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The Wave Matrix Module Function Code
Published:
It's late...
I'll be traveling to IA early tomorrow.
Below is the code and a link to a text file of the code.
I will get more in to it later.
For now, you can examine.
If you know what to do, do it.
https://member.lotterypost.com/jadelottery/images/TheWaveMatrixModuleFunctionCode-00.txt
____________________________________________________________
Function TheWaveMatrix(ByVal theRange As Range, _
ByVal waves As Long, _
ByVal iterations As Integer, _
ByVal precision As Integer) As Variant()
On Error GoTo ExitFunction
Dim Er(0) As Variant: Er(0) = "Error"
Dim i, j, k, items, mn, mx As Long: items = theRange.Rows.Count
Dim arry() As Double: ReDim arry(1 To items): For i = 1 To items: arry(i) = theRange.Cells(i, 1): Next i
Dim matrix() As Variant: ReDim matrix(1 To items, 1 To (waves + 2))
Dim a, b, degree, sum_y, sum_xy, avg_x, avg_y, avg_xx, avg_xy As Double
Dim amplitude_degree, amplitude_degree_precision As Double
Dim frequency_degree, frequency_degree_precision As Double
Dim degree_precision As Double: degree_precision = 1
Dim optimal_found, optimal, last_optimal_state, arry_zeroed As Boolean
Dim arry_up() As Double: ReDim arry_up(1 To items)
Dim arry_down() As Double: ReDim arry_down(1 To items)
Dim arry_average() As Double: ReDim arry_average(1 To items)
Dim arry_sqr_sum, BMA_arry_sqr_sum, RMS_arry, RMS_BMA_arry As Double
Dim frequency() As Long: ReDim frequency(1 To items)
Dim diff_frequency() As Long: ReDim diff_frequency(1 To items - 1)
Dim diff_diff_frequency() As Long: ReDim diff_diff_frequency(1 To items - 2)
Dim frequency_set(1 To 3) As Long
If (theRange.Columns.Count > 1) Then Er(0) = " Too Many Columns Selected": GoTo ExitFunction
If (waves < 1) Then Er(0) = " # of Waves < 1": GoTo ExitFunction
If (iterations < 1) Then Er(0) = " # of Iterations < 1": GoTo ExitFunction
If (precision < 1) Or (precision > 8) Then Er(0) = " Precision = {1, 2, 3, 4, 5, 6, 7, 8}": GoTo ExitFunction
For i = 1 To precision
degree_precision = degree_precision / 10
Next i
sum_y = 0
sum_xy = 0
For i = 1 To items
sum_y = sum_y + arry(i)
sum_xy = sum_xy + i * arry(i)
Next i
avg_y = sum_y / items
avg_xy = sum_xy / items
avg_x = (items + 1) / 2
avg_xx = (items + 1) * (2 * items + 1) / 6
b = (avg_xy - avg_x * avg_y) / (avg_xx - avg_x * avg_x)
a = avg_y - (b * avg_x)
For i = 1 To items
matrix(i, 1) = a + (b * i)
arry(i) = arry(i) - matrix(i, 1)
Next i
arry_zeroed = False
For k = 1 To waves
sum_y = 0
For i = 1 To items
sum_y = sum_y + Abs(arry(i))
Next i
If (sum_y = 0) Then arry_zeroed = True
If arry_zeroed Then
For i = 1 To items
matrix(i, k + 1) = arry(i)
Next i
Else
amplitude_degree = 0
amplitude_degree_precision = 1
optimal_found = False
For i = 1 To items
arry_average(i) = arry(i)
Next i
For j = 1 To iterations
arry_up(1) = arry_average(1)
For i = 2 To items
arry_up(i) = (arry_up(i - 1) + Exp(amplitude_degree) * arry_average(i)) / (1 + Exp(amplitude_degree))
Next i
arry_down(items) = arry_average(items)
For i = (items - 1) To 1 Step -1
arry_down(i) = (arry_down(i + 1) + Exp(amplitude_degree) * arry_average(i)) / (1 + Exp(amplitude_degree))
Next i
For i = 1 To items
arry_average(i) = (arry_up(i) + arry_down(i)) / 2
Next i
Next j
arry_sqr_sum = 0
BMA_arry_sqr_sum = 0
RMS_arry = 0
RMS_BMA_arry = 0
For i = 1 To items
arry_sqr_sum = arry_sqr_sum + arry(i) * arry(i)
BMA_arry_sqr_sum = BMA_arry_sqr_sum + arry_average(i) * arry_average(i)
Next i
RMS_arry = Sqr(arry_sqr_sum / items)
RMS_BMA_arry = Sqr(BMA_arry_sqr_sum / items)
If ((RMS_arry / RMS_BMA_arry) > 2) Then
optimal = True
Else
optimal = False
End If
last_optimal_state = optimal
Do
For i = 1 To items
arry_average(i) = arry(i)
Next i
For j = 1 To iterations
arry_up(1) = arry_average(1)
For i = 2 To items
arry_up(i) = (arry_up(i - 1) + Exp(amplitude_degree) * arry_average(i)) / (1 + Exp(amplitude_degree))
Next i
arry_down(items) = arry_average(items)
For i = (items - 1) To 1 Step -1
arry_down(i) = (arry_down(i + 1) + Exp(amplitude_degree) * arry_average(i)) / (1 + Exp(amplitude_degree))
Next i
For i = 1 To items
arry_average(i) = (arry_up(i) + arry_down(i)) / 2
Next i
Next j
arry_sqr_sum = 0
BMA_arry_sqr_sum = 0
RMS_arry = 0
RMS_BMA_arry = 0
For i = 1 To items
arry_sqr_sum = arry_sqr_sum + arry(i) * arry(i)
BMA_arry_sqr_sum = BMA_arry_sqr_sum + arry_average(i) * arry_average(i)
Next i
RMS_arry = Sqr(arry_sqr_sum / items)
RMS_BMA_arry = Sqr(BMA_arry_sqr_sum / items)
If ((RMS_arry / RMS_BMA_arry) > 2) Then
optimal = True
Else
optimal = False
End If
If (Not optimal) And (Not last_optimal_state) Then
amplitude_degree = amplitude_degree - amplitude_degree_precision
ElseIf (Not optimal) And (last_optimal_state) Then
amplitude_degree = amplitude_degree - amplitude_degree_precision
amplitude_degree_precision = amplitude_degree_precision / 10
ElseIf (optimal) And (last_optimal_state) Then
amplitude_degree = amplitude_degree + amplitude_degree_precision
ElseIf (optimal) And (Not last_optimal_state) Then
amplitude_degree = amplitude_degree + amplitude_degree_precision
amplitude_degree_precision = amplitude_degree_precision / 10
End If
If (optimal) And (amplitude_degree_precision <= degree_precision) Then optimal_found = True
If (Abs(amplitude_degree) >= 100) Then optimal_found = True
last_optimal_state = optimal
Loop Until optimal_found
frequency_degree = 0
frequency_degree_precision = 1
optimal_found = False
For i = 1 To items
arry_average(i) = arry(i)
Next i
For j = 1 To iterations
arry_up(1) = arry_average(1)
For i = 2 To items
arry_up(i) = (arry_up(i - 1) + Exp(frequency_degree) * arry_average(i)) / (1 + Exp(frequency_degree))
Next i
arry_down(items) = arry_average(items)
For i = (items - 1) To 1 Step -1
arry_down(i) = (arry_down(i + 1) + Exp(frequency_degree) * arry_average(i)) / (1 + Exp(frequency_degree))
Next i
For i = 1 To items
arry_average(i) = (arry_up(i) + arry_down(i)) / 2
Next i
Next j
frequency_set(1) = 0
frequency_set(2) = 0
frequency_set(3) = 0
For i = 1 To items
If (arry_average(i) > 0) Then
frequency(i) = 1
Else
frequency(i) = 0
End If
Next i
For i = 1 To items - 1
If ((arry_average(i + 1) - arry_average(i)) > 0) Then
diff_frequency(i) = 1
Else
diff_frequency(i) = 0
End If
Next i
For i = 1 To items - 2
If ((arry_average(i + 2) - 2 * arry_average(i + 1) + arry_average(i)) > 0) Then
diff_diff_frequency(i) = 1
Else
diff_diff_frequency(i) = 0
End If
Next i
For i = 1 To items - 1
frequency_set(1) = frequency_set(1) + Abs(frequency(i + 1) - frequency(i))
Next i
For i = 1 To items - 2
frequency_set(2) = frequency_set(2) + Abs(diff_frequency(i + 1) - diff_frequency(i))
Next i
For i = 1 To items - 3
frequency_set(3) = frequency_set(3) + Abs(diff_diff_frequency(i + 1) - diff_diff_frequency(i))
Next i
mn = frequency_set(1)
mx = frequency_set(1)
If frequency_set(2) < mn Then mn = frequency_set(2)
If frequency_set(2) > mx Then mx = frequency_set(2)
If frequency_set(3) < mn Then mn = frequency_set(3)
If frequency_set(3) > mx Then mx = frequency_set(3)
If ((mx - mn) > 3) Then
optimal = False
Else
optimal = True
End If
last_optimal_state = optimal
Do
For i = 1 To items
arry_average(i) = arry(i)
Next i
For j = 1 To iterations
arry_up(1) = arry_average(1)
For i = 2 To items
arry_up(i) = (arry_up(i - 1) + Exp(frequency_degree) * arry_average(i)) / (1 + Exp(frequency_degree))
Next i
arry_down(items) = arry_average(items)
For i = (items - 1) To 1 Step -1
arry_down(i) = (arry_down(i + 1) + Exp(frequency_degree) * arry_average(i)) / (1 + Exp(frequency_degree))
Next i
For i = 1 To items
arry_average(i) = (arry_up(i) + arry_down(i)) / 2
Next i
Next j
frequency_set(1) = 0
frequency_set(2) = 0
frequency_set(3) = 0
For i = 1 To items
If (arry_average(i) > 0) Then
frequency(i) = 1
Else
frequency(i) = 0
End If
Next i
For i = 1 To items - 1
If ((arry_average(i + 1) - arry_average(i)) > 0) Then
diff_frequency(i) = 1
Else
diff_frequency(i) = 0
End If
Next i
For i = 1 To items - 2
If ((arry_average(i + 2) - 2 * arry_average(i + 1) + arry_average(i)) > 0) Then
diff_diff_frequency(i) = 1
Else
diff_diff_frequency(i) = 0
End If
Next i
For i = 1 To items - 1
frequency_set(1) = frequency_set(1) + Abs(frequency(i + 1) - frequency(i))
Next i
For i = 1 To items - 2
frequency_set(2) = frequency_set(2) + Abs(diff_frequency(i + 1) - diff_frequency(i))
Next i
For i = 1 To items - 3
frequency_set(3) = frequency_set(3) + Abs(diff_diff_frequency(i + 1) - diff_diff_frequency(i))
Next i
mn = frequency_set(1)
mx = frequency_set(1)
If frequency_set(2) < mn Then mn = frequency_set(2)
If frequency_set(2) > mx Then mx = frequency_set(2)
If frequency_set(3) < mn Then mn = frequency_set(3)
If frequency_set(3) > mx Then mx = frequency_set(3)
If ((mx - mn) > 3) Then
optimal = False
Else
optimal = True
End If
If (Not optimal) And (Not last_optimal_state) Then
frequency_degree = frequency_degree - frequency_degree_precision
ElseIf (Not optimal) And (last_optimal_state) Then
frequency_degree = frequency_degree - frequency_degree_precision
frequency_degree_precision = frequency_degree_precision / 10
ElseIf (optimal) And (Not last_optimal_state) Then
frequency_degree = frequency_degree + frequency_degree_precision
frequency_degree_precision = frequency_degree_precision / 10
ElseIf (optimal) And (last_optimal_state) Then
frequency_degree = frequency_degree + frequency_degree_precision
End If
If (optimal) And (frequency_degree_precision <= degree_precision) Then optimal_found = True
If (Abs(frequency_degree) >= 100) Then optimal_found = True
last_optimal_state = optimal
Loop Until optimal_found
degree = (amplitude_degree + frequency_degree) / 2
For i = 1 To items
arry_average(i) = arry(i)
Next i
For j = 1 To iterations
arry_up(1) = arry_average(1)
For i = 2 To items
arry_up(i) = (arry_up(i - 1) + Exp(degree) * arry_average(i)) / (1 + Exp(degree))
Next i
arry_down(items) = arry_average(items)
For i = (items - 1) To 1 Step -1
arry_down(i) = (arry_down(i + 1) + Exp(degree) * arry_average(i)) / (1 + Exp(degree))
Next i
For i = 1 To items
arry_average(i) = (arry_up(i) + arry_down(i)) / 2
Next i
Next j
For i = 1 To items
matrix(i, k + 1) = arry_average(i)
arry(i) = arry(i) - matrix(i, k + 1)
Next i
End If
Next k
For i = 1 To items
matrix(i, waves + 2) = arry(i)
Next i
TheWaveMatrix = matrix()
Exit Function
ExitFunction:
If Er(0) = "Error" Then Er(0) = " Error - " & err.Number & ", " & err.Description
TheWaveMatrix = Er()
End Function
Comments
I'll post a "How To..." either tonight or tomorrow.
Keep in mind, I will not be running an Excel 101 Class.
I'll expect you to know how to use Excel reasonably well and how to navigate the spreadsheet and using functions therein.
Post a Comment
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