{ From user Lonnie, Model A1_D______2_D_date_t at 16-May-2016 8:13:37 PM }
SoftwareVersion 4.6.2


{ System Variables with non-default values: }
TypeChecking := 1
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Model A1_D______2_D_date_t
Title: 1-D <==> 2-D date transformations
Description: Challenge problems: Transforming between 1-D and 2-D indexes involving months and years.~
~
In this exercise, you'll transform a 2-D array indexed by Month_of_year and Year to a 1-D array indexed by Month. And then you'll do the inverse transformation as well. You are allowed to take advantage of the fact that the cells correspond to dates, if that helps.
Author: Lonnie Chrisman, Ph.D.	~
Lumina Decision Systems
Date: Mon, May 16, 2016 7:33 PM
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FontStyle: Arial,15
FileInfo: 0,Model A1_D______2_D_date_t,2,2,0,0,C:\Users\Lonnie\Documents\Month-Year-Transformations.ana

Index Month_of_year
Title: Month of year
Definition: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
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NodeSize: 48,24
ValueState: 2,88,95,441,379,0,MIDM
{!40000|Att_PrevIndexValue: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']}

Index Year
Title: Year
Definition: 2016..2025
NodeLocation: 96,128,1
NodeSize: 48,24
{!40000|Att_PrevIndexValue: [2016,2017,2018,2019,2020,2021,2022,2023,2024,2025]}

Index Month
Title: Month
Definition: Sequence(1-Jan-2016, 1-Dec-2025, dateUnit:'M')
NodeLocation: 96,192,1
NodeSize: 48,24
ValueState: 2,539,38,439,448,0,MIDM
{!40000|Att_PrevIndexValue: [1-Jan-2016,1-Feb-2016,1-Mar-2016,1-Apr-2016,1-May-2016,1-Jun-2016,1-Jul-2016,1-Aug-2016,1-Sep-2016,1-Oct-2016,1-Nov-2016,1-Dec-2016,1-Jan-2017,1-Feb-2017,1-Mar-2017,1-Apr-2017,1-May-2017,1-Jun-2017,1-Jul-2017,1-Aug-2017,1-Sep-2017,1-Oct-2017,1-Nov-2017,1-Dec-2017,1-Jan-2018,1-Feb-2018,1-Mar-2018,1-Apr-2018,1-May-2018,1-Jun-2018,1-Jul-2018,1-Aug-2018,1-Sep-2018,1-Oct-2018,1-Nov-2018,1-Dec-2018,1-Jan-2019,1-Feb-2019,1-Mar-2019,1-Apr-2019,1-May-2019,1-Jun-2019,1-Jul-2019,1-Aug-2019,1-Sep-2019,1-Oct-2019,1-Nov-2019,1-Dec-2019,1-Jan-2020,1-Feb-2020,1-Mar-2020,1-Apr-2020,1-May-2020,1-Jun-2020,1-Jul-2020,1-Aug-2020,1-Sep-2020,1-Oct-2020,1-Nov-2020,1-Dec-2020,1-Jan-2021,1-Feb-2021,1-Mar-2021,1-Apr-2021,1-May-2021,1-Jun-2021,1-Jul-2021,1-Aug-2021,1-Sep-2021,1-Oct-2021,1-Nov-2021,1-Dec-2021,1-Jan-2022,1-Feb-2022,1-Mar-2022,1-Apr-2022,1-May-2022,1-Jun-2022,1-Jul-2022,1-Aug-2022,1-Sep-2022,1-Oct-2022,1-Nov-2022,1-Dec-2022,1-Jan-2023,1-Feb-2023,1-Mar-2023,1-Apr-2023,1-May-2023,1-Jun-2023,1-Jul-2023,1-Aug-2023,1-Sep-2023,1-Oct-2023,1-Nov-2023,1-Dec-2023,1-Jan-2024,1-Feb-2024,1-Mar-2024,1-Apr-2024,1-May-2024,1-Jun-2024,1-Jul-2024,1-Aug-2024,1-Sep-2024,1-Oct-2024,1-Nov-2024,1-Dec-2024,1-Jan-2025,1-Feb-2025,1-Mar-2025,1-Apr-2025,1-May-2025,1-Jun-2025,1-Jul-2025,1-Aug-2025,1-Sep-2025,1-Oct-2025,1-Nov-2025,1-Dec-2025]}

Variable Array_on_Month
Title: Array on Month
Description: One-D data indexed by Month.
Definition: Table(Month)(103,105.2,106.5,121.7,122.7,112,104.9,115,119.7,127.2,153.4,147.7,127.5,115.9,109.9,137.2,137.8,111.8,109.8,101.4,98.3,105.8,112.7,142.5,124.5,109.3,106.3,116.7,129,129.5,128.2,133,139.7,122.7,118.4,108.2,113.2,133.7,142.6,135.8,126.4,111.2,124.1,124.2,131.6,116,125.3,116.1,119,122.6,114,108.7,102.7,104.1,107.1,96.5,82.8,78.1,74.6,77.2,77.6,74.6,81.5,88.9,89.7,110.1,112.7,142.9,129,124.1,140.9,139.8,125.4,139.2,132.1,151.5,168,174.8,188.4,168.6,185.2,194.9,205.8,198.9,248.4,270.7,278.3,313.2,284.5,309.1,362.7,428.7,436.6,383.1,455.8,471.9,445.3,446.6,430.4,464.4,408.1,426.3,450,508.4,508.5,496.2,519.2,511.9,455.3,437.9,484.9,449.2,493.2,572.5,513,522.5,419.8,431.5,447.3,428.8)
NodeLocation: 232,192,1
NodeSize: 48,24
ValueState: 2,263,27,828,379,1,MIDM
Aliases: Alias Al1463453188
DisplayOutputs: Variable Transformed_to_Y_x_M

Variable Array_on_Year_x_MoY
Title: Array on Year x MoY
Description: 2-D data indexed by month_of_year and year.
Definition: Table(Month_of_year,Year)(~
103,127.5,124.5,113.2,119,77.6,125.4,248.4,445.3,455.3,~
105.2,115.9,109.3,133.7,122.6,74.6,139.2,270.7,446.6,437.9,~
106.5,109.9,106.3,142.6,114,81.5,132.1,278.3,430.4,484.9,~
121.7,137.2,116.7,135.8,108.7,88.9,151.5,313.2,464.4,449.2,~
122.7,137.8,129,126.4,102.7,89.7,168,284.5,408.1,493.2,~
112,111.8,129.5,111.2,104.1,110.1,174.8,309.1,426.3,572.5,~
104.9,109.8,128.2,124.1,107.1,112.7,188.4,362.7,450,513,~
115,101.4,133,124.2,96.5,142.9,168.6,428.7,508.4,522.5,~
119.7,98.3,139.7,131.6,82.8,129,185.2,436.6,508.5,419.8,~
127.2,105.8,122.7,116,78.1,124.1,194.9,383.1,496.2,431.5,~
153.4,112.7,118.4,125.3,74.6,140.9,205.8,455.8,519.2,447.3,~
147.7,142.5,108.2,116.1,77.2,139.8,198.9,471.9,511.9,428.8)
NodeLocation: 232,88,1
NodeSize: 48,32
Aliases: Alias Al1463453189
DisplayOutputs: Variable Transformed_to_Month

Variable Transformed_to_Y_x_M
Title: Transformed to Y x MoY
Description: Write a definition that transforms the 1-D data in Array_on_month into a 2-D array on Month_of_year x Year. ~
~
If you do it correctly, your result should be the same as the result for Array_on_Year_x_MoY. 
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ReformVal: [Year,Month_of_year]
DisplayInputs: Variable Array_on_Month
{!40000|Att_XRole: Year}
{!40000|Att_ColorRole: Month_of_year}

Module Solutions
Title: Solutions
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Variable Transformed_to_Y_x_1
Title: Transformed to Y x MoY
Description: When mapping from a 1-D array to a 2-D array, all you need is a 2-D map, where for each of the 2-D combinations, it specifies the element from the 1-D array. This map establishes the correspondence between the indexes. Once you have that map, then the transformation is just x[ i = map ], where i is the index of x. This general pattern generalizes to any number of target dimensions (e.g., mapping from 1-D to 4-D). ~
~
In this example, the map is obtained easily using MakeDate. In more complex cases, you might want to use a separate variable to hold the map, so that the mapping is computed only once.
Definition: Array_on_Month[ Month = MakeDate( Year, @Month_of_year) ]
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ReformVal: [Year,Month_of_year]
{!40000|Att_XRole: Year}
{!40000|Att_ColorRole: Month_of_year}

Variable Transformed_to_Mont1
Title: Transformed to Month
Description: This is a super-efficient way to do it, although it makes an assumption that our Month index starts in the first month and extends to the last month of the year.
Definition: ConcatRows( Array_on_Year_x_MoY, Year, Month_of_year, Month )
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Alias Al1463453188
Title: Array on Month
Definition: 1
NodeLocation: 104,144,1
NodeSize: 48,24
Original: Array_on_Month

Alias Al1463453189
Title: Array on Year x MoY
Definition: 1
NodeLocation: 96,56,1
NodeSize: 48,32
Original: Array_on_Year_x_MoY

Variable Transformed_to_Mont2
Title: Transformed to Month
Description: This demonstrates one possible method, which is extremely general, for mapping from 2-D to 1-D (or really from any fixed number of dimensions to any arbitrary number of dimensions). We have two mappings, from the target dimensions to the source dimensions. For example, DatePart(Month,'Y') maps from Month to Year -- our source array has Year, and we want to go to Month.
Definition: Array_on_Year_x_MoY[ Year = DatePart(Month,'Y'), ~
						@Month_of_year = DatePart(Month,'M')]
NodeLocation: 264,56,1
NodeSize: 56,24
WindState: 2,102,87,784,329

Close Solutions

Variable Transformed_to_Month
Title: Transformed to Month
Description: Write a definition here that transforms the 2-D data in Array_on_Year_x_Month to a 1-D array on Month.~
~
If you do it correctly, your result should be the same as the result for Array_on_month.
NodeLocation: 424,88,1
NodeSize: 56,24
WindState: 2,564,281,476,224
ValueState: 2,216,223,416,303,0,MIDM
DisplayInputs: Variable Array_on_Year_x_MoY

Close A1_D______2_D_date_t