Implemented ArnaudLegouxMAVisitor

hosseinmoein · Jul 12, 2021 · 62354a7 · 62354a7
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diff --git a/docs/HTML/ArnaudLegouxMAVisitor.html b/docs/HTML/ArnaudLegouxMAVisitor.html
@@ -0,0 +1,113 @@
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+<!DOCTYPE html>
+<html>
+<body>
+  <table align="center" border="1">
+
+    <tr bgcolor="lightblue">
+      <th>Signature</th> <th>Description</th> <th>Parameters</th>
+    </tr>
+    <tr bgcolor="lightgrey">
+      <td bgcolor="maroon"> <font color="white">
+        <PRE><B>#include &lt;DataFrame/DataFrameFinancialVisitors.h&gt;
+
+template&lt;typename T, typename I = unsigned long&gt;
+struct ArnaudLegouxMAVisitor;
+
+// -------------------------------------
+
+template&lt;typename T, typename I = unsigned long&gt;
+using alma_v = ArnaudLegouxMAVisitor&lt;T, I&gt;;
+        </B></PRE></font>
+      </td>
+      <td>
+        This is a “single action visitor”, meaning it is passed the whole data vector in one call and you must use the single_act_visit() interface.<BR><BR>
+        This visitor calculates the rolling values of Arnaud Legoux Moving Average. It requires 1 input column.<BR>
+        The result is a vector of values with same number of items as the given column. The first roll_count items, in the result, will be NAN.<BR>
+        The ALMA is a technical analysis tool that aims to give investors and traders a more reliable trading signal by reducing the noise that can interfere with traditional moving averages. It eliminates the small fluctuations in an asset price to make the trend clearer. The ALMA reduces price lag and creates a smoother line than other moving averages. Rather than a straightforward moving average for a certain period, it applies a moving average twice – from left to right as well as right to left.<BR>
+        <I>
+        <PRE>
+    explicit
+    ArnaudLegouxMAVisitor(size_t roll_count = 10, T sigma = 6.0, T dist_offset = 0.85)
+
+    <B>roll_count</B>: Moving average period
+    <B>sigma</B>: The standard deviation applied to the combo line. It makes the combo line sharper.
+    <B>dis_offset</B>: Offset is the Gaussian applied to the combo line and it is 0.85 by default.
+                Setting offset at 1 makes it fully aligned to the current price just
+                like the exponential moving average.
+        </PRE>
+        </I>
+      </td>
+      <td width="12%">
+        <B>T</B>: Column data type<BR>
+        <B>I</B>: Index type
+      </td>
+    </tr>
+
+  </table>
+
+<pre style='color:#000000;background:#ffffff;'><span style='color:#800000; font-weight:bold; '>static</span> <span style='color:#800000; font-weight:bold; '>void</span> test_ArnaudLegouxMAVisitor<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span>  <span style='color:#800080; '>{</span>
+
+    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>cout</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#800000; '>"</span><span style='color:#0f69ff; '>\n</span><span style='color:#0000e6; '>Testing ArnaudLegouxMAVisitor{  } ...</span><span style='color:#800000; '>"</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>endl</span><span style='color:#800080; '>;</span>
+
+    <span style='color:#800000; font-weight:bold; '>typedef</span> StdDataFrame<span style='color:#800080; '>&lt;</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>string</span><span style='color:#800080; '>></span> StrDataFrame<span style='color:#800080; '>;</span>
+
+    StrDataFrame    df<span style='color:#800080; '>;</span>
+
+    <span style='color:#800000; font-weight:bold; '>try</span>  <span style='color:#800080; '>{</span>
+        df<span style='color:#808030; '>.</span>read<span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>data/SHORT_IBM.csv</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> io_format<span style='color:#800080; '>::</span>csv2<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+
+        alma_v<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#808030; '>,</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>string</span><span style='color:#800080; '>></span> alma<span style='color:#800080; '>;</span>
+
+        df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>IBM_Close</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> alma<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+
+        assert<span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>=</span><span style='color:#808030; '>=</span> <span style='color:#008c00; '>1721</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span>isnan<span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>0</span><span style='color:#808030; '>]</span><span style='color:#808030; '>)</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span>isnan<span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>9</span><span style='color:#808030; '>]</span><span style='color:#808030; '>)</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>10</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>187.533</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>14</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>186.359</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>25</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>176.892</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>1720</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>117.841</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>1712</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>127.677</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+        assert<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>abs</span><span style='color:#808030; '>(</span>alma<span style='color:#808030; '>.</span>get_result<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#808030; '>[</span><span style='color:#008c00; '>1707</span><span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> <span style='color:#008000; '>121.435</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
+    <span style='color:#800080; '>}</span>
+    <span style='color:#800000; font-weight:bold; '>catch</span> <span style='color:#808030; '>(</span><span style='color:#800000; font-weight:bold; '>const</span> DataFrameError <span style='color:#808030; '>&amp;</span>ex<span style='color:#808030; '>)</span>  <span style='color:#800080; '>{</span>
+        <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>cout</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> ex<span style='color:#808030; '>.</span>what<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>endl</span><span style='color:#800080; '>;</span>
+    <span style='color:#800080; '>}</span>
+<span style='color:#800080; '>}</span>
+</pre>
+<!--Created using ToHtml.com on 2021-07-12 15:55:00 UTC -->
+
+</body>
+</html>
+
+<!--
+Local Variables:
+mode:HTML
+tab-width:4
+c-basic-offset:4
+End:
+-->
diff --git a/docs/HTML/DataFrame.html b/docs/HTML/DataFrame.html
@@ -737,6 +737,10 @@ <H2><font color="blue">Table of Features (with Code Samples)</font></H2>
       <th><font color="white">DataFrame Built-in Financial Visitors</font></th>
     </tr>
 
+    <tr class="item" onmouseover="this.style.backgroundColor='#ffff66';" onmouseout="this.style.backgroundColor='#d4e3e5';">
+      <td title="Calculates Arnaud Legoux Moving Average">struct <a href="https://htmlpreview.github.io/?https://github.com/hosseinmoein/DataFrame/blob/master/docs/HTML/ArnaudLegouxMAVisitor.html">ArnaudLegouxMAVisitor</a>{  }</td>
+    </tr>
+
     <tr class="item" onmouseover="this.style.backgroundColor='#ffff66';" onmouseout="this.style.backgroundColor='#d4e3e5';">
       <td title="Calculates Average Directional Movement Index (ADX)">struct <a href="https://htmlpreview.github.io/?https://github.com/hosseinmoein/DataFrame/blob/master/docs/HTML/AvgDirMovIdxVisitor.html">AvgDirMovIdxVisitor</a>{  }</td>
     </tr>

diff --git a/include/DataFrame/DataFrameFinancialVisitors.h b/include/DataFrame/DataFrameFinancialVisitors.h
@@ -3479,6 +3479,75 @@ struct  CenterOfGravityVisitor  {
 template<typename T, typename I = unsigned long>
 using cog_v = CenterOfGravityVisitor<T, I>;
 
+// ----------------------------------------------------------------------------
+
+// Arnaud Legoux Moving Average
+//
+template<typename T, typename I = unsigned long>
+struct  ArnaudLegouxMAVisitor  {
+
+    DEFINE_VISIT_BASIC_TYPES_3
+
+    template <typename K, typename H>
+    inline void
+    operator() (const K &idx_begin,
+                const K &idx_end,
+                const H &column_begin,
+                const H &column_end)  {
+
+        if (roll_count_ == 0)  return;
+
+        GET_COL_SIZE
+        assert (roll_count_ > 1);
+        assert (col_s > roll_count_);
+
+        result_type result (col_s, std::numeric_limits<T>::quiet_NaN());
+
+        for (size_type i = roll_count_; i < col_s; ++i)  {
+            value_type  win_sum { 0 };
+
+            for (size_type j = 0; j < roll_count_; ++j)
+                win_sum += wtd_[j] * *(column_begin + (i - j));
+
+            result[i] = win_sum / cum_sum_;
+        }
+
+        result_.swap(result);
+    }
+
+    DEFINE_PRE_POST
+    DEFINE_RESULT
+
+    explicit
+    ArnaudLegouxMAVisitor(size_type r_count = 10,
+                          value_type sigma = 6.0,
+                          value_type dist_offset = 0.85)
+        : roll_count_(r_count),
+          m_(dist_offset * T(r_count - 1)),
+          s_(T(r_count) / sigma),
+          wtd_(r_count)  {
+
+        for (size_type i = 0; i < roll_count_; ++i)  {
+            wtd_[i] =
+                std::exp(T(-1) *
+                         ((T(i) - m_) * (T(i) - m_)) /
+                         ((T(2) * s_ * s_)));
+            cum_sum_ += wtd_[i];
+        }
+    }
+
+private:
+
+    const size_type         roll_count_;
+    const value_type        m_;
+    const value_type        s_;
+    value_type              cum_sum_ { 0 };
+    std::vector<value_type> wtd_;
+    result_type             result_ { };
+};
+
+template<typename T, typename I = unsigned long>
+using alma_v = ArnaudLegouxMAVisitor<T, I>;
 
 } // namespace hmdf
 

diff --git a/test/dataframe_tester_2.cc b/test/dataframe_tester_2.cc
@@ -3641,6 +3641,39 @@ static void test_CenterOfGravityVisitor()  {
     }
 }
 
+// -----------------------------------------------------------------------------
+
+static void test_ArnaudLegouxMAVisitor()  {
+
+    std::cout << "\nTesting ArnaudLegouxMAVisitor{  } ..." << std::endl;
+
+    typedef StdDataFrame<std::string> StrDataFrame;
+
+    StrDataFrame    df;
+
+    try  {
+        df.read("data/SHORT_IBM.csv", io_format::csv2);
+
+        alma_v<double, std::string> alma;
+
+        df.single_act_visit<double>("IBM_Close", alma);
+
+        assert(alma.get_result().size() == 1721);
+        assert(std::isnan(alma.get_result()[0]));
+        assert(std::isnan(alma.get_result()[9]));
+        assert(std::abs(alma.get_result()[10] - 187.533) < 0.001);
+        assert(std::abs(alma.get_result()[14] - 186.359) < 0.001);
+        assert(std::abs(alma.get_result()[25] - 176.892) < 0.001);
+        assert(std::abs(alma.get_result()[1720] - 117.841) < 0.001);
+        assert(std::abs(alma.get_result()[1712] - 127.677) < 0.001);
+        assert(std::abs(alma.get_result()[1707] - 121.435) < 0.001);
+    }
+    catch (const DataFrameError &ex)  {
+        std::cout << ex.what() << std::endl;
+    }
+}
+
+
 // -----------------------------------------------------------------------------
 int main(int argc, char *argv[]) {
 
@@ -3712,6 +3745,7 @@ int main(int argc, char *argv[]) {
     test_HeikinAshiCndlVisitor();
     test_FastFourierTransVisitor();
     test_CenterOfGravityVisitor();
+    test_ArnaudLegouxMAVisitor();
 
     return (0);
 }

diff --git a/test/dataframe_tester_output.txt b/test/dataframe_tester_output.txt
@@ -1638,3 +1638,5 @@ Testing FastFourierTransVisitor{  } ...
 (8.88178e-16,-4.44089e-16) | (1,1) | (3,3) | (4,4) | (4,4) | (3,3) | (1,1) |
 
 Testing CenterOfGravityVisitor{  } ...
+
+Testing ArnaudLegouxMAVisitor{  } ...