span class="sourceLineNo">861</span><a name="line.861"></a> |
| <span class="sourceLineNo">862</span> /**<a name="line.862"></a> |
| <span class="sourceLineNo">863</span> * @param a dataset<a name="line.863"></a> |
| <span class="sourceLineNo">864</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.864"></a> |
| <span class="sourceLineNo">865</span> * @return product of all items in dataset<a name="line.865"></a> |
| <span class="sourceLineNo">866</span> * @since 2.0<a name="line.866"></a> |
| <span class="sourceLineNo">867</span> */<a name="line.867"></a> |
| <span class="sourceLineNo">868</span> public static Object product(final Dataset a, final boolean... ignoreInvalids) {<a name="line.868"></a> |
| <span class="sourceLineNo">869</span> return typedProduct(a.getClass(), a, ignoreInvalids);<a name="line.869"></a> |
| <span class="sourceLineNo">870</span> }<a name="line.870"></a> |
| <span class="sourceLineNo">871</span><a name="line.871"></a> |
| <span class="sourceLineNo">872</span> /**<a name="line.872"></a> |
| <span class="sourceLineNo">873</span> * @param a dataset<a name="line.873"></a> |
| <span class="sourceLineNo">874</span> * @param axis<a name="line.874"></a> |
| <span class="sourceLineNo">875</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.875"></a> |
| <span class="sourceLineNo">876</span> * @return product of items along axis in dataset<a name="line.876"></a> |
| <span class="sourceLineNo">877</span> * @since 2.0<a name="line.877"></a> |
| <span class="sourceLineNo">878</span> */<a name="line.878"></a> |
| <span class="sourceLineNo">879</span> public static Dataset product(final Dataset a, final int axis, final boolean... ignoreInvalids) {<a name="line.879"></a> |
| <span class="sourceLineNo">880</span> return typedProduct(a.getClass(), a, axis, ignoreInvalids);<a name="line.880"></a> |
| <span class="sourceLineNo">881</span> }<a name="line.881"></a> |
| <span class="sourceLineNo">882</span><a name="line.882"></a> |
| <span class="sourceLineNo">883</span> /**<a name="line.883"></a> |
| <span class="sourceLineNo">884</span> * @param a dataset<a name="line.884"></a> |
| <span class="sourceLineNo">885</span> * @param axes<a name="line.885"></a> |
| <span class="sourceLineNo">886</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.886"></a> |
| <span class="sourceLineNo">887</span> * @return product of items along axes in dataset<a name="line.887"></a> |
| <span class="sourceLineNo">888</span> * @since 2.2<a name="line.888"></a> |
| <span class="sourceLineNo">889</span> */<a name="line.889"></a> |
| <span class="sourceLineNo">890</span> public static Dataset product(final Dataset a, final int[] axes, final boolean... ignoreInvalids) {<a name="line.890"></a> |
| <span class="sourceLineNo">891</span> return typedProduct(a.getClass(), a, axes, ignoreInvalids);<a name="line.891"></a> |
| <span class="sourceLineNo">892</span> }<a name="line.892"></a> |
| <span class="sourceLineNo">893</span><a name="line.893"></a> |
| <span class="sourceLineNo">894</span> /**<a name="line.894"></a> |
| <span class="sourceLineNo">895</span> * @param clazz dataset class<a name="line.895"></a> |
| <span class="sourceLineNo">896</span> * @param a dataset<a name="line.896"></a> |
| <span class="sourceLineNo">897</span> * @param dtype<a name="line.897"></a> |
| <span class="sourceLineNo">898</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.898"></a> |
| <span class="sourceLineNo">899</span> * @return typed product of all items in dataset<a name="line.899"></a> |
| <span class="sourceLineNo">900</span> * @since 2.3<a name="line.900"></a> |
| <span class="sourceLineNo">901</span> */<a name="line.901"></a> |
| <span class="sourceLineNo">902</span> public static Object typedProduct(final Class<? extends Dataset> clazz, final Dataset a, final boolean... ignoreInvalids) {<a name="line.902"></a> |
| <span class="sourceLineNo">903</span> return typedProduct(a, DTypeUtils.getDType(clazz), ignoreInvalids);<a name="line.903"></a> |
| <span class="sourceLineNo">904</span> }<a name="line.904"></a> |
| <span class="sourceLineNo">905</span><a name="line.905"></a> |
| <span class="sourceLineNo">906</span> /**<a name="line.906"></a> |
| <span class="sourceLineNo">907</span> * @param a dataset<a name="line.907"></a> |
| <span class="sourceLineNo">908</span> * @param dtype<a name="line.908"></a> |
| <span class="sourceLineNo">909</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.909"></a> |
| <span class="sourceLineNo">910</span> * @return typed product of all items in dataset<a name="line.910"></a> |
| <span class="sourceLineNo">911</span> * @since 2.0<a name="line.911"></a> |
| <span class="sourceLineNo">912</span> * @deprecated Please use the class-based method {@link #typedProduct(Class, Dataset, boolean...)}<a name="line.912"></a> |
| <span class="sourceLineNo">913</span> */<a name="line.913"></a> |
| <span class="sourceLineNo">914</span> @Deprecated<a name="line.914"></a> |
| <span class="sourceLineNo">915</span> public static Object typedProduct(final Dataset a, final int dtype, final boolean... ignoreInvalids) {<a name="line.915"></a> |
| <span class="sourceLineNo">916</span> final boolean ignoreNaNs;<a name="line.916"></a> |
| <span class="sourceLineNo">917</span> final boolean ignoreInfs;<a name="line.917"></a> |
| <span class="sourceLineNo">918</span> if (a.hasFloatingPointElements()) {<a name="line.918"></a> |
| <span class="sourceLineNo">919</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.919"></a> |
| <span class="sourceLineNo">920</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.920"></a> |
| <span class="sourceLineNo">921</span> } else {<a name="line.921"></a> |
| <span class="sourceLineNo">922</span> ignoreNaNs = false;<a name="line.922"></a> |
| <span class="sourceLineNo">923</span> ignoreInfs = false;<a name="line.923"></a> |
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| <span class="sourceLineNo">925</span><a name="line.925"></a> |
| <span class="sourceLineNo">926</span> if (a.isComplex()) {<a name="line.926"></a> |
| <span class="sourceLineNo">927</span> IndexIterator it = a.getIterator();<a name="line.927"></a> |
| <span class="sourceLineNo">928</span> double rv = 1, iv = 0;<a name="line.928"></a> |
| <span class="sourceLineNo">929</span><a name="line.929"></a> |
| <span class="sourceLineNo">930</span> while (it.hasNext()) {<a name="line.930"></a> |
| <span class="sourceLineNo">931</span> final double r1 = a.getElementDoubleAbs(it.index);<a name="line.931"></a> |
| <span class="sourceLineNo">932</span> final double i1 = a.getElementDoubleAbs(it.index + 1);<a name="line.932"></a> |
| <span class="sourceLineNo">933</span> if (ignoreNaNs && (Double.isNaN(r1) || Double.isNaN(i1))) {<a name="line.933"></a> |
| <span class="sourceLineNo">934</span> continue;<a name="line.934"></a> |
| <span class="sourceLineNo">935</span> }<a name="line.935"></a> |
| <span class="sourceLineNo">936</span> if (ignoreInfs && (Double.isInfinite(r1) || Double.isInfinite(i1))) {<a name="line.936"></a> |
| <span class="sourceLineNo">937</span> continue;<a name="line.937"></a> |
| <span class="sourceLineNo">938</span> }<a name="line.938"></a> |
| <span class="sourceLineNo">939</span> final double tv = r1*rv - i1*iv;<a name="line.939"></a> |
| <span class="sourceLineNo">940</span> iv = r1*iv + i1*rv;<a name="line.940"></a> |
| <span class="sourceLineNo">941</span> rv = tv;<a name="line.941"></a> |
| <span class="sourceLineNo">942</span> if (Double.isNaN(rv) && Double.isNaN(iv)) {<a name="line.942"></a> |
| <span class="sourceLineNo">943</span> break;<a name="line.943"></a> |
| <span class="sourceLineNo">944</span> }<a name="line.944"></a> |
| <span class="sourceLineNo">945</span> }<a name="line.945"></a> |
| <span class="sourceLineNo">946</span><a name="line.946"></a> |
| <span class="sourceLineNo">947</span> return new Complex(rv, iv);<a name="line.947"></a> |
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| <span class="sourceLineNo">949</span><a name="line.949"></a> |
| <span class="sourceLineNo">950</span> IndexIterator it = a.getIterator();<a name="line.950"></a> |
| <span class="sourceLineNo">951</span> final int is;<a name="line.951"></a> |
| <span class="sourceLineNo">952</span> final long[] lresults;<a name="line.952"></a> |
| <span class="sourceLineNo">953</span> final double[] dresults;<a name="line.953"></a> |
| <span class="sourceLineNo">954</span><a name="line.954"></a> |
| <span class="sourceLineNo">955</span> switch (dtype) {<a name="line.955"></a> |
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| <span class="sourceLineNo">957</span> case Dataset.INT8: case Dataset.INT16:<a name="line.957"></a> |
| <span class="sourceLineNo">958</span> case Dataset.INT32: case Dataset.INT64:<a name="line.958"></a> |
| <span class="sourceLineNo">959</span> long lresult = 1;<a name="line.959"></a> |
| <span class="sourceLineNo">960</span> while (it.hasNext()) {<a name="line.960"></a> |
| <span class="sourceLineNo">961</span> lresult *= a.getElementLongAbs(it.index);<a name="line.961"></a> |
| <span class="sourceLineNo">962</span> }<a name="line.962"></a> |
| <span class="sourceLineNo">963</span> return Long.valueOf(lresult);<a name="line.963"></a> |
| <span class="sourceLineNo">964</span> case Dataset.ARRAYINT8: case Dataset.ARRAYINT16:<a name="line.964"></a> |
| <span class="sourceLineNo">965</span> case Dataset.ARRAYINT32: case Dataset.ARRAYINT64:<a name="line.965"></a> |
| <span class="sourceLineNo">966</span> lresult = 1;<a name="line.966"></a> |
| <span class="sourceLineNo">967</span> is = a.getElementsPerItem();<a name="line.967"></a> |
| <span class="sourceLineNo">968</span> lresults = new long[is];<a name="line.968"></a> |
| <span class="sourceLineNo">969</span> for (int j = 0; j < is; j++) {<a name="line.969"></a> |
| <span class="sourceLineNo">970</span> lresults[j] = 1;<a name="line.970"></a> |
| <span class="sourceLineNo">971</span> }<a name="line.971"></a> |
| <span class="sourceLineNo">972</span> while (it.hasNext()) {<a name="line.972"></a> |
| <span class="sourceLineNo">973</span> for (int j = 0; j < is; j++)<a name="line.973"></a> |
| <span class="sourceLineNo">974</span> lresults[j] *= a.getElementLongAbs(it.index+j);<a name="line.974"></a> |
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| <span class="sourceLineNo">976</span> return lresults;<a name="line.976"></a> |
| <span class="sourceLineNo">977</span> case Dataset.FLOAT32: case Dataset.FLOAT64:<a name="line.977"></a> |
| <span class="sourceLineNo">978</span> double dresult = 1.;<a name="line.978"></a> |
| <span class="sourceLineNo">979</span> while (it.hasNext()) {<a name="line.979"></a> |
| <span class="sourceLineNo">980</span> final double x = a.getElementDoubleAbs(it.index);<a name="line.980"></a> |
| <span class="sourceLineNo">981</span> if (ignoreNaNs && Double.isNaN(x)) {<a name="line.981"></a> |
| <span class="sourceLineNo">982</span> continue;<a name="line.982"></a> |
| <span class="sourceLineNo">983</span> }<a name="line.983"></a> |
| <span class="sourceLineNo">984</span> if (ignoreInfs && Double.isInfinite(x)) {<a name="line.984"></a> |
| <span class="sourceLineNo">985</span> continue;<a name="line.985"></a> |
| <span class="sourceLineNo">986</span> }<a name="line.986"></a> |
| <span class="sourceLineNo">987</span> dresult *= x;<a name="line.987"></a> |
| <span class="sourceLineNo">988</span> if (Double.isNaN(dresult)) {<a name="line.988"></a> |
| <span class="sourceLineNo">989</span> break;<a name="line.989"></a> |
| <span class="sourceLineNo">990</span> }<a name="line.990"></a> |
| <span class="sourceLineNo">991</span> }<a name="line.991"></a> |
| <span class="sourceLineNo">992</span> return Double.valueOf(dresult);<a name="line.992"></a> |
| <span class="sourceLineNo">993</span> case Dataset.ARRAYFLOAT32:<a name="line.993"></a> |
| <span class="sourceLineNo">994</span> case Dataset.ARRAYFLOAT64:<a name="line.994"></a> |
| <span class="sourceLineNo">995</span> is = a.getElementsPerItem();<a name="line.995"></a> |
| <span class="sourceLineNo">996</span> double[] vals = new double[is];<a name="line.996"></a> |
| <span class="sourceLineNo">997</span> dresults = new double[is];<a name="line.997"></a> |
| <span class="sourceLineNo">998</span> for (int j = 0; j < is; j++) {<a name="line.998"></a> |
| <span class="sourceLineNo">999</span> dresults[j] = 1.;<a name="line.999"></a> |
| <span class="sourceLineNo">1000</span> }<a name="line.1000"></a> |
| <span class="sourceLineNo">1001</span> while (it.hasNext()) {<a name="line.1001"></a> |
| <span class="sourceLineNo">1002</span> boolean okay = true;<a name="line.1002"></a> |
| <span class="sourceLineNo">1003</span> for (int j = 0; j < is; j++) {<a name="line.1003"></a> |
| <span class="sourceLineNo">1004</span> final double val = a.getElementDoubleAbs(it.index + j);<a name="line.1004"></a> |
| <span class="sourceLineNo">1005</span> if (ignoreNaNs && Double.isNaN(val)) {<a name="line.1005"></a> |
| <span class="sourceLineNo">1006</span> okay = false;<a name="line.1006"></a> |
| <span class="sourceLineNo">1007</span> break;<a name="line.1007"></a> |
| <span class="sourceLineNo">1008</span> }<a name="line.1008"></a> |
| <span class="sourceLineNo">1009</span> if (ignoreInfs && Double.isInfinite(val)) {<a name="line.1009"></a> |
| <span class="sourceLineNo">1010</span> okay = false;<a name="line.1010"></a> |
| <span class="sourceLineNo">1011</span> break;<a name="line.1011"></a> |
| <span class="sourceLineNo">1012</span> }<a name="line.1012"></a> |
| <span class="sourceLineNo">1013</span> vals[j] = val;<a name="line.1013"></a> |
| <span class="sourceLineNo">1014</span> }<a name="line.1014"></a> |
| <span class="sourceLineNo">1015</span> if (okay) {<a name="line.1015"></a> |
| <span class="sourceLineNo">1016</span> for (int j = 0; j < is; j++) {<a name="line.1016"></a> |
| <span class="sourceLineNo">1017</span> double val = vals[j];<a name="line.1017"></a> |
| <span class="sourceLineNo">1018</span> dresults[j] *= val;<a name="line.1018"></a> |
| <span class="sourceLineNo">1019</span> }<a name="line.1019"></a> |
| <span class="sourceLineNo">1020</span> }<a name="line.1020"></a> |
| <span class="sourceLineNo">1021</span> }<a name="line.1021"></a> |
| <span class="sourceLineNo">1022</span> return dresults;<a name="line.1022"></a> |
| <span class="sourceLineNo">1023</span> }<a name="line.1023"></a> |
| <span class="sourceLineNo">1024</span><a name="line.1024"></a> |
| <span class="sourceLineNo">1025</span> return null;<a name="line.1025"></a> |
| <span class="sourceLineNo">1026</span> }<a name="line.1026"></a> |
| <span class="sourceLineNo">1027</span><a name="line.1027"></a> |
| <span class="sourceLineNo">1028</span> /**<a name="line.1028"></a> |
| <span class="sourceLineNo">1029</span> * @param clazz dataset class<a name="line.1029"></a> |
| <span class="sourceLineNo">1030</span> * @param a dataset<a name="line.1030"></a> |
| <span class="sourceLineNo">1031</span> * @param axis<a name="line.1031"></a> |
| <span class="sourceLineNo">1032</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1032"></a> |
| <span class="sourceLineNo">1033</span> * @return typed product of items along axis in dataset<a name="line.1033"></a> |
| <span class="sourceLineNo">1034</span> * @since 2.3<a name="line.1034"></a> |
| <span class="sourceLineNo">1035</span> */<a name="line.1035"></a> |
| <span class="sourceLineNo">1036</span> public static <T extends Dataset> T typedProduct(final Class<T> clazz, final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.1036"></a> |
| <span class="sourceLineNo">1037</span> return typedProduct(clazz, a, new int[] {axis}, ignoreInvalids);<a name="line.1037"></a> |
| <span class="sourceLineNo">1038</span> }<a name="line.1038"></a> |
| <span class="sourceLineNo">1039</span><a name="line.1039"></a> |
| <span class="sourceLineNo">1040</span> /**<a name="line.1040"></a> |
| <span class="sourceLineNo">1041</span> * @param clazz dataset class<a name="line.1041"></a> |
| <span class="sourceLineNo">1042</span> * @param a dataset<a name="line.1042"></a> |
| <span class="sourceLineNo">1043</span> * @param axes<a name="line.1043"></a> |
| <span class="sourceLineNo">1044</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1044"></a> |
| <span class="sourceLineNo">1045</span> * @return typed product of items in axes of dataset<a name="line.1045"></a> |
| <span class="sourceLineNo">1046</span> * @since 2.3<a name="line.1046"></a> |
| <span class="sourceLineNo">1047</span> */<a name="line.1047"></a> |
| <span class="sourceLineNo">1048</span> @SuppressWarnings("unchecked")<a name="line.1048"></a> |
| <span class="sourceLineNo">1049</span> public static <T extends Dataset> T typedProduct(final Class<T> clazz, final Dataset a, int[] axes, final boolean... ignoreInvalids) {<a name="line.1049"></a> |
| <span class="sourceLineNo">1050</span> return (T) typedProduct(a, DTypeUtils.getDType(clazz), axes, ignoreInvalids);<a name="line.1050"></a> |
| <span class="sourceLineNo">1051</span> }<a name="line.1051"></a> |
| <span class="sourceLineNo">1052</span><a name="line.1052"></a> |
| <span class="sourceLineNo">1053</span> /**<a name="line.1053"></a> |
| <span class="sourceLineNo">1054</span> * @param a dataset<a name="line.1054"></a> |
| <span class="sourceLineNo">1055</span> * @param dtype<a name="line.1055"></a> |
| <span class="sourceLineNo">1056</span> * @param axis<a name="line.1056"></a> |
| <span class="sourceLineNo">1057</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1057"></a> |
| <span class="sourceLineNo">1058</span> * @return typed product of items along axis in dataset<a name="line.1058"></a> |
| <span class="sourceLineNo">1059</span> * @since 2.0<a name="line.1059"></a> |
| <span class="sourceLineNo">1060</span> * @deprecated Please use the class-based method {@link #typedProduct(Class, Dataset, int, boolean...)}<a name="line.1060"></a> |
| <span class="sourceLineNo">1061</span> */<a name="line.1061"></a> |
| <span class="sourceLineNo">1062</span> @Deprecated<a name="line.1062"></a> |
| <span class="sourceLineNo">1063</span> public static Dataset typedProduct(final Dataset a, final int dtype, int axis, final boolean... ignoreInvalids) {<a name="line.1063"></a> |
| <span class="sourceLineNo">1064</span> return typedProduct(a, dtype, new int[] {axis}, ignoreInvalids);<a name="line.1064"></a> |
| <span class="sourceLineNo">1065</span> }<a name="line.1065"></a> |
| <span class="sourceLineNo">1066</span><a name="line.1066"></a> |
| <span class="sourceLineNo">1067</span> /**<a name="line.1067"></a> |
| <span class="sourceLineNo">1068</span> * @param a dataset<a name="line.1068"></a> |
| <span class="sourceLineNo">1069</span> * @param dtype<a name="line.1069"></a> |
| <span class="sourceLineNo">1070</span> * @param axes<a name="line.1070"></a> |
| <span class="sourceLineNo">1071</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1071"></a> |
| <span class="sourceLineNo">1072</span> * @return typed product of items in axes of dataset<a name="line.1072"></a> |
| <span class="sourceLineNo">1073</span> * @since 2.2<a name="line.1073"></a> |
| <span class="sourceLineNo">1074</span> * @deprecated Please use the class-based method {@link #typedProduct(Class, Dataset, int[], boolean...)}<a name="line.1074"></a> |
| <span class="sourceLineNo">1075</span> */<a name="line.1075"></a> |
| <span class="sourceLineNo">1076</span> @Deprecated<a name="line.1076"></a> |
| <span class="sourceLineNo">1077</span> public static Dataset typedProduct(final Dataset a, final int dtype, int[] axes, final boolean... ignoreInvalids) {<a name="line.1077"></a> |
| <span class="sourceLineNo">1078</span> axes = ShapeUtils.checkAxes(a.getRank(), axes);<a name="line.1078"></a> |
| <span class="sourceLineNo">1079</span> SliceNDIterator siter = new SliceNDIterator(new SliceND(a.getShapeRef()), axes);<a name="line.1079"></a> |
| <span class="sourceLineNo">1080</span><a name="line.1080"></a> |
| <span class="sourceLineNo">1081</span> int[] nshape = siter.getUsedSlice().getSourceShape();<a name="line.1081"></a> |
| <span class="sourceLineNo">1082</span> final int is = a.getElementsPerItem();<a name="line.1082"></a> |
| <span class="sourceLineNo">1083</span><a name="line.1083"></a> |
| <span class="sourceLineNo">1084</span> final boolean ignoreNaNs;<a name="line.1084"></a> |
| <span class="sourceLineNo">1085</span> final boolean ignoreInfs;<a name="line.1085"></a> |
| <span class="sourceLineNo">1086</span> if (a.hasFloatingPointElements()) {<a name="line.1086"></a> |
| <span class="sourceLineNo">1087</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.1087"></a> |
| <span class="sourceLineNo">1088</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.1088"></a> |
| <span class="sourceLineNo">1089</span> } else {<a name="line.1089"></a> |
| <span class="sourceLineNo">1090</span> ignoreNaNs = false;<a name="line.1090"></a> |
| <span class="sourceLineNo">1091</span> ignoreInfs = false;<a name="line.1091"></a> |
| <span class="sourceLineNo">1092</span> }<a name="line.1092"></a> |
| <span class="sourceLineNo">1093</span> Dataset result = DatasetFactory.zeros(is, nshape, dtype);<a name="line.1093"></a> |
| <span class="sourceLineNo">1094</span><a name="line.1094"></a> |
| <span class="sourceLineNo">1095</span> int[] spos = siter.getUsedPos();<a name="line.1095"></a> |
| <span class="sourceLineNo">1096</span><a name="line.1096"></a> |
| <span class="sourceLineNo">1097</span> // TODO add getLongArray(long[], int...) to CompoundDataset<a name="line.1097"></a> |
| <span class="sourceLineNo">1098</span> final boolean isComplex = a.isComplex();<a name="line.1098"></a> |
| <span class="sourceLineNo">1099</span> while (siter.hasNext()) {<a name="line.1099"></a> |
| <span class="sourceLineNo">1100</span> IndexIterator iter = a.getSliceIterator(siter.getCurrentSlice());<a name="line.1100"></a> |
| <span class="sourceLineNo">1101</span> final int[] pos = iter.getPos();<a name="line.1101"></a> |
| <span class="sourceLineNo">1102</span><a name="line.1102"></a> |
| <span class="sourceLineNo">1103</span> if (isComplex) {<a name="line.1103"></a> |
| <span class="sourceLineNo">1104</span> double rv = 1, iv = 0;<a name="line.1104"></a> |
| <span class="sourceLineNo">1105</span> switch (dtype) {<a name="line.1105"></a> |
| <span class="sourceLineNo">1106</span> case Dataset.COMPLEX64:<a name="line.1106"></a> |
| <span class="sourceLineNo">1107</span> ComplexFloatDataset af = (ComplexFloatDataset) a;<a name="line.1107"></a> |
| <span class="sourceLineNo">1108</span> while (iter.hasNext()) {<a name="line.1108"></a> |
| <span class="sourceLineNo">1109</span> final float r1 = af.getReal(pos);<a name="line.1109"></a> |
| <span class="sourceLineNo">1110</span> final float i1 = af.getImag(pos);<a name="line.1110"></a> |
| <span class="sourceLineNo">1111</span> if (ignoreNaNs && (Float.isNaN(r1) || Float.isNaN(i1))) {<a name="line.1111"></a> |
| <span class="sourceLineNo">1112</span> continue;<a name="line.1112"></a> |
| <span class="sourceLineNo">1113</span> }<a name="line.1113"></a> |
| <span class="sourceLineNo">1114</span> if (ignoreInfs && (Float.isInfinite(r1) || Float.isInfinite(i1))) {<a name="line.1114"></a> |
| <span class="sourceLineNo">1115</span> continue;<a name="line.1115"></a> |
| <span class="sourceLineNo">1116</span> }<a name="line.1116"></a> |
| <span class="sourceLineNo">1117</span> final double tv = r1*rv - i1*iv;<a name="line.1117"></a> |
| <span class="sourceLineNo">1118</span> iv = r1*iv + i1*rv;<a name="line.1118"></a> |
| <span class="sourceLineNo">1119</span> rv = tv;<a name="line.1119"></a> |
| <span class="sourceLineNo">1120</span> if (Double.isNaN(rv) && Double.isNaN(iv)) {<a name="line.1120"></a> |
| <span class="sourceLineNo">1121</span> break;<a name="line.1121"></a> |
| <span class="sourceLineNo">1122</span> }<a name="line.1122"></a> |
| <span class="sourceLineNo">1123</span> }<a name="line.1123"></a> |
| <span class="sourceLineNo">1124</span> break;<a name="line.1124"></a> |
| <span class="sourceLineNo">1125</span> case Dataset.COMPLEX128:<a name="line.1125"></a> |
| <span class="sourceLineNo">1126</span> ComplexDoubleDataset ad = (ComplexDoubleDataset) a;<a name="line.1126"></a> |
| <span class="sourceLineNo">1127</span> while (iter.hasNext()) {<a name="line.1127"></a> |
| <span class="sourceLineNo">1128</span> final double r1 = ad.getReal(pos);<a name="line.1128"></a> |
| <span class="sourceLineNo">1129</span> final double i1 = ad.getImag(pos);<a name="line.1129"></a> |
| <span class="sourceLineNo">1130</span> if (ignoreNaNs && (Double.isNaN(r1) || Double.isNaN(i1))) {<a name="line.1130"></a> |
| <span class="sourceLineNo">1131</span> continue;<a name="line.1131"></a> |
| <span class="sourceLineNo">1132</span> }<a name="line.1132"></a> |
| <span class="sourceLineNo">1133</span> if (ignoreInfs && (Double.isInfinite(r1) || Double.isInfinite(i1))) {<a name="line.1133"></a> |
| <span class="sourceLineNo">1134</span> continue;<a name="line.1134"></a> |
| <span class="sourceLineNo">1135</span> }<a name="line.1135"></a> |
| <span class="sourceLineNo">1136</span> final double tv = r1*rv - i1*iv;<a name="line.1136"></a> |
| <span class="sourceLineNo">1137</span> iv = r1*iv + i1*rv;<a name="line.1137"></a> |
| <span class="sourceLineNo">1138</span> rv = tv;<a name="line.1138"></a> |
| <span class="sourceLineNo">1139</span> if (Double.isNaN(rv) && Double.isNaN(iv)) {<a name="line.1139"></a> |
| <span class="sourceLineNo">1140</span> break;<a name="line.1140"></a> |
| <span class="sourceLineNo">1141</span> }<a name="line.1141"></a> |
| <span class="sourceLineNo">1142</span> }<a name="line.1142"></a> |
| <span class="sourceLineNo">1143</span> break;<a name="line.1143"></a> |
| <span class="sourceLineNo">1144</span> }<a name="line.1144"></a> |
| <span class="sourceLineNo">1145</span><a name="line.1145"></a> |
| <span class="sourceLineNo">1146</span> result.set(new Complex(rv, iv), spos);<a name="line.1146"></a> |
| <span class="sourceLineNo">1147</span> } else {<a name="line.1147"></a> |
| <span class="sourceLineNo">1148</span> final long[] lresults;<a name="line.1148"></a> |
| <span class="sourceLineNo">1149</span> final double[] dresults;<a name="line.1149"></a> |
| <span class="sourceLineNo">1150</span><a name="line.1150"></a> |
| <span class="sourceLineNo">1151</span> switch (dtype) {<a name="line.1151"></a> |
| <span class="sourceLineNo">1152</span> case Dataset.BOOL:<a name="line.1152"></a> |
| <span class="sourceLineNo">1153</span> case Dataset.INT8: case Dataset.INT16:<a name="line.1153"></a> |
| <span class="sourceLineNo">1154</span> case Dataset.INT32: case Dataset.INT64:<a name="line.1154"></a> |
| <span class="sourceLineNo">1155</span> long lresult = 1;<a name="line.1155"></a> |
| <span class="sourceLineNo">1156</span> while (iter.hasNext()) {<a name="line.1156"></a> |
| <span class="sourceLineNo">1157</span> lresult *= a.getInt(pos);<a name="line.1157"></a> |
| <span class="sourceLineNo">1158</span> }<a name="line.1158"></a> |
| <span class="sourceLineNo">1159</span> result.set(lresult, spos);<a name="line.1159"></a> |
| <span class="sourceLineNo">1160</span> break;<a name="line.1160"></a> |
| <span class="sourceLineNo">1161</span> case Dataset.ARRAYINT8:<a name="line.1161"></a> |
| <span class="sourceLineNo">1162</span> lresults = new long[is];<a name="line.1162"></a> |
| <span class="sourceLineNo">1163</span> for (int k = 0; k < is; k++) {<a name="line.1163"></a> |
| <span class="sourceLineNo">1164</span> lresults[k] = 1;<a name="line.1164"></a> |
| <span class="sourceLineNo">1165</span> }<a name="line.1165"></a> |
| <span class="sourceLineNo">1166</span> while (iter.hasNext()) {<a name="line.1166"></a> |
| <span class="sourceLineNo">1167</span> final byte[] va = (byte[]) a.getObject(pos);<a name="line.1167"></a> |
| <span class="sourceLineNo">1168</span> for (int k = 0; k < is; k++) {<a name="line.1168"></a> |
| <span class="sourceLineNo">1169</span> lresults[k] *= va[k];<a name="line.1169"></a> |
| <span class="sourceLineNo">1170</span> }<a name="line.1170"></a> |
| <span class="sourceLineNo">1171</span> }<a name="line.1171"></a> |
| <span class="sourceLineNo">1172</span> result.set(lresults, spos);<a name="line.1172"></a> |
| <span class="sourceLineNo">1173</span> break;<a name="line.1173"></a> |
| <span class="sourceLineNo">1174</span> case Dataset.ARRAYINT16:<a name="line.1174"></a> |
| <span class="sourceLineNo">1175</span> lresults = new long[is];<a name="line.1175"></a> |
| <span class="sourceLineNo">1176</span> for (int k = 0; k < is; k++) {<a name="line.1176"></a> |
| <span class="sourceLineNo">1177</span> lresults[k] = 1;<a name="line.1177"></a> |
| <span class="sourceLineNo">1178</span> }<a name="line.1178"></a> |
| <span class="sourceLineNo">1179</span> while (iter.hasNext()) {<a name="line.1179"></a> |
| <span class="sourceLineNo">1180</span> final short[] va = (short[]) a.getObject(pos);<a name="line.1180"></a> |
| <span class="sourceLineNo">1181</span> for (int k = 0; k < is; k++) {<a name="line.1181"></a> |
| <span class="sourceLineNo">1182</span> lresults[k] *= va[k];<a name="line.1182"></a> |
| <span class="sourceLineNo">1183</span> }<a name="line.1183"></a> |
| <span class="sourceLineNo">1184</span> }<a name="line.1184"></a> |
| <span class="sourceLineNo">1185</span> result.set(lresults, spos);<a name="line.1185"></a> |
| <span class="sourceLineNo">1186</span> break;<a name="line.1186"></a> |
| <span class="sourceLineNo">1187</span> case Dataset.ARRAYINT32:<a name="line.1187"></a> |
| <span class="sourceLineNo">1188</span> lresults = new long[is];<a name="line.1188"></a> |
| <span class="sourceLineNo">1189</span> for (int k = 0; k < is; k++) {<a name="line.1189"></a> |
| <span class="sourceLineNo">1190</span> lresults[k] = 1;<a name="line.1190"></a> |
| <span class="sourceLineNo">1191</span> }<a name="line.1191"></a> |
| <span class="sourceLineNo">1192</span> while (iter.hasNext()) {<a name="line.1192"></a> |
| <span class="sourceLineNo">1193</span> final int[] va = (int[]) a.getObject(pos);<a name="line.1193"></a> |
| <span class="sourceLineNo">1194</span> for (int k = 0; k < is; k++) {<a name="line.1194"></a> |
| <span class="sourceLineNo">1195</span> lresults[k] *= va[k];<a name="line.1195"></a> |
| <span class="sourceLineNo">1196</span> }<a name="line.1196"></a> |
| <span class="sourceLineNo">1197</span> }<a name="line.1197"></a> |
| <span class="sourceLineNo">1198</span> result.set(lresults, spos);<a name="line.1198"></a> |
| <span class="sourceLineNo">1199</span> break;<a name="line.1199"></a> |
| <span class="sourceLineNo">1200</span> case Dataset.ARRAYINT64:<a name="line.1200"></a> |
| <span class="sourceLineNo">1201</span> lresults = new long[is];<a name="line.1201"></a> |
| <span class="sourceLineNo">1202</span> for (int k = 0; k < is; k++) {<a name="line.1202"></a> |
| <span class="sourceLineNo">1203</span> lresults[k] = 1;<a name="line.1203"></a> |
| <span class="sourceLineNo">1204</span> }<a name="line.1204"></a> |
| <span class="sourceLineNo">1205</span> while (iter.hasNext()) {<a name="line.1205"></a> |
| <span class="sourceLineNo">1206</span> final long[] va = (long[]) a.getObject(pos);<a name="line.1206"></a> |
| <span class="sourceLineNo">1207</span> for (int k = 0; k < is; k++) {<a name="line.1207"></a> |
| <span class="sourceLineNo">1208</span> lresults[k] *= va[k];<a name="line.1208"></a> |
| <span class="sourceLineNo">1209</span> }<a name="line.1209"></a> |
| <span class="sourceLineNo">1210</span> }<a name="line.1210"></a> |
| <span class="sourceLineNo">1211</span> result.set(lresults, spos);<a name="line.1211"></a> |
| <span class="sourceLineNo">1212</span> break;<a name="line.1212"></a> |
| <span class="sourceLineNo">1213</span> case Dataset.FLOAT32: case Dataset.FLOAT64:<a name="line.1213"></a> |
| <span class="sourceLineNo">1214</span> double dresult = 1.;<a name="line.1214"></a> |
| <span class="sourceLineNo">1215</span> while (iter.hasNext()) {<a name="line.1215"></a> |
| <span class="sourceLineNo">1216</span> final double x = a.getElementDoubleAbs(iter.index); <a name="line.1216"></a> |
| <span class="sourceLineNo">1217</span> if (ignoreNaNs && Double.isNaN(x)) {<a name="line.1217"></a> |
| <span class="sourceLineNo">1218</span> continue;<a name="line.1218"></a> |
| <span class="sourceLineNo">1219</span> }<a name="line.1219"></a> |
| <span class="sourceLineNo">1220</span> if (ignoreInfs && Double.isInfinite(x)) {<a name="line.1220"></a> |
| <span class="sourceLineNo">1221</span> continue;<a name="line.1221"></a> |
| <span class="sourceLineNo">1222</span> }<a name="line.1222"></a> |
| <span class="sourceLineNo">1223</span> dresult *= x;<a name="line.1223"></a> |
| <span class="sourceLineNo">1224</span> if (Double.isNaN(dresult)) {<a name="line.1224"></a> |
| <span class="sourceLineNo">1225</span> break;<a name="line.1225"></a> |
| <span class="sourceLineNo">1226</span> }<a name="line.1226"></a> |
| <span class="sourceLineNo">1227</span> }<a name="line.1227"></a> |
| <span class="sourceLineNo">1228</span> result.set(dresult, spos);<a name="line.1228"></a> |
| <span class="sourceLineNo">1229</span> break;<a name="line.1229"></a> |
| <span class="sourceLineNo">1230</span> case Dataset.ARRAYFLOAT32: case Dataset.ARRAYFLOAT64:<a name="line.1230"></a> |
| <span class="sourceLineNo">1231</span> CompoundDataset da = (CompoundDataset) a;<a name="line.1231"></a> |
| <span class="sourceLineNo">1232</span> double[] dvalues = new double[is];<a name="line.1232"></a> |
| <span class="sourceLineNo">1233</span> dresults = new double[is];<a name="line.1233"></a> |
| <span class="sourceLineNo">1234</span> for (int k = 0; k < is; k++) {<a name="line.1234"></a> |
| <span class="sourceLineNo">1235</span> dresults[k] = 1.;<a name="line.1235"></a> |
| <span class="sourceLineNo">1236</span> }<a name="line.1236"></a> |
| <span class="sourceLineNo">1237</span> while (iter.hasNext()) {<a name="line.1237"></a> |
| <span class="sourceLineNo">1238</span> da.getDoubleArrayAbs(iter.index, dvalues);<a name="line.1238"></a> |
| <span class="sourceLineNo">1239</span> boolean okay = true;<a name="line.1239"></a> |
| <span class="sourceLineNo">1240</span> for (int k = 0; k < is; k++) {<a name="line.1240"></a> |
| <span class="sourceLineNo">1241</span> final double val = dvalues[k];<a name="line.1241"></a> |
| <span class="sourceLineNo">1242</span> if (ignoreNaNs && Double.isNaN(val)) {<a name="line.1242"></a> |
| <span class="sourceLineNo">1243</span> okay = false;<a name="line.1243"></a> |
| <span class="sourceLineNo">1244</span> break;<a name="line.1244"></a> |
| <span class="sourceLineNo">1245</span> }<a name="line.1245"></a> |
| <span class="sourceLineNo">1246</span> if (ignoreInfs && Double.isInfinite(val)) {<a name="line.1246"></a> |
| <span class="sourceLineNo">1247</span> okay = false;<a name="line.1247"></a> |
| <span class="sourceLineNo">1248</span> break;<a name="line.1248"></a> |
| <span class="sourceLineNo">1249</span> }<a name="line.1249"></a> |
| <span class="sourceLineNo">1250</span> }<a name="line.1250"></a> |
| <span class="sourceLineNo">1251</span> if (okay) {<a name="line.1251"></a> |
| <span class="sourceLineNo">1252</span> for (int k = 0; k < is; k++) {<a name="line.1252"></a> |
| <span class="sourceLineNo">1253</span> dresults[k] *= dvalues[k];<a name="line.1253"></a> |
| <span class="sourceLineNo">1254</span> }<a name="line.1254"></a> |
| <span class="sourceLineNo">1255</span> }<a name="line.1255"></a> |
| <span class="sourceLineNo">1256</span> }<a name="line.1256"></a> |
| <span class="sourceLineNo">1257</span> result.set(dresults, spos);<a name="line.1257"></a> |
| <span class="sourceLineNo">1258</span> break;<a name="line.1258"></a> |
| <span class="sourceLineNo">1259</span> }<a name="line.1259"></a> |
| <span class="sourceLineNo">1260</span> }<a name="line.1260"></a> |
| <span class="sourceLineNo">1261</span> }<a name="line.1261"></a> |
| <span class="sourceLineNo">1262</span><a name="line.1262"></a> |
| <span class="sourceLineNo">1263</span>// result.setShape(ShapeUtils.squeezeShape(oshape, axes));<a name="line.1263"></a> |
| <span class="sourceLineNo">1264</span> return result;<a name="line.1264"></a> |
| <span class="sourceLineNo">1265</span> }<a name="line.1265"></a> |
| <span class="sourceLineNo">1266</span><a name="line.1266"></a> |
| <span class="sourceLineNo">1267</span> /**<a name="line.1267"></a> |
| <span class="sourceLineNo">1268</span> * @param a dataset<a name="line.1268"></a> |
| <span class="sourceLineNo">1269</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1269"></a> |
| <span class="sourceLineNo">1270</span> * @return cumulative product of items in flattened dataset<a name="line.1270"></a> |
| <span class="sourceLineNo">1271</span> * @since 2.0<a name="line.1271"></a> |
| <span class="sourceLineNo">1272</span> */<a name="line.1272"></a> |
| <span class="sourceLineNo">1273</span> public static Dataset cumulativeProduct(final Dataset a, final boolean... ignoreInvalids) {<a name="line.1273"></a> |
| <span class="sourceLineNo">1274</span> return cumulativeProduct(a.flatten(), 0, ignoreInvalids);<a name="line.1274"></a> |
| <span class="sourceLineNo">1275</span> }<a name="line.1275"></a> |
| <span class="sourceLineNo">1276</span><a name="line.1276"></a> |
| <span class="sourceLineNo">1277</span> /**<a name="line.1277"></a> |
| <span class="sourceLineNo">1278</span> * @param a dataset<a name="line.1278"></a> |
| <span class="sourceLineNo">1279</span> * @param axis<a name="line.1279"></a> |
| <span class="sourceLineNo">1280</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.1280"></a> |
| <span class="sourceLineNo">1281</span> * @return cumulative product of items along axis in dataset<a name="line.1281"></a> |
| <span class="sourceLineNo">1282</span> * @since 2.0<a name="line.1282"></a> |
| <span class="sourceLineNo">1283</span> */<a name="line.1283"></a> |
| <span class="sourceLineNo">1284</span> public static Dataset cumulativeProduct(final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.1284"></a> |
| <span class="sourceLineNo">1285</span> axis = a.checkAxis(axis);<a name="line.1285"></a> |
| <span class="sourceLineNo">1286</span> int dtype = a.getDType();<a name="line.1286"></a> |
| <span class="sourceLineNo">1287</span> int[] oshape = a.getShape();<a name="line.1287"></a> |
| <span class="sourceLineNo">1288</span> int alen = oshape[axis];<a name="line.1288"></a> |
| <span class="sourceLineNo">1289</span> oshape[axis] = 1;<a name="line.1289"></a> |
| <span class="sourceLineNo">1290</span><a name="line.1290"></a> |
| <span class="sourceLineNo">1291</span> final boolean ignoreNaNs;<a name="line.1291"></a> |
| <span class="sourceLineNo">1292</span> final boolean ignoreInfs;<a name="line.1292"></a> |
| <span class="sourceLineNo">1293</span> if (a.hasFloatingPointElements()) {<a name="line.1293"></a> |
| <span class="sourceLineNo">1294</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.1294"></a> |
| <span class="sourceLineNo">1295</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.1295"></a> |
| <span class="sourceLineNo">1296</span> } else {<a name="line.1296"></a> |
| <span class="sourceLineNo">1297</span> ignoreNaNs = false;<a name="line.1297"></a> |
| <span class="sourceLineNo">1298</span> ignoreInfs = false;<a name="line.1298"></a> |
| <span class="sourceLineNo">1299</span> }<a name="line.1299"></a> |
| <span class="sourceLineNo">1300</span> Dataset result = DatasetFactory.zeros(a);<a name="line.1300"></a> |
| <span class="sourceLineNo">1301</span> PositionIterator pi = result.getPositionIterator(axis);<a name="line.1301"></a> |
| <span class="sourceLineNo">1302</span><a name="line.1302"></a> |
| <span class="sourceLineNo">1303</span> int[] pos = pi.getPos();<a name="line.1303"></a> |
| <span class="sourceLineNo">1304</span><a name="line.1304"></a> |
| <span class="sourceLineNo">1305</span> while (pi.hasNext()) {<a name="line.1305"></a> |
| <span class="sourceLineNo">1306</span><a name="line.1306"></a> |
| <span class="sourceLineNo">1307</span> if (a.isComplex()) {<a name="line.1307"></a> |
| <span class="sourceLineNo">1308</span> double rv = 1, iv = 0;<a name="line.1308"></a> |
| <span class="sourceLineNo">1309</span> switch (dtype) {<a name="line.1309"></a> |
| <span class="sourceLineNo">1310</span> case Dataset.COMPLEX64:<a name="line.1310"></a> |
| <span class="sourceLineNo">1311</span> ComplexFloatDataset af = (ComplexFloatDataset) a;<a name="line.1311"></a> |
| <span class="sourceLineNo">1312</span> ComplexFloatDataset rf = (ComplexFloatDataset) result;<a name="line.1312"></a> |
| <span class="sourceLineNo">1313</span> for (int j = 0; j < alen; j++) {<a name="line.1313"></a> |
| <span class="sourceLineNo">1314</span> if (!Double.isNaN(rv) || !Double.isNaN(iv)) {<a name="line.1314"></a> |
| <span class="sourceLineNo">1315</span> pos[axis] = j;<a name="line.1315"></a> |
| <span class="sourceLineNo">1316</span> final float r1 = af.getReal(pos);<a name="line.1316"></a> |
| <span class="sourceLineNo">1317</span> final float i1 = af.getImag(pos);<a name="line.1317"></a> |
| <span class="sourceLineNo">1318</span> if (ignoreNaNs && (Float.isNaN(r1) || Float.isNaN(i1))) {<a name="line.1318"></a> |
| <span class="sourceLineNo">1319</span> continue;<a name="line.1319"></a> |
| <span class="sourceLineNo">1320</span> }<a name="line.1320"></a> |
| <span class="sourceLineNo">1321</span> if (ignoreInfs && (Float.isInfinite(r1) || Float.isInfinite(i1))) {<a name="line.1321"></a> |
| <span class="sourceLineNo">1322</span> continue;<a name="line.1322"></a> |
| <span class="sourceLineNo">1323</span> }<a name="line.1323"></a> |
| <span class="sourceLineNo">1324</span> final double tv = r1*rv - i1*iv;<a name="line.1324"></a> |
| <span class="sourceLineNo">1325</span> iv = r1*iv + i1*rv;<a name="line.1325"></a> |
| <span class="sourceLineNo">1326</span> rv = tv;<a name="line.1326"></a> |
| <span class="sourceLineNo">1327</span> }<a name="line.1327"></a> |
| <span class="sourceLineNo">1328</span> rf.set((float) rv, (float) iv, pos);<a name="line.1328"></a> |
| <span class="sourceLineNo">1329</span> }<a name="line.1329"></a> |
| <span class="sourceLineNo">1330</span> break;<a name="line.1330"></a> |
| <span class="sourceLineNo">1331</span> case Dataset.COMPLEX128:<a name="line.1331"></a> |
| <span class="sourceLineNo">1332</span> ComplexDoubleDataset ad = (ComplexDoubleDataset) a;<a name="line.1332"></a> |
| <span class="sourceLineNo">1333</span> ComplexDoubleDataset rd = (ComplexDoubleDataset) result;<a name="line.1333"></a> |
| <span class="sourceLineNo">1334</span> for (int j = 0; j < alen; j++) {<a name="line.1334"></a> |
| <span class="sourceLineNo">1335</span> if (!Double.isNaN(rv) || !Double.isNaN(iv)) {<a name="line.1335"></a> |
| <span class="sourceLineNo">1336</span> pos[axis] = j;<a name="line.1336"></a> |
| <span class="sourceLineNo">1337</span> final double r1 = ad.getReal(pos);<a name="line.1337"></a> |
| <span class="sourceLineNo">1338</span> final double i1 = ad.getImag(pos);<a name="line.1338"></a> |
| <span class="sourceLineNo">1339</span> if (ignoreNaNs && (Double.isNaN(r1) || Double.isNaN(i1))) {<a name="line.1339"></a> |
| <span class="sourceLineNo">1340</span> continue;<a name="line.1340"></a> |
| <span class="sourceLineNo">1341</span> }<a name="line.1341"></a> |
| <span class="sourceLineNo">1342</span> if (ignoreInfs && (Double.isInfinite(r1) || Double.isInfinite(i1))) {<a name="line.1342"></a> |
| <span class="sourceLineNo">1343</span> continue;<a name="line.1343"></a> |
| <span class="sourceLineNo">1344</span> }<a name="line.1344"></a> |
| <span class="sourceLineNo">1345</span> final double tv = r1*rv - i1*iv;<a name="line.1345"></a> |
| <span class="sourceLineNo">1346</span> iv = r1*iv + i1*rv;<a name="line.1346"></a> |
| <span class="sourceLineNo">1347</span> rv = tv;<a name="line.1347"></a> |
| <span class="sourceLineNo">1348</span> }<a name="line.1348"></a> |
| <span class="sourceLineNo">1349</span> rd.set(rv, iv, pos);<a name="line.1349"></a> |
| <span class="sourceLineNo">1350</span> }<a name="line.1350"></a> |
| <span class="sourceLineNo">1351</span> break;<a name="line.1351"></a> |
| <span class="sourceLineNo">1352</span> }<a name="line.1352"></a> |
| <span class="sourceLineNo">1353</span> } else {<a name="line.1353"></a> |
| <span class="sourceLineNo">1354</span> final int is;<a name="line.1354"></a> |
| <span class="sourceLineNo">1355</span> final long[] lresults;<a name="line.1355"></a> |
| <span class="sourceLineNo">1356</span> final double[] dresults;<a name="line.1356"></a> |
| <span class="sourceLineNo">1357</span><a name="line.1357"></a> |
| <span class="sourceLineNo">1358</span> switch (dtype) {<a name="line.1358"></a> |
| <span class="sourceLineNo">1359</span> case Dataset.BOOL:<a name="line.1359"></a> |
| <span class="sourceLineNo">1360</span> case Dataset.INT8: case Dataset.INT16:<a name="line.1360"></a> |
| <span class="sourceLineNo">1361</span> case Dataset.INT32: case Dataset.INT64:<a name="line.1361"></a> |
| <span class="sourceLineNo">1362</span> long lresult = 1;<a name="line.1362"></a> |
| <span class="sourceLineNo">1363</span> for (int j = 0; j < alen; j++) {<a name="line.1363"></a> |
| <span class="sourceLineNo">1364</span> pos[axis] = j;<a name="line.1364"></a> |
| <span class="sourceLineNo">1365</span> lresult *= a.getInt(pos);<a name="line.1365"></a> |
| <span class="sourceLineNo">1366</span> result.set(lresult, pos);<a name="line.1366"></a> |
| <span class="sourceLineNo">1367</span> }<a name="line.1367"></a> |
| <span class="sourceLineNo">1368</span> break;<a name="line.1368"></a> |
| <span class="sourceLineNo">1369</span> case Dataset.ARRAYINT8:<a name="line.1369"></a> |
| <span class="sourceLineNo">1370</span> is = a.getElementsPerItem();<a name="line.1370"></a> |
| <span class="sourceLineNo">1371</span> lresults = new long[is];<a name="line.1371"></a> |
| <span class="sourceLineNo">1372</span> for (int k = 0; k < is; k++) {<a name="line.1372"></a> |
| <span class="sourceLineNo">1373</span> lresults[k] = 1;<a name="line.1373"></a> |
| <span class="sourceLineNo">1374</span> }<a name="line.1374"></a> |
| <span class="sourceLineNo">1375</span> for (int j = 0; j < alen; j++) {<a name="line.1375"></a> |
| <span class="sourceLineNo">1376</span> pos[axis] = j;<a name="line.1376"></a> |
| <span class="sourceLineNo">1377</span> final byte[] va = (byte[]) a.getObject(pos);<a name="line.1377"></a> |
| <span class="sourceLineNo">1378</span> for (int k = 0; k < is; k++) {<a name="line.1378"></a> |
| <span class="sourceLineNo">1379</span> lresults[k] *= va[k];<a name="line.1379"></a> |
| <span class="sourceLineNo">1380</span> }<a name="line.1380"></a> |
| <span class="sourceLineNo">1381</span> result.set(lresults, pos);<a name="line.1381"></a> |
| <span class="sourceLineNo">1382</span> }<a name="line.1382"></a> |
| <span class="sourceLineNo">1383</span> break;<a name="line.1383"></a> |
| <span class="sourceLineNo">1384</span> case Dataset.ARRAYINT16:<a name="line.1384"></a> |
| <span class="sourceLineNo">1385</span> is = a.getElementsPerItem();<a name="line.1385"></a> |
| <span class="sourceLineNo">1386</span> lresults = new long[is];<a name="line.1386"></a> |
| <span class="sourceLineNo">1387</span> for (int k = 0; k < is; k++) {<a name="line.1387"></a> |
| <span class="sourceLineNo">1388</span> lresults[k] = 1;<a name="line.1388"></a> |
| <span class="sourceLineNo">1389</span> }<a name="line.1389"></a> |
| <span class="sourceLineNo">1390</span> for (int j = 0; j < alen; j++) {<a name="line.1390"></a> |
| <span class="sourceLineNo">1391</span> pos[axis] = j;<a name="line.1391"></a> |
| <span class="sourceLineNo">1392</span> final short[] va = (short[]) a.getObject(pos);<a name="line.1392"></a> |
| <span class="sourceLineNo">1393</span> for (int k = 0; k < is; k++) {<a name="line.1393"></a> |
| <span class="sourceLineNo">1394</span> lresults[k] *= va[k];<a name="line.1394"></a> |
| <span class="sourceLineNo">1395</span> }<a name="line.1395"></a> |
| <span class="sourceLineNo">1396</span> result.set(lresults, pos);<a name="line.1396"></a> |
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| <span class="sourceLineNo">1398</span> break;<a name="line.1398"></a> |
| <span class="sourceLineNo">1399</span> case Dataset.ARRAYINT32:<a name="line.1399"></a> |
| <span class="sourceLineNo">1400</span> is = a.getElementsPerItem();<a name="line.1400"></a> |
| <span class="sourceLineNo">1401</span> lresults = new long[is];<a name="line.1401"></a> |
| <span class="sourceLineNo">1402</span> for (int k = 0; k < is; k++) {<a name="line.1402"></a> |
| <span class="sourceLineNo">1403</span> lresults[k] = 1;<a name="line.1403"></a> |
| <span class="sourceLineNo">1404</span> }<a name="line.1404"></a> |
| <span class="sourceLineNo">1405</span> for (int j = 0; j < alen; j++) {<a name="line.1405"></a> |
| <span class="sourceLineNo">1406</span> pos[axis] = j;<a name="line.1406"></a> |
| <span class="sourceLineNo">1407</span> final int[] va = (int[]) a.getObject(pos);<a name="line.1407"></a> |
| <span class="sourceLineNo">1408</span> for (int k = 0; k < is; k++) {<a name="line.1408"></a> |
| <span class="sourceLineNo">1409</span> lresults[k] *= va[k];<a name="line.1409"></a> |
| <span class="sourceLineNo">1410</span> }<a name="line.1410"></a> |
| <span class="sourceLineNo">1411</span> result.set(lresults, pos);<a name="line.1411"></a> |
| <span class="sourceLineNo">1412</span> }<a name="line.1412"></a> |
| <span class="sourceLineNo">1413</span> break;<a name="line.1413"></a> |
| <span class="sourceLineNo">1414</span> case Dataset.ARRAYINT64:<a name="line.1414"></a> |
| <span class="sourceLineNo">1415</span> is = a.getElementsPerItem();<a name="line.1415"></a> |
| <span class="sourceLineNo">1416</span> lresults = new long[is];<a name="line.1416"></a> |
| <span class="sourceLineNo">1417</span> for (int k = 0; k < is; k++) {<a name="line.1417"></a> |
| <span class="sourceLineNo">1418</span> lresults[k] = 1;<a name="line.1418"></a> |
| <span class="sourceLineNo">1419</span> }<a name="line.1419"></a> |
| <span class="sourceLineNo">1420</span> for (int j = 0; j < alen; j++) {<a name="line.1420"></a> |
| <span class="sourceLineNo">1421</span> pos[axis] = j;<a name="line.1421"></a> |
| <span class="sourceLineNo">1422</span> final long[] va = (long[]) a.getObject(pos);<a name="line.1422"></a> |
| <span class="sourceLineNo">1423</span> for (int k = 0; k < is; k++) {<a name="line.1423"></a> |
| <span class="sourceLineNo">1424</span> lresults[k] *= va[k];<a name="line.1424"></a> |
| <span class="sourceLineNo">1425</span> }<a name="line.1425"></a> |
| <span class="sourceLineNo">1426</span> result.set(lresults, pos);<a name="line.1426"></a> |
| <span class="sourceLineNo">1427</span> }<a name="line.1427"></a> |
| <span class="sourceLineNo">1428</span> break;<a name="line.1428"></a> |
| <span class="sourceLineNo">1429</span> case Dataset.FLOAT32: case Dataset.FLOAT64:<a name="line.1429"></a> |
| <span class="sourceLineNo">1430</span> double dresult = 1.;<a name="line.1430"></a> |
| <span class="sourceLineNo">1431</span> for (int j = 0; j < alen; j++) {<a name="line.1431"></a> |
| <span class="sourceLineNo">1432</span> if (!Double.isNaN(dresult)) {<a name="line.1432"></a> |
| <span class="sourceLineNo">1433</span> pos[axis] = j;<a name="line.1433"></a> |
| <span class="sourceLineNo">1434</span> final double x = a.getDouble(pos);<a name="line.1434"></a> |
| <span class="sourceLineNo">1435</span> if (ignoreNaNs && Double.isNaN(x)) {<a name="line.1435"></a> |
| <span class="sourceLineNo">1436</span> continue;<a name="line.1436"></a> |
| <span class="sourceLineNo">1437</span> }<a name="line.1437"></a> |
| <span class="sourceLineNo">1438</span> if (ignoreInfs && Double.isInfinite(x)) {<a name="line.1438"></a> |
| <span class="sourceLineNo">1439</span> continue;<a name="line.1439"></a> |
| <span class="sourceLineNo">1440</span> }<a name="line.1440"></a> |
| <span class="sourceLineNo">1441</span> dresult *= x;<a name="line.1441"></a> |
| <span class="sourceLineNo">1442</span> }<a name="line.1442"></a> |
| <span class="sourceLineNo">1443</span> result.set(dresult, pos);<a name="line.1443"></a> |
| <span class="sourceLineNo">1444</span> }<a name="line.1444"></a> |
| <span class="sourceLineNo">1445</span> break;<a name="line.1445"></a> |
| <span class="sourceLineNo">1446</span> case Dataset.ARRAYFLOAT32: case Dataset.ARRAYFLOAT64:<a name="line.1446"></a> |
| <span class="sourceLineNo">1447</span> is = a.getElementsPerItem();<a name="line.1447"></a> |
| <span class="sourceLineNo">1448</span> CompoundDataset da = (CompoundDataset) a;<a name="line.1448"></a> |
| <span class="sourceLineNo">1449</span> double[] dvalues = new double[is];<a name="line.1449"></a> |
| <span class="sourceLineNo">1450</span> dresults = new double[is];<a name="line.1450"></a> |
| <span class="sourceLineNo">1451</span> for (int k = 0; k < is; k++) {<a name="line.1451"></a> |
| <span class="sourceLineNo">1452</span> dresults[k] = 1.;<a name="line.1452"></a> |
| <span class="sourceLineNo">1453</span> }<a name="line.1453"></a> |
| <span class="sourceLineNo">1454</span> for (int j = 0; j < alen; j++) {<a name="line.1454"></a> |
| <span class="sourceLineNo">1455</span> pos[axis] = j;<a name="line.1455"></a> |
| <span class="sourceLineNo">1456</span> da.getDoubleArray(dvalues, pos);<a name="line.1456"></a> |
| <span class="sourceLineNo">1457</span> boolean okay = true;<a name="line.1457"></a> |
| <span class="sourceLineNo">1458</span> for (int k = 0; k < is; k++) {<a name="line.1458"></a> |
| <span class="sourceLineNo">1459</span> final double val = dvalues[k];<a name="line.1459"></a> |
| <span class="sourceLineNo">1460</span> if (ignoreNaNs && Double.isNaN(val)) {<a name="line.1460"></a> |
| <span class="sourceLineNo">1461</span> okay = false;<a name="line.1461"></a> |
| <span class="sourceLineNo">1462</span> break;<a name="line.1462"></a> |
| <span class="sourceLineNo">1463</span> }<a name="line.1463"></a> |
| <span class="sourceLineNo">1464</span> if (ignoreInfs && Double.isInfinite(val)) {<a name="line.1464"></a> |
| <span class="sourceLineNo">1465</span> okay = false;<a name="line.1465"></a> |
| <span class="sourceLineNo">1466</span> break;<a name="line.1466"></a> |
| <span class="sourceLineNo">1467</span> }<a name="line.1467"></a> |
| <span class="sourceLineNo">1468</span> }<a name="line.1468"></a> |
| <span class="sourceLineNo">1469</span> if (okay) {<a name="line.1469"></a> |
| <span class="sourceLineNo">1470</span> for (int k = 0; k < is; k++) {<a name="line.1470"></a> |
| <span class="sourceLineNo">1471</span> dresults[k] *= dvalues[k];<a name="line.1471"></a> |
| <span class="sourceLineNo">1472</span> }<a name="line.1472"></a> |
| <span class="sourceLineNo">1473</span> }<a name="line.1473"></a> |
| <span class="sourceLineNo">1474</span> result.set(dresults, pos);<a name="line.1474"></a> |
| <span class="sourceLineNo">1475</span> }<a name="line.1475"></a> |
| <span class="sourceLineNo">1476</span> break;<a name="line.1476"></a> |
| <span class="sourceLineNo">1477</span> }<a name="line.1477"></a> |
| <span class="sourceLineNo">1478</span> }<a name="line.1478"></a> |
| <span class="sourceLineNo">1479</span> }<a name="line.1479"></a> |
| <span class="sourceLineNo">1480</span><a name="line.1480"></a> |
| <span class="sourceLineNo">1481</span> return result;<a name="line.1481"></a> |
| <span class="sourceLineNo">1482</span> }<a name="line.1482"></a> |
| <span class="sourceLineNo">1483</span><a name="line.1483"></a> |
| <span class="sourceLineNo">1484</span> /**<a name="line.1484"></a> |
| <span class="sourceLineNo">1485</span> * @param a dataset<a name="line.1485"></a> |
| <span class="sourceLineNo">1486</span> * @param ignoreInvalids see {@link IDataset#max(boolean...)}<a name="line.1486"></a> |
| <span class="sourceLineNo">1487</span> * @return cumulative sum of items in flattened dataset<a name="line.1487"></a> |
| <span class="sourceLineNo">1488</span> * @since 2.0<a name="line.1488"></a> |
| <span class="sourceLineNo">1489</span> */<a name="line.1489"></a> |
| <span class="sourceLineNo">1490</span> public static Dataset cumulativeSum(final Dataset a, final boolean... ignoreInvalids) {<a name="line.1490"></a> |
| <span class="sourceLineNo">1491</span> return cumulativeSum(a.flatten(), 0, ignoreInvalids);<a name="line.1491"></a> |
| <span class="sourceLineNo">1492</span> }<a name="line.1492"></a> |
| <span class="sourceLineNo">1493</span><a name="line.1493"></a> |
| <span class="sourceLineNo">1494</span> /**<a name="line.1494"></a> |
| <span class="sourceLineNo">1495</span> * @param a dataset<a name="line.1495"></a> |
| <span class="sourceLineNo">1496</span> * @param axis<a name="line.1496"></a> |
| <span class="sourceLineNo">1497</span> * @param ignoreInvalids see {@link Dataset#max(int, boolean...)}<a name="line.1497"></a> |
| <span class="sourceLineNo">1498</span> * @return cumulative sum of items along axis in dataset<a name="line.1498"></a> |
| <span class="sourceLineNo">1499</span> * @since 2.0<a name="line.1499"></a> |
| <span class="sourceLineNo">1500</span> */<a name="line.1500"></a> |
| <span class="sourceLineNo">1501</span> public static Dataset cumulativeSum(final Dataset a, int axis, final boolean... ignoreInvalids) {<a name="line.1501"></a> |
| <span class="sourceLineNo">1502</span> axis = a.checkAxis(axis);<a name="line.1502"></a> |
| <span class="sourceLineNo">1503</span> int dtype = a.getDType();<a name="line.1503"></a> |
| <span class="sourceLineNo">1504</span> int[] oshape = a.getShape();<a name="line.1504"></a> |
| <span class="sourceLineNo">1505</span> int alen = oshape[axis];<a name="line.1505"></a> |
| <span class="sourceLineNo">1506</span> oshape[axis] = 1;<a name="line.1506"></a> |
| <span class="sourceLineNo">1507</span><a name="line.1507"></a> |
| <span class="sourceLineNo">1508</span> final boolean ignoreNaNs;<a name="line.1508"></a> |
| <span class="sourceLineNo">1509</span> final boolean ignoreInfs;<a name="line.1509"></a> |
| <span class="sourceLineNo">1510</span> if (a.hasFloatingPointElements()) {<a name="line.1510"></a> |
| <span class="sourceLineNo">1511</span> ignoreNaNs = ignoreInvalids != null && ignoreInvalids.length > 0 ? ignoreInvalids[0] : false;<a name="line.1511"></a> |
| <span class="sourceLineNo">1512</span> ignoreInfs = ignoreInvalids != null && ignoreInvalids.length > 1 ? ignoreInvalids[1] : ignoreNaNs;<a name="line.1512"></a> |
| <span class="sourceLineNo">1513</span> } else {<a name="line.1513"></a> |
| <span class="sourceLineNo">1514</span> ignoreNaNs = false;<a name="line.1514"></a> |
| <span class="sourceLineNo">1515</span> ignoreInfs = false;<a name="line.1515"></a> |
| <span class="sourceLineNo">1516</span> }<a name="line.1516"></a> |
| <span class="sourceLineNo">1517</span> Dataset result = DatasetFactory.zeros(a);<a name="line.1517"></a> |
| <span class="sourceLineNo">1518</span> PositionIterator pi = result.getPositionIterator(axis);<a name="line.1518"></a> |
| <span class="sourceLineNo">1519</span><a name="line.1519"></a> |
| <span class="sourceLineNo">1520</span> int[] pos = pi.getPos();<a name="line.1520"></a> |
| <span class="sourceLineNo">1521</span><a name="line.1521"></a> |
| <span class="sourceLineNo">1522</span> while (pi.hasNext()) {<a name="line.1522"></a> |
| <span class="sourceLineNo">1523</span><a name="line.1523"></a> |
| <span class="sourceLineNo">1524</span> if (a.isComplex()) {<a name="line.1524"></a> |
| <span class="sourceLineNo">1525</span> double rv = 0, iv = 0;<a name="line.1525"></a> |
| <span class="sourceLineNo">1526</span> switch (dtype) {<a name="line.1526"></a> |
| <span class="sourceLineNo">1527</span> case Dataset.COMPLEX64:<a name="line.1527"></a> |
| <span class="sourceLineNo">1528</span> ComplexFloatDataset af = (ComplexFloatDataset) a;<a name="line.1528"></a> |
| <span class="sourceLineNo">1529</span> ComplexFloatDataset rf = (ComplexFloatDataset) result;<a name="line.1529"></a> |
| <span class="sourceLineNo">1530</span> for (int j = 0; j < alen; j++) {<a name="line.1530"></a> |
| <span class="sourceLineNo">1531</span> if (!Double.isNaN(rv) || !Double.isNaN(iv)) {<a name="line.1531"></a> |
| <span class="sourceLineNo">1532</span> pos[axis] = j;<a name="line.1532"></a> |
| <span class="sourceLineNo">1533</span> final float r1 = af.getReal(pos);<a name="line.1533"></a> |
| <span class="sourceLineNo">1534</span> final float i1 = af.getImag(pos);<a name="line.1534"></a> |
| <span class="sourceLineNo">1535</span> if (ignoreNaNs && (Float.isNaN(r1) || Float.isNaN(i1))) {<a name="line.1535"></a> |
| <span class="sourceLineNo">1536</span> continue;<a name="line.1536"></a> |
| <span class="sourceLineNo">1537</span> }<a name="line.1537"></a> |
| <span class="sourceLineNo">1538</span> if (ignoreInfs && (Float.isInfinite(r1) || Float.isInfinite(i1))) {<a name="line.1538"></a> |
| <span class="sourceLineNo">1539</span> continue;<a name="line.1539"></a> |
| <span class="sourceLineNo">1540</span> }<a name="line.1540"></a> |
| <span class="sourceLineNo">1541</span> rv += r1;<a name="line.1541"></a> |
| <span class="sourceLineNo">1542</span> iv += i1;<a name="line.1542"></a> |
| <span class="sourceLineNo">1543</span> }<a name="line.1543"></a> |
| <span class="sourceLineNo">1544</span> rf.set((float) rv, (float) iv, pos);<a name="line.1544"></a> |
| <span class="sourceLineNo">1545</span> }<a name="line.1545"></a> |
| <span class="sourceLineNo">1546</span> break;<a name="line.1546"></a> |
| <span class="sourceLineNo">1547</span> case Dataset.COMPLEX128:<a name="line.1547"></a> |
| <span class="sourceLineNo">1548</span> ComplexDoubleDataset ad = (ComplexDoubleDataset) a;<a name="line.1548"></a> |
| <span class="sourceLineNo">1549</span> ComplexDoubleDataset rd = (ComplexDoubleDataset) result;<a name="line.1549"></a> |
| <span class="sourceLineNo">1550</span> for (int j = 0; j < alen; j++) {<a name="line.1550"></a> |
| <span class="sourceLineNo">1551</span> if (!Double.isNaN(rv) || !Double.isNaN(iv)) {<a name="line.1551"></a> |
| <span class="sourceLineNo">1552</span> pos[axis] = j;<a name="line.1552"></a> |
| <span class="sourceLineNo">1553</span> final double r1 = ad.getReal(pos);<a name="line.1553"></a> |
| <span class="sourceLineNo">1554</span> final double i1 = ad.getImag(pos);<a name="line.1554"></a> |
| <span class="sourceLineNo">1555</span> if (ignoreNaNs && (Double.isNaN(r1) || Double.isNaN(i1))) {<a name="line.1555"></a> |
| <span class="sourceLineNo">1556</span> continue;<a name="line.1556"></a> |
| <span class="sourceLineNo">1557</span> }<a name="line.1557"></a> |
| <span class="sourceLineNo">1558</span> if (ignoreInfs && (Double.isInfinite(r1) || Double.isInfinite(i1))) {<a name="line.1558"></a> |
| <span class="sourceLineNo">1559</span> continue;<a name="line.1559"></a> |
| <span class="sourceLineNo">1560</span> }<a name="line.1560"></a> |
| <span class="sourceLineNo">1561</span> rv += r1;<a name="line.1561"></a> |
| <span class="sourceLineNo">1562</span> iv += i1;<a name="line.1562"></a> |
| <span class="sourceLineNo">1563</span> }<a name="line.1563"></a> |
| <span class="sourceLineNo">1564</span> rd.set(rv, iv, pos);<a name="line.1564"></a> |
| <span class="sourceLineNo">1565</span> }<a name="line.1565"></a> |
| <span class="sourceLineNo">1566</span> break;<a name="line.1566"></a> |
| <span class="sourceLineNo">1567</span> }<a name="line.1567"></a> |
| <span class="sourceLineNo">1568</span> } else {<a name="line.1568"></a> |
| <span class="sourceLineNo">1569</span> final int is;<a name="line.1569"></a> |
| <span class="sourceLineNo">1570</span> final long[] lresults;<a name="line.1570"></a> |
| <span class="sourceLineNo">1571</span> final double[] dresults;<a name="line.1571"></a> |
| <span class="sourceLineNo">1572</span><a name="line.1572"></a> |
| <span class="sourceLineNo">1573</span> switch (dtype) {<a name="line.1573"></a> |
| <span class="sourceLineNo">1574</span> case Dataset.BOOL:<a name="line.1574"></a> |
| <span class="sourceLineNo">1575</span> case Dataset.INT8: case Dataset.INT16:<a name="line.1575"></a> |
| <span class="sourceLineNo">1576</span> case Dataset.INT32: case Dataset.INT64:<a name="line.1576"></a> |
| <span class="sourceLineNo">1577</span> long lresult = 0;<a name="line.1577"></a> |
| <span class="sourceLineNo">1578</span> for (int j = 0; j < alen; j++) {<a name="line.1578"></a> |
| <span class="sourceLineNo">1579</span> pos[axis] = j;<a name="line.1579"></a> |
| <span class="sourceLineNo">1580</span> lresult += a.getInt(pos);<a name="line.1580"></a> |
| <span class="sourceLineNo">1581</span> result.set(lresult, pos);<a name="line.1581"></a> |
| <span class="sourceLineNo">1582</span> }<a name="line.1582"></a> |
| <span class="sourceLineNo">1583</span> break;<a name="line.1583"></a> |
| <span class="sourceLineNo">1584</span> case Dataset.ARRAYINT8:<a name="line.1584"></a> |
| <span class="sourceLineNo">1585</span> is = a.getElementsPerItem();<a name="line.1585"></a> |
| <span class="sourceLineNo">1586</span> lresults = new long[is];<a name="line.1586"></a> |
| <span class="sourceLineNo">1587</span> for (int j = 0; j < alen; j++) {<a name="line.1587"></a> |
| <span class="sourceLineNo">1588</span> pos[axis] = j;<a name="line.1588"></a> |
| <span class="sourceLineNo">1589</span> final byte[] va = (byte[]) a.getObject(pos);<a name="line.1589"></a> |
| <span class="sourceLineNo">1590</span> for (int k = 0; k < is; k++) {<a name="line.1590"></a> |
| <span class="sourceLineNo">1591</span> lresults[k] += va[k];<a name="line.1591"></a> |
| <span class="sourceLineNo">1592</span> }<a name="line.1592"></a> |
| <span class="sourceLineNo">1593</span> result.set(lresults, pos);<a name="line.1593"></a> |
| <span class="sourceLineNo">1594</span> }<a name="line.1594"></a> |
| <span class="sourceLineNo">1595</span> break;<a name="line.1595"></a> |
| <span class="sourceLineNo">1596</span> case Dataset.ARRAYINT16:<a name="line.1596"></a> |
| <span class="sourceLineNo">1597</span> is = a.getElementsPerItem();<a name="line.1597"></a> |
| <span class="sourceLineNo">1598</span> lresults = new long[is];<a name="line.1598"></a> |
| <span class="sourceLineNo">1599</span> for (int j = 0; j < alen; j++) {<a name="line.1599"></a> |
| <span class="sourceLineNo">1600</span> pos[axis] = j;<a name="line.1600"></a> |
| <span class="sourceLineNo">1601</span> final short[] va = (short[]) a.getObject(pos);<a name="line.1601"></a> |
| <span class="sourceLineNo">1602</span> for (int k = 0; k < is; k++) {<a name="line.1602"></a> |
| <span class="sourceLineNo">1603</span> lresults[k] += va[k];<a name="line.1603"></a> |
| <span class="sourceLineNo">1604</span> }<a name="line.1604"></a> |
| <span class="sourceLineNo">1605</span> result.set(lresults, pos);<a name="line.1605"></a> |
| <span class="sourceLineNo">1606</span> }<a name="line.1606"></a> |
| <span class="sourceLineNo">1607</span> break;<a name="line.1607"></a> |
| <span class="sourceLineNo">1608</span> case Dataset.ARRAYINT32:<a name="line.1608"></a> |
| <span class="sourceLineNo">1609</span> is = a.getElementsPerItem();<a name="line.1609"></a> |
| <span class="sourceLineNo">1610</span> lresults = new long[is];<a name="line.1610"></a> |
| <span class="sourceLineNo">1611</span> for (int j = 0; j < alen; j++) {<a name="line.1611"></a> |
| <span class="sourceLineNo">1612</span> pos[axis] = j;<a name="line.1612"></a> |
| <span class="sourceLineNo">1613</span> final int[] va = (int[]) a.getObject(pos);<a name="line.1613"></a> |
| <span class="sourceLineNo">1614</span> for (int k = 0; k < is; k++) {<a name="line.1614"></a> |
| <span class="sourceLineNo">1615</span> lresults[k] += va[k];<a name="line.1615"></a> |
| <span class="sourceLineNo">1616</span> }<a name="line.1616"></a> |
| <span class="sourceLineNo">1617</span> result.set(lresults, pos);<a name="line.1617"></a> |
| <span class="sourceLineNo">1618</span> }<a name="line.1618"></a> |
| <span class="sourceLineNo">1619</span> break;<a name="line.1619"></a> |
| <span class="sourceLineNo">1620</span> case Dataset.ARRAYINT64:<a name="line.1620"></a> |
| <span class="sourceLineNo">1621</span> is = a.getElementsPerItem();<a name="line.1621"></a> |
| <span class="sourceLineNo">1622</span> lresults = new long[is];<a name="line.1622"></a> |
| <span class="sourceLineNo">1623</span> for (int j = 0; j < alen; j++) {<a name="line.1623"></a> |
| <span class="sourceLineNo">1624</span> pos[axis] = j;<a name="line.1624"></a> |
| <span class="sourceLineNo">1625</span> final long[] va = (long[]) a.getObject(pos);<a name="line.1625"></a> |
| <span class="sourceLineNo">1626</span> for (int k = 0; k < is; k++) {<a name="line.1626"></a> |
| <span class="sourceLineNo">1627</span> lresults[k] += va[k];<a name="line.1627"></a> |
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| <span class="sourceLineNo">1629</span> result.set(lresults, pos);<a name="line.1629"></a> |
| <span class="sourceLineNo">1630</span> }<a name="line.1630"></a> |
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| <span class="sourceLineNo">1632</span> case Dataset.FLOAT32: case Dataset.FLOAT64:<a name="line.1632"></a> |
| <span class="sourceLineNo">1633</span> double dresult = 0.;<a name="line.1633"></a> |
| <span class="sourceLineNo">1634</span> for (int j = 0; j < alen; j++) {<a name="line.1634"></a> |
| <span class="sourceLineNo">1635</span> if (!Double.isNaN(dresult)) {<a name="line.1635"></a> |
| <span class="sourceLineNo">1636</span> pos[axis] = j;<a name="line.1636"></a> |
| <span class="sourceLineNo">1637</span> final double x = a.getDouble(pos);<a name="line.1637"></a> |
| <span class="sourceLineNo">1638</span> if (ignoreNaNs && Double.isNaN(x)) {<a name="line.1638"></a> |
| <span class="sourceLineNo">1639</span> continue;<a name="line.1639"></a> |
| <span class="sourceLineNo">1640</span> }<a name="line.1640"></a> |
| <span class="sourceLineNo">1641</span> if (ignoreInfs && Double.isInfinite(x)) {<a name="line.1641"></a> |
| <span class="sourceLineNo">1642</span> continue;<a name="line.1642"></a> |
| <span class="sourceLineNo">1643</span> }<a name="line.1643"></a> |
| <span class="sourceLineNo">1644</span> dresult += x;<a name="line.1644"></a> |
| <span class="sourceLineNo">1645</span> }<a name="line.1645"></a> |
| <span class="sourceLineNo">1646</span> result.set(dresult, pos);<a name="line.1646"></a> |
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| <span class="sourceLineNo">1649</span> case Dataset.ARRAYFLOAT32: case Dataset.ARRAYFLOAT64:<a name="line.1649"></a> |
| <span class="sourceLineNo">1650</span> is = a.getElementsPerItem();<a name="line.1650"></a> |
| <span class="sourceLineNo">1651</span> CompoundDataset da = (CompoundDataset) a;<a name="line.1651"></a> |
| <span class="sourceLineNo">1652</span> double[] dvalues = new double[is];<a name="line.1652"></a> |
| <span class="sourceLineNo">1653</span> dresults = new double[is];<a name="line.1653"></a> |
| <span class="sourceLineNo">1654</span> for (int j = 0; j < alen; j++) {<a name="line.1654"></a> |
| <span class="sourceLineNo">1655</span> pos[axis] = j;<a name="line.1655"></a> |
| <span class="sourceLineNo">1656</span> da.getDoubleArray(dvalues, pos);<a name="line.1656"></a> |
| <span class="sourceLineNo">1657</span> boolean okay = true;<a name="line.1657"></a> |
| <span class="sourceLineNo">1658</span> for (int k = 0; k < is; k++) {<a name="line.1658"></a> |
| <span class="sourceLineNo">1659</span> final double val = dvalues[k];<a name="line.1659"></a> |
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| <span class="sourceLineNo">1661</span> okay = false;<a name="line.1661"></a> |
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| <span class="sourceLineNo">1665</span> okay = false;<a name="line.1665"></a> |
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| <span class="sourceLineNo">1667</span> }<a name="line.1667"></a> |
| <span class="sourceLineNo">1668</span> }<a name="line.1668"></a> |
| <span class="sourceLineNo">1669</span> if (okay) {<a name="line.1669"></a> |
| <span class="sourceLineNo">1670</span> for (int k = 0; k < is; k++) {<a name="line.1670"></a> |
| <span class="sourceLineNo">1671</span> dresults[k] += dvalues[k];<a name="line.1671"></a> |
| <span class="sourceLineNo">1672</span> }<a name="line.1672"></a> |
| <span class="sourceLineNo">1673</span> }<a name="line.1673"></a> |
| <span class="sourceLineNo">1674</span> result.set(dresults, pos);<a name="line.1674"></a> |
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| <span class="sourceLineNo">1677</span> }<a name="line.1677"></a> |
| <span class="sourceLineNo">1678</span> }<a name="line.1678"></a> |
| <span class="sourceLineNo">1679</span> }<a name="line.1679"></a> |
| <span class="sourceLineNo">1680</span><a name="line.1680"></a> |
| <span class="sourceLineNo">1681</span> return result;<a name="line.1681"></a> |
| <span class="sourceLineNo">1682</span> }<a name="line.1682"></a> |
| <span class="sourceLineNo">1683</span><a name="line.1683"></a> |
| <span class="sourceLineNo">1684</span> /**<a name="line.1684"></a> |
| <span class="sourceLineNo">1685</span> * @param a<a name="line.1685"></a> |
| <span class="sourceLineNo">1686</span> * @return average deviation value of all items the dataset<a name="line.1686"></a> |
| <span class="sourceLineNo">1687</span> */<a name="line.1687"></a> |
| <span class="sourceLineNo">1688</span> public static Object averageDeviation(final Dataset a) {<a name="line.1688"></a> |
| <span class="sourceLineNo">1689</span> final IndexIterator it = a.getIterator();<a name="line.1689"></a> |
| <span class="sourceLineNo">1690</span> final int is = a.getElementsPerItem();<a name="line.1690"></a> |
| <span class="sourceLineNo">1691</span><a name="line.1691"></a> |
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| <span class="sourceLineNo">1694</span> double sum = 0.0;<a name="line.1694"></a> |
| <span class="sourceLineNo">1695</span><a name="line.1695"></a> |
| <span class="sourceLineNo">1696</span> while (it.hasNext()) {<a name="line.1696"></a> |
| <span class="sourceLineNo">1697</span> sum += Math.abs(a.getElementDoubleAbs(it.index) - mean);<a name="line.1697"></a> |
| <span class="sourceLineNo">1698</span> }<a name="line.1698"></a> |
| <span class="sourceLineNo">1699</span><a name="line.1699"></a> |
| <span class="sourceLineNo">1700</span> return sum / a.getSize();<a name="line.1700"></a> |
| <span class="sourceLineNo">1701</span> }<a name="line.1701"></a> |
| <span class="sourceLineNo">1702</span><a name="line.1702"></a> |
| <span class="sourceLineNo">1703</span> double[] means = (double[]) a.mean();<a name="line.1703"></a> |
| <span class="sourceLineNo">1704</span> double[] sums = new double[is];<a name="line.1704"></a> |
| <span class="sourceLineNo">1705</span><a name="line.1705"></a> |
| <span class="sourceLineNo">1706</span> while (it.hasNext()) {<a name="line.1706"></a> |
| <span class="sourceLineNo">1707</span> for (int j = 0; j < is; j++)<a name="line.1707"></a> |
| <span class="sourceLineNo">1708</span> sums[j] += Math.abs(a.getElementDoubleAbs(it.index + j) - means[j]);<a name="line.1708"></a> |
| <span class="sourceLineNo">1709</span> }<a name="line.1709"></a> |
| <span class="sourceLineNo">1710</span><a name="line.1710"></a> |
| <span class="sourceLineNo">1711</span> double n = a.getSize();<a name="line.1711"></a> |
| <span class="sourceLineNo">1712</span> for (int j = 0; j < is; j++)<a name="line.1712"></a> |
| <span class="sourceLineNo">1713</span> sums[j] /= n;<a name="line.1713"></a> |
| <span class="sourceLineNo">1714</span><a name="line.1714"></a> |
| <span class="sourceLineNo">1715</span> return sums;<a name="line.1715"></a> |
| <span class="sourceLineNo">1716</span> }<a name="line.1716"></a> |
| <span class="sourceLineNo">1717</span><a name="line.1717"></a> |
| <span class="sourceLineNo">1718</span> /**<a name="line.1718"></a> |
| <span class="sourceLineNo">1719</span> * The residual is the sum of squared differences<a name="line.1719"></a> |
| <span class="sourceLineNo">1720</span> * @param a<a name="line.1720"></a> |
| <span class="sourceLineNo">1721</span> * @param b<a name="line.1721"></a> |
| <span class="sourceLineNo">1722</span> * @return residual value<a name="line.1722"></a> |
| <span class="sourceLineNo">1723</span> */<a name="line.1723"></a> |
| <span class="sourceLineNo">1724</span> public static double residual(final Dataset a, final Dataset b) {<a name="line.1724"></a> |
| <span class="sourceLineNo">1725</span> return a.residual(b);<a name="line.1725"></a> |
| <span class="sourceLineNo">1726</span> }<a name="line.1726"></a> |
| <span class="sourceLineNo">1727</span><a name="line.1727"></a> |
| <span class="sourceLineNo">1728</span> /**<a name="line.1728"></a> |
| <span class="sourceLineNo">1729</span> * The residual is the sum of squared differences<a name="line.1729"></a> |
| <span class="sourceLineNo">1730</span> * @param a<a name="line.1730"></a> |
| <span class="sourceLineNo">1731</span> * @param b<a name="line.1731"></a> |
| <span class="sourceLineNo">1732</span> * @param w<a name="line.1732"></a> |
| <span class="sourceLineNo">1733</span> * @return residual value<a name="line.1733"></a> |
| <span class="sourceLineNo">1734</span> */<a name="line.1734"></a> |
| <span class="sourceLineNo">1735</span> public static double weightedResidual(final Dataset a, final Dataset b, final Dataset w) {<a name="line.1735"></a> |
| <span class="sourceLineNo">1736</span> return a.residual(b, w, false);<a name="line.1736"></a> |
| <span class="sourceLineNo">1737</span> }<a name="line.1737"></a> |
| <span class="sourceLineNo">1738</span><a name="line.1738"></a> |
| <span class="sourceLineNo">1739</span> /**<a name="line.1739"></a> |
| <span class="sourceLineNo">1740</span> * Calculate approximate outlier values. These are defined as the values in the dataset<a name="line.1740"></a> |
| <span class="sourceLineNo">1741</span> * that are approximately below and above the given thresholds - in terms of percentages<a name="line.1741"></a> |
| <span class="sourceLineNo">1742</span> * of dataset size.<a name="line.1742"></a> |
| <span class="sourceLineNo">1743</span> * <p><a name="line.1743"></a> |
| <span class="sourceLineNo">1744</span> * It approximates by limiting the number of items (given by length) used internally by<a name="line.1744"></a> |
| <span class="sourceLineNo">1745</span> * data structures - the larger this is, the more accurate will those outlier values become.<a name="line.1745"></a> |
| <span class="sourceLineNo">1746</span> * The actual thresholds used are returned in the array.<a name="line.1746"></a> |
| <span class="sourceLineNo">1747</span> * <p><a name="line.1747"></a> |
| <span class="sourceLineNo">1748</span> * Also, the low and high values will be made distinct if possible by adjusting the thresholds<a name="line.1748"></a> |
| <span class="sourceLineNo">1749</span> * @param a<a name="line.1749"></a> |
| <span class="sourceLineNo">1750</span> * @param lo percentage threshold for lower limit<a name="line.1750"></a> |
| <span class="sourceLineNo">1751</span> * @param hi percentage threshold for higher limit<a name="line.1751"></a> |
| <span class="sourceLineNo">1752</span> * @param length maximum number of items used internally, if negative, then unlimited<a name="line.1752"></a> |
| <span class="sourceLineNo">1753</span> * @return double array with low and high values, and low and high percentage thresholds<a name="line.1753"></a> |
| <span class="sourceLineNo">1754</span> */<a name="line.1754"></a> |
| <span class="sourceLineNo">1755</span> public static double[] outlierValues(final Dataset a, double lo, double hi, final int length) {<a name="line.1755"></a> |
| <span class="sourceLineNo">1756</span> return outlierValues(a, null, true, lo, hi, length);<a name="line.1756"></a> |
| <span class="sourceLineNo">1757</span> }<a name="line.1757"></a> |
| <span class="sourceLineNo">1758</span><a name="line.1758"></a> |
| <span class="sourceLineNo">1759</span> /**<a name="line.1759"></a> |
| <span class="sourceLineNo">1760</span> * Calculate approximate outlier values. These are defined as the values in the dataset<a name="line.1760"></a> |
| <span class="sourceLineNo">1761</span> * that are approximately below and above the given thresholds - in terms of percentages<a name="line.1761"></a> |
| <span class="sourceLineNo">1762</span> * of dataset size.<a name="line.1762"></a> |
| <span class="sourceLineNo">1763</span> * <p><a name="line.1763"></a> |
| <span class="sourceLineNo">1764</span> * It approximates by limiting the number of items (given by length) used internally by<a name="line.1764"></a> |
| <span class="sourceLineNo">1765</span> * data structures - the larger this is, the more accurate will those outlier values become.<a name="line.1765"></a> |
| <span class="sourceLineNo">1766</span> * The actual thresholds used are returned in the array.<a name="line.1766"></a> |
| <span class="sourceLineNo">1767</span> * <p><a name="line.1767"></a> |
| <span class="sourceLineNo">1768</span> * Also, the low and high values will be made distinct if possible by adjusting the thresholds<a name="line.1768"></a> |
| <span class="sourceLineNo">1769</span> * @param a<a name="line.1769"></a> |
| <span class="sourceLineNo">1770</span> * @param mask can be null<a name="line.1770"></a> |
| <span class="sourceLineNo">1771</span> * @param value value of mask to match to include for calculation<a name="line.1771"></a> |
| <span class="sourceLineNo">1772</span> * @param lo percentage threshold for lower limit<a name="line.1772"></a> |
| <span class="sourceLineNo">1773</span> * @param hi percentage threshold for higher limit<a name="line.1773"></a> |
| <span class="sourceLineNo">1774</span> * @param length maximum number of items used internally, if negative, then unlimited<a name="line.1774"></a> |
| <span class="sourceLineNo">1775</span> * @return double array with low and high values, and low and high percentage thresholds<a name="line.1775"></a> |
| <span class="sourceLineNo">1776</span> * @since 2.1<a name="line.1776"></a> |
| <span class="sourceLineNo">1777</span> */<a name="line.1777"></a> |
| <span class="sourceLineNo">1778</span> public static double[] outlierValues(final Dataset a, final Dataset mask, final boolean value, double lo, double hi, final int length) {<a name="line.1778"></a> |
| <span class="sourceLineNo">1779</span> if (lo <= 0 || hi <= 0 || lo >= hi || hi >= 100 || Double.isNaN(lo)|| Double.isNaN(hi)) {<a name="line.1779"></a> |
| <span class="sourceLineNo">1780</span> throw new IllegalArgumentException("Thresholds must be between (0,100) and in order");<a name="line.1780"></a> |
| <span class="sourceLineNo">1781</span> }<a name="line.1781"></a> |
| <span class="sourceLineNo">1782</span> final int size = a.getSize();<a name="line.1782"></a> |
| <span class="sourceLineNo">1783</span> int nl = Math.max((int) ((lo*size)/100), 1);<a name="line.1783"></a> |
| <span class="sourceLineNo">1784</span> if (length > 0 && nl > length)<a name="line.1784"></a> |
| <span class="sourceLineNo">1785</span> nl = length;<a name="line.1785"></a> |
| <span class="sourceLineNo">1786</span> int nh = Math.max((int) (((100-hi)*size)/100), 1);<a name="line.1786"></a> |
| <span class="sourceLineNo">1787</span> if (length > 0 && nh > length)<a name="line.1787"></a> |
| <span class="sourceLineNo">1788</span> nh = length;<a name="line.1788"></a> |
| <span class="sourceLineNo">1789</span><a name="line.1789"></a> |
| <span class="sourceLineNo">1790</span> IndexIterator it = mask == null ? a.getIterator() : a.getBooleanIterator(mask, value);<a name="line.1790"></a> |
| <span class="sourceLineNo">1791</span> double[] results = Math.max(nl, nh) > 640 ? outlierValuesMap(a, it, nl, nh) : outlierValuesList(a, it, nl, nh);<a name="line.1791"></a> |
| <span class="sourceLineNo">1792</span><a name="line.1792"></a> |
| <span class="sourceLineNo">1793</span> results[2] = results[2]*100./size;<a name="line.1793"></a> |
| <span class="sourceLineNo">1794</span> results[3] = 100. - results[3]*100./size;<a name="line.1794"></a> |
| <span class="sourceLineNo">1795</span> return results;<a name="line.1795"></a> |
| <span class="sourceLineNo">1796</span> }<a name="line.1796"></a> |
| <span class="sourceLineNo">1797</span><a name="line.1797"></a> |
| <span class="sourceLineNo">1798</span> static double[] outlierValuesMap(final Dataset a, final IndexIterator it, int nl, int nh) {<a name="line.1798"></a> |
| <span class="sourceLineNo">1799</span> final TreeMap<Double, Integer> lMap = new TreeMap<Double, Integer>();<a name="line.1799"></a> |
| <span class="sourceLineNo">1800</span> final TreeMap<Double, Integer> hMap = new TreeMap<Double, Integer>();<a name="line.1800"></a> |
| <span class="sourceLineNo">1801</span><a name="line.1801"></a> |
| <span class="sourceLineNo">1802</span> int ml = 0;<a name="line.1802"></a> |
| <span class="sourceLineNo">1803</span> int mh = 0;<a name="line.1803"></a> |
| <span class="sourceLineNo">1804</span> while (it.hasNext()) {<a name="line.1804"></a> |
| <span class="sourceLineNo">1805</span> Double x = a.getElementDoubleAbs(it.index);<a name="line.1805"></a> |
| <span class="sourceLineNo">1806</span> if (Double.isNaN(x)) {<a name="line.1806"></a> |
| <span class="sourceLineNo">1807</span> continue;<a name="line.1807"></a> |
| <span class="sourceLineNo">1808</span> }<a name="line.1808"></a> |
| <span class="sourceLineNo">1809</span> Integer i;<a name="line.1809"></a> |
| <span class="sourceLineNo">1810</span> if (ml == nl) {<a name="line.1810"></a> |
| <span class="sourceLineNo">1811</span> Double k = lMap.lastKey();<a name="line.1811"></a> |
| <span class="sourceLineNo">1812</span> if (x < k) {<a name="line.1812"></a> |
| <span class="sourceLineNo">1813</span> i = lMap.get(k) - 1;<a name="line.1813"></a> |
| <span class="sourceLineNo">1814</span> if (i == 0) {<a name="line.1814"></a> |
| <span class="sourceLineNo">1815</span> lMap.remove(k);<a name="line.1815"></a> |
| <span class="sourceLineNo">1816</span> } else {<a name="line.1816"></a> |
| <span class="sourceLineNo">1817</span> lMap.put(k, i);<a name="line.1817"></a> |
| <span class="sourceLineNo">1818</span> }<a name="line.1818"></a> |
| <span class="sourceLineNo">1819</span> i = lMap.get(x);<a name="line.1819"></a> |
| <span class="sourceLineNo">1820</span> if (i == null) {<a name="line.1820"></a> |
| <span class="sourceLineNo">1821</span> lMap.put(x, 1);<a name="line.1821"></a> |
| <span class="sourceLineNo">1822</span> } else {<a name="line.1822"></a> |
| <span class="sourceLineNo">1823</span> lMap.put(x, i + 1);<a name="line.1823"></a> |
| <span class="sourceLineNo">1824</span> }<a name="line.1824"></a> |
| <span class="sourceLineNo">1825</span> }<a name="line.1825"></a> |
| <span class="sourceLineNo">1826</span> } else {<a name="line.1826"></a> |
| <span class="sourceLineNo">1827</span> i = lMap.get(x);<a name="line.1827"></a> |
| <span class="sourceLineNo">1828</span> if (i == null) {<a name="line.1828"></a> |
| <span class="sourceLineNo">1829</span> lMap.put(x, 1);<a name="line.1829"></a> |
| <span class="sourceLineNo">1830</span> } else {<a name="line.1830"></a> |
| <span class="sourceLineNo">1831</span> lMap.put(x, i + 1);<a name="line.1831"></a> |
| <span class="sourceLineNo">1832</span> }<a name="line.1832"></a> |
| <span class="sourceLineNo">1833</span> ml++;<a name="line.1833"></a> |
| <span class="sourceLineNo">1834</span> }<a name="line.1834"></a> |
| <span class="sourceLineNo">1835</span><a name="line.1835"></a> |
| <span class="sourceLineNo">1836</span> if (mh == nh) {<a name="line.1836"></a> |
| <span class="sourceLineNo">1837</span> Double k = hMap.firstKey();<a name="line.1837"></a> |
| <span class="sourceLineNo">1838</span> if (x > k) {<a name="line.1838"></a> |
| <span class="sourceLineNo">1839</span> i = hMap.get(k) - 1;<a name="line.1839"></a> |
| <span class="sourceLineNo">1840</span> if (i == 0) {<a name="line.1840"></a> |
| <span class="sourceLineNo">1841</span> hMap.remove(k);<a name="line.1841"></a> |
| <span class="sourceLineNo">1842</span> } else {<a name="line.1842"></a> |
| <span class="sourceLineNo">1843</span> hMap.put(k, i);<a name="line.1843"></a> |
| <span class="sourceLineNo">1844</span> }<a name="line.1844"></a> |
| <span class="sourceLineNo">1845</span> i = hMap.get(x);<a name="line.1845"></a> |
| <span class="sourceLineNo">1846</span> if (i == null) {<a name="line.1846"></a> |
| <span class="sourceLineNo">1847</span> hMap.put(x, 1);<a name="line.1847"></a> |
| <span class="sourceLineNo">1848</span> } else {<a name="line.1848"></a> |
| <span class="sourceLineNo">1849</span> hMap.put(x, i+1);<a name="line.1849"></a> |
| <span class="sourceLineNo">1850</span> }<a name="line.1850"></a> |
| <span class="sourceLineNo">1851</span> }<a name="line.1851"></a> |
| <span class="sourceLineNo">1852</span> } else {<a name="line.1852"></a> |
| <span class="sourceLineNo">1853</span> i = hMap.get(x);<a name="line.1853"></a> |
| <span class="sourceLineNo">1854</span> if (i == null) {<a name="line.1854"></a> |
| <span class="sourceLineNo">1855</span> hMap.put(x, 1);<a name="line.1855"></a> |
| <span class="sourceLineNo">1856</span> } else {<a name="line.1856"></a> |
| <span class="sourceLineNo">1857</span> hMap.put(x, i+1);<a name="line.1857"></a> |
| <span class="sourceLineNo">1858</span> }<a name="line.1858"></a> |
| <span class="sourceLineNo">1859</span> mh++;<a name="line.1859"></a> |
| <span class="sourceLineNo">1860</span> }<a name="line.1860"></a> |
| <span class="sourceLineNo">1861</span> }<a name="line.1861"></a> |
| <span class="sourceLineNo">1862</span><a name="line.1862"></a> |
| <span class="sourceLineNo">1863</span> // Attempt to make values distinct<a name="line.1863"></a> |
| <span class="sourceLineNo">1864</span> double lx = lMap.lastKey();<a name="line.1864"></a> |
| <span class="sourceLineNo">1865</span> double hx = hMap.firstKey();<a name="line.1865"></a> |
| <span class="sourceLineNo">1866</span> if (lx >= hx) {<a name="line.1866"></a> |
| <span class="sourceLineNo">1867</span> Double h = hMap.higherKey(lx);<a name="line.1867"></a> |
| <span class="sourceLineNo">1868</span> if (h != null) {<a name="line.1868"></a> |
| <span class="sourceLineNo">1869</span> hx = h;<a name="line.1869"></a> |
| <span class="sourceLineNo">1870</span> mh--;<a name="line.1870"></a> |
| <span class="sourceLineNo">1871</span> } else {<a name="line.1871"></a> |
| <span class="sourceLineNo">1872</span> Double l = lMap.lowerKey(hx);<a name="line.1872"></a> |
| <span class="sourceLineNo">1873</span> if (l != null) {<a name="line.1873"></a> |
| <span class="sourceLineNo">1874</span> lx = l;<a name="line.1874"></a> |
| <span class="sourceLineNo">1875</span> ml--;<a name="line.1875"></a> |
| <span class="sourceLineNo">1876</span> }<a name="line.1876"></a> |
| <span class="sourceLineNo">1877</span> }<a name="line.1877"></a> |
| <span class="sourceLineNo">1878</span> <a name="line.1878"></a> |
| <span class="sourceLineNo">1879</span> }<a name="line.1879"></a> |
| <span class="sourceLineNo">1880</span> return new double[] {lMap.lastKey(), hMap.firstKey(), ml, mh};<a name="line.1880"></a> |
| <span class="sourceLineNo">1881</span> }<a name="line.1881"></a> |
| <span class="sourceLineNo">1882</span><a name="line.1882"></a> |
| <span class="sourceLineNo">1883</span> static double[] outlierValuesList(final Dataset a, final IndexIterator it, int nl, int nh) {<a name="line.1883"></a> |
| <span class="sourceLineNo">1884</span> final List<Double> lList = new ArrayList<Double>(nl);<a name="line.1884"></a> |
| <span class="sourceLineNo">1885</span> final List<Double> hList = new ArrayList<Double>(nh);<a name="line.1885"></a> |
| <span class="sourceLineNo">1886</span><a name="line.1886"></a> |
| <span class="sourceLineNo">1887</span> double lx = Double.POSITIVE_INFINITY;<a name="line.1887"></a> |
| <span class="sourceLineNo">1888</span> double hx = Double.NEGATIVE_INFINITY;<a name="line.1888"></a> |
| <span class="sourceLineNo">1889</span><a name="line.1889"></a> |
| <span class="sourceLineNo">1890</span> while (it.hasNext()) {<a name="line.1890"></a> |
| <span class="sourceLineNo">1891</span> double x = a.getElementDoubleAbs(it.index);<a name="line.1891"></a> |
| <span class="sourceLineNo">1892</span> if (Double.isNaN(x)) {<a name="line.1892"></a> |
| <span class="sourceLineNo">1893</span> continue;<a name="line.1893"></a> |
| <span class="sourceLineNo">1894</span> }<a name="line.1894"></a> |
| <span class="sourceLineNo">1895</span> if (x < lx) {<a name="line.1895"></a> |
| <span class="sourceLineNo">1896</span> if (lList.size() == nl) {<a name="line.1896"></a> |
| <span class="sourceLineNo">1897</span> lList.remove(lx);<a name="line.1897"></a> |
| <span class="sourceLineNo">1898</span> }<a name="line.1898"></a> |
| <span class="sourceLineNo">1899</span> lList.add(x);<a name="line.1899"></a> |
| <span class="sourceLineNo">1900</span> lx = Collections.max(lList);<a name="line.1900"></a> |
| <span class="sourceLineNo">1901</span> } else if (x == lx) {<a name="line.1901"></a> |
| <span class="sourceLineNo">1902</span> if (lList.size() < nl) {<a name="line.1902"></a> |
| <span class="sourceLineNo">1903</span> lList.add(x);<a name="line.1903"></a> |
| <span class="sourceLineNo">1904</span> }<a name="line.1904"></a> |
| <span class="sourceLineNo">1905</span> }<a name="line.1905"></a> |
| <span class="sourceLineNo">1906</span><a name="line.1906"></a> |
| <span class="sourceLineNo">1907</span> if (x > hx) {<a name="line.1907"></a> |
| <span class="sourceLineNo">1908</span> if (hList.size() == nh) {<a name="line.1908"></a> |
| <span class="sourceLineNo">1909</span> hList.remove(hx);<a name="line.1909"></a> |
| <span class="sourceLineNo">1910</span> }<a name="line.1910"></a> |
| <span class="sourceLineNo">1911</span> hList.add(x);<a name="line.1911"></a> |
| <span class="sourceLineNo">1912</span> hx = Collections.min(hList);<a name="line.1912"></a> |
| <span class="sourceLineNo">1913</span> } else if (x == hx) {<a name="line.1913"></a> |
| <span class="sourceLineNo">1914</span> if (hList.size() < nh) {<a name="line.1914"></a> |
| <span class="sourceLineNo">1915</span> hList.add(x);<a name="line.1915"></a> |
| <span class="sourceLineNo">1916</span> }<a name="line.1916"></a> |
| <span class="sourceLineNo">1917</span> }<a name="line.1917"></a> |
| <span class="sourceLineNo">1918</span> }<a name="line.1918"></a> |
| <span class="sourceLineNo">1919</span><a name="line.1919"></a> |
| <span class="sourceLineNo">1920</span> nl = lList.size();<a name="line.1920"></a> |
| <span class="sourceLineNo">1921</span> nh = hList.size();<a name="line.1921"></a> |
| <span class="sourceLineNo">1922</span><a name="line.1922"></a> |
| <span class="sourceLineNo">1923</span> // Attempt to make values distinct<a name="line.1923"></a> |
| <span class="sourceLineNo">1924</span> if (lx >= hx) {<a name="line.1924"></a> |
| <span class="sourceLineNo">1925</span> Collections.sort(hList);<a name="line.1925"></a> |
| <span class="sourceLineNo">1926</span> for (double h : hList) {<a name="line.1926"></a> |
| <span class="sourceLineNo">1927</span> if (h > hx) {<a name="line.1927"></a> |
| <span class="sourceLineNo">1928</span> hx = h;<a name="line.1928"></a> |
| <span class="sourceLineNo">1929</span> break;<a name="line.1929"></a> |
| <span class="sourceLineNo">1930</span> }<a name="line.1930"></a> |
| <span class="sourceLineNo">1931</span> nh--;<a name="line.1931"></a> |
| <span class="sourceLineNo">1932</span> }<a name="line.1932"></a> |
| <span class="sourceLineNo">1933</span> if (lx >= hx) {<a name="line.1933"></a> |
| <span class="sourceLineNo">1934</span> Collections.sort(lList);<a name="line.1934"></a> |
| <span class="sourceLineNo">1935</span> Collections.reverse(lList);<a name="line.1935"></a> |
| <span class="sourceLineNo">1936</span> for (double l : lList) {<a name="line.1936"></a> |
| <span class="sourceLineNo">1937</span> if (l < lx) {<a name="line.1937"></a> |
| <span class="sourceLineNo">1938</span> lx = l;<a name="line.1938"></a> |
| <span class="sourceLineNo">1939</span> break;<a name="line.1939"></a> |
| <span class="sourceLineNo">1940</span> }<a name="line.1940"></a> |
| <span class="sourceLineNo">1941</span> nl--;<a name="line.1941"></a> |
| <span class="sourceLineNo">1942</span> }<a name="line.1942"></a> |
| <span class="sourceLineNo">1943</span> }<a name="line.1943"></a> |
| <span class="sourceLineNo">1944</span> }<a name="line.1944"></a> |
| <span class="sourceLineNo">1945</span> return new double[] {lx, hx, nl, nh};<a name="line.1945"></a> |
| <span class="sourceLineNo">1946</span> }<a name="line.1946"></a> |
| <span class="sourceLineNo">1947</span><a name="line.1947"></a> |
| <span class="sourceLineNo">1948</span> /**<a name="line.1948"></a> |
| <span class="sourceLineNo">1949</span> * See {@link #covariance(Dataset a, Dataset b, boolean rowvar, boolean bias, Integer ddof)} with b = null, rowvar = true, bias = false and ddof = null.<a name="line.1949"></a> |
| <span class="sourceLineNo">1950</span> * @param a<a name="line.1950"></a> |
| <span class="sourceLineNo">1951</span> * @return covariance array of a<a name="line.1951"></a> |
| <span class="sourceLineNo">1952</span> */<a name="line.1952"></a> |
| <span class="sourceLineNo">1953</span> public static Dataset covariance(final Dataset a) {<a name="line.1953"></a> |
| <span class="sourceLineNo">1954</span> return covariance(a, true, false, null); <a name="line.1954"></a> |
| <span class="sourceLineNo">1955</span> }<a name="line.1955"></a> |
| <span class="sourceLineNo">1956</span><a name="line.1956"></a> |
| <span class="sourceLineNo">1957</span> /**<a name="line.1957"></a> |
| <span class="sourceLineNo">1958</span> * See {@link #covariance(Dataset a, Dataset b, boolean rowvar, boolean bias, Integer ddof)} with b = null.<a name="line.1958"></a> |
| <span class="sourceLineNo">1959</span> * @param a<a name="line.1959"></a> |
| <span class="sourceLineNo">1960</span> * @return covariance array of a<a name="line.1960"></a> |
| <span class="sourceLineNo">1961</span> * @since 2.0<a name="line.1961"></a> |
| <span class="sourceLineNo">1962</span> */<a name="line.1962"></a> |
| <span class="sourceLineNo">1963</span> public static Dataset covariance(final Dataset a, <a name="line.1963"></a> |
| <span class="sourceLineNo">1964</span> boolean rowvar, boolean bias, Integer ddof) {<a name="line.1964"></a> |
| <span class="sourceLineNo">1965</span> return covariance(a, null, rowvar, bias, ddof);<a name="line.1965"></a> |
| <span class="sourceLineNo">1966</span> }<a name="line.1966"></a> |
| <span class="sourceLineNo">1967</span><a name="line.1967"></a> |
| <span class="sourceLineNo">1968</span> /**<a name="line.1968"></a> |
| <span class="sourceLineNo">1969</span> * See {@link #covariance(Dataset a, Dataset b, boolean rowvar, boolean bias, Integer ddof)} with b = null, rowvar = true, bias = false and ddof = null.<a name="line.1969"></a> |
| <span class="sourceLineNo">1970</span> * @param a<a name="line.1970"></a> |
| <span class="sourceLineNo">1971</span> * @return covariance array of a concatenated with b<a name="line.1971"></a> |
| <span class="sourceLineNo">1972</span> */<a name="line.1972"></a> |
| <span class="sourceLineNo">1973</span> public static Dataset covariance(final Dataset a, final Dataset b) {<a name="line.1973"></a> |
| <span class="sourceLineNo">1974</span> return covariance(a, b, true, false, null);<a name="line.1974"></a> |
| <span class="sourceLineNo">1975</span> }<a name="line.1975"></a> |
| <span class="sourceLineNo">1976</span><a name="line.1976"></a> |
| <span class="sourceLineNo">1977</span> /**<a name="line.1977"></a> |
| <span class="sourceLineNo">1978</span> * Calculate the covariance matrix (array) of a concatenated with b. This <a name="line.1978"></a> |
| <span class="sourceLineNo">1979</span> * method is directly based on the implementation in numpy (cov). <a name="line.1979"></a> |
| <span class="sourceLineNo">1980</span> * @param a Array containing multiple variable and observations. Each row represents a variable, each column an observation.<a name="line.1980"></a> |
| <span class="sourceLineNo">1981</span> * @param b An extra set of variables and observations. Must be of same type as a and have a compatible shape. <a name="line.1981"></a> |
| <span class="sourceLineNo">1982</span> * @param rowvar When true (default), each row is a variable; when false each column is a variable.<a name="line.1982"></a> |
| <span class="sourceLineNo">1983</span> * @param bias Default normalisation is (N - 1) - N is number of observations. If set true, normalisation is (N). <a name="line.1983"></a> |
| <span class="sourceLineNo">1984</span> * @param ddof Default normalisation is (N - 1). If ddof is set, then normalisation is (N - ddof).<a name="line.1984"></a> |
| <span class="sourceLineNo">1985</span> * @return covariance array of a concatenated with b<a name="line.1985"></a> |
| <span class="sourceLineNo">1986</span> * @since 2.0<a name="line.1986"></a> |
| <span class="sourceLineNo">1987</span> */<a name="line.1987"></a> |
| <span class="sourceLineNo">1988</span> public static Dataset covariance (final Dataset a, final Dataset b, <a name="line.1988"></a> |
| <span class="sourceLineNo">1989</span> boolean rowvar, boolean bias, Integer ddof) {<a name="line.1989"></a> |
| <span class="sourceLineNo">1990</span> <a name="line.1990"></a> |
| <span class="sourceLineNo">1991</span> //Create a working copy of the dataset & check its rank.<a name="line.1991"></a> |
| <span class="sourceLineNo">1992</span> Dataset vars = a.clone();<a name="line.1992"></a> |
| <span class="sourceLineNo">1993</span> if (a.getRank() == 1) {<a name="line.1993"></a> |
| <span class="sourceLineNo">1994</span> vars.setShape(1, a.getShapeRef()[0]);<a name="line.1994"></a> |
| <span class="sourceLineNo">1995</span> }<a name="line.1995"></a> |
| <span class="sourceLineNo">1996</span> <a name="line.1996"></a> |
| <span class="sourceLineNo">1997</span> //1D of variables, so consider rows as variables<a name="line.1997"></a> |
| <span class="sourceLineNo">1998</span> if (vars.getShapeRef()[0] == 1) {<a name="line.1998"></a> |
| <span class="sourceLineNo">1999</span> rowvar = true;<a name="line.1999"></a> |
| <span class="sourceLineNo">2000</span> }<a name="line.2000"></a> |
| <span class="sourceLineNo">2001</span> <a name="line.2001"></a> |
| <span class="sourceLineNo">2002</span> //nr is the number of records; axis is index<a name="line.2002"></a> |
| <span class="sourceLineNo">2003</span> int nr, axis;<a name="line.2003"></a> |
| <span class="sourceLineNo">2004</span> if (rowvar) {<a name="line.2004"></a> |
| <span class="sourceLineNo">2005</span> nr = vars.getShapeRef()[1];<a name="line.2005"></a> |
| <span class="sourceLineNo">2006</span> axis = 0;<a name="line.2006"></a> |
| <span class="sourceLineNo">2007</span> } else {<a name="line.2007"></a> |
| <span class="sourceLineNo">2008</span> nr = vars.getShapeRef()[0];<a name="line.2008"></a> |
| <span class="sourceLineNo">2009</span> axis = 1;<a name="line.2009"></a> |
| <span class="sourceLineNo">2010</span> }<a name="line.2010"></a> |
| <span class="sourceLineNo">2011</span> <a name="line.2011"></a> |
| <span class="sourceLineNo">2012</span> //Set the reduced degrees of freedom & normalisation factor<a name="line.2012"></a> |
| <span class="sourceLineNo">2013</span> if (ddof == null) {<a name="line.2013"></a> |
| <span class="sourceLineNo">2014</span> if (bias == false) {<a name="line.2014"></a> |
| <span class="sourceLineNo">2015</span> ddof = 1;<a name="line.2015"></a> |
| <span class="sourceLineNo">2016</span> } else {<a name="line.2016"></a> |
| <span class="sourceLineNo">2017</span> ddof = 0;<a name="line.2017"></a> |
| <span class="sourceLineNo">2018</span> }<a name="line.2018"></a> |
| <span class="sourceLineNo">2019</span> }<a name="line.2019"></a> |
| <span class="sourceLineNo">2020</span> double norm_fact = nr - ddof;<a name="line.2020"></a> |
| <span class="sourceLineNo">2021</span> if (norm_fact <= 0.) {<a name="line.2021"></a> |
| <span class="sourceLineNo">2022</span> //TODO Some sort of warning here?<a name="line.2022"></a> |
| <span class="sourceLineNo">2023</span> norm_fact = 0.;<a name="line.2023"></a> |
| <span class="sourceLineNo">2024</span> }<a name="line.2024"></a> |
| <span class="sourceLineNo">2025</span> <a name="line.2025"></a> |
| <span class="sourceLineNo">2026</span> //Concatenate additional set of variables with main set<a name="line.2026"></a> |
| <span class="sourceLineNo">2027</span> if (b != null) {<a name="line.2027"></a> |
| <span class="sourceLineNo">2028</span> //Create a working copy of the dataset & check its rank.<a name="line.2028"></a> |
| <span class="sourceLineNo">2029</span> Dataset extraVars = b.clone();<a name="line.2029"></a> |
| <span class="sourceLineNo">2030</span> if (b.getRank() == 1) {<a name="line.2030"></a> |
| <span class="sourceLineNo">2031</span> extraVars.setShape(1, a.getShapeRef()[0]);<a name="line.2031"></a> |
| <span class="sourceLineNo">2032</span> }<a name="line.2032"></a> |
| <span class="sourceLineNo">2033</span> vars = DatasetUtils.concatenate(new Dataset[]{vars, extraVars}, axis);<a name="line.2033"></a> |
| <span class="sourceLineNo">2034</span> }<a name="line.2034"></a> |
| <span class="sourceLineNo">2035</span> <a name="line.2035"></a> |
| <span class="sourceLineNo">2036</span> //Calculate deviations & covariance matrix<a name="line.2036"></a> |
| <span class="sourceLineNo">2037</span> Dataset varsMean = vars.mean(1-axis, false);<a name="line.2037"></a> |
| <span class="sourceLineNo">2038</span> //-vars & varsMean need same shape (this is a hack!)<a name="line.2038"></a> |
| <span class="sourceLineNo">2039</span> int[] meanShape = vars.getShape();<a name="line.2039"></a> |
| <span class="sourceLineNo">2040</span> meanShape[1-axis] = 1;<a name="line.2040"></a> |
| <span class="sourceLineNo">2041</span> varsMean.setShape(meanShape);<a name="line.2041"></a> |
| <span class="sourceLineNo">2042</span> vars.isubtract(varsMean);<a name="line.2042"></a> |
| <span class="sourceLineNo">2043</span> Dataset cov;<a name="line.2043"></a> |
| <span class="sourceLineNo">2044</span> if (rowvar) {<a name="line.2044"></a> |
| <span class="sourceLineNo">2045</span> cov = Maths.divide(LinearAlgebra.dotProduct(vars, Maths.conjugate(vars.transpose())), norm_fact).squeeze();<a name="line.2045"></a> |
| <span class="sourceLineNo">2046</span> } else {<a name="line.2046"></a> |
| <span class="sourceLineNo">2047</span> cov = Maths.divide(LinearAlgebra.dotProduct(vars.transpose(), Maths.conjugate(vars)), norm_fact).squeeze();<a name="line.2047"></a> |
| <span class="sourceLineNo">2048</span> }<a name="line.2048"></a> |
| <span class="sourceLineNo">2049</span> return cov;<a name="line.2049"></a> |
| <span class="sourceLineNo">2050</span> }<a name="line.2050"></a> |
| <span class="sourceLineNo">2051</span>}<a name="line.2051"></a> |
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| </pre> |
| </div> |
| </body> |
| </html> |
