Chapter 7 Support Tools

7.1 FF_CONTAINER_MAP_DISPLAY Examples

Go back to fan’s MEconTools Toolbox (bookdown), Matlab Code Examples Repository (bookdown), or Math for Econ with Matlab Repository (bookdown).

Examples](https://fanwangecon.github.io/M4Econ/), or** Dynamic Asset This is the example vignette for function: ff_container_map_display from the MEconTools Package. This function summarizes statistics of matrixes stored in a container map, as well as scalar, string, function and other values stored in container maps.

7.1.1 Test FF_CONTAINER_MAP_DISPLAY Defaults

Call the function with defaults.

ff_container_map_display();

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xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
 ND Array (Matrix etc)
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                      i     idx    ndim    numel    rowN    colN     sum       mean        std      coefvari       min          max  
                      __    ___    ____    _____    ____    ____    ______    _______    _______    ________    __________    _______

    mat_1              1     7      2        12       3       4     6.5142    0.54285     0.2232    0.41115        0.22685    0.98076
    mat_2              2     8      2      2650      50      53     1313.3    0.49559    0.29232    0.58985     6.7838e-05    0.99964
    mat_2_boolean      3     9      2      2650      50      53       1361    0.51358    0.49991    0.97337              0          1
    mat_3              4    10      2         4       2       2     1.8111    0.45277    0.45111    0.99635     0.00012471    0.88615
    tensor_1           5    15      3        16       2       8     7.3043    0.45652    0.27787    0.60867       0.018091     0.8345
    tensor_2           6    16      3        75       3      25     40.195    0.53593    0.29044    0.54194      0.0024293    0.99731
    tensor_3           7    17      2         4       1       4     1.6926    0.42315    0.37389    0.88359         0.1219    0.91553
    tesseract_1        8    18      4        72       3      24     34.321    0.47669    0.26374    0.55327       0.010239    0.96435
    tesseract_2        9    19      4        20       2      10     8.4191    0.42096    0.28981    0.68846       0.043114    0.97146
    tesseract_bl_3    10    20      4        10       1      10          3        0.3    0.48305     1.6102              0          1

xxx TABLE:mat_1 xxxxxxxxxxxxxxxxxx
            c1         c2         c3         c4   
          _______    _______    _______    _______

    r1    0.69647    0.55131    0.98076    0.39212
    r2    0.28614    0.71947    0.68483    0.34318
    r3    0.22685    0.42311    0.48093    0.72905

xxx TABLE:mat_2 xxxxxxxxxxxxxxxxxx
              c1          c2         c3          c4         c50         c51         c52         c53   
           ________    ________    _______    ________    ________    ________    ________    ________

    r1      0.43857      0.6249    0.17108     0.56564    0.072152     0.67855     0.61667     0.54002
    r2     0.059678     0.67469    0.82911    0.084904     0.63289     0.27236     0.32528     0.24957
    r3      0.39804     0.84234    0.33867     0.58267    0.046367     0.44513    0.075047      0.7839
    r4        0.738    0.083195    0.55237     0.81484     0.50561     0.11117     0.59532     0.35603
    r5      0.18249     0.76368    0.57855     0.33707     0.10653    0.028681      0.7435     0.91869
    r46      0.6813     0.55326    0.88786     0.69983     0.83758     0.16382     0.74191    0.065638
    r47     0.87546     0.85445    0.69631     0.66117     0.97069     0.79092     0.42466     0.78725
    r48     0.51042     0.38484    0.44033    0.049097    0.017768     0.33302     0.24401     0.97956
    r49     0.66931     0.31679    0.43821      0.7923     0.12979     0.75311     0.79466    0.079086
    r50     0.58594     0.35426     0.7651     0.51872     0.86415     0.58281     0.84795      0.4579

xxx TABLE:mat_2_boolean xxxxxxxxxxxxxxxxxx
            c1       c2       c3       c4       c50      c51      c52      c53 
           _____    _____    _____    _____    _____    _____    _____    _____

    r1     true     false    false    true     true     false    true     true 
    r2     true     false    true     true     false    false    true     true 
    r3     false    true     false    true     false    true     false    true 
    r4     false    true     false    false    false    true     true     true 
    r5     true     true     true     false    true     false    false    true 
    r46    false    true     true     false    true     true     true     true 
    r47    true     true     true     true     true     true     false    false
    r48    true     false    false    false    true     true     false    true 
    r49    true     true     false    true     true     true     false    false
    r50    false    false    false    false    false    false    false    false

xxx TABLE:mat_3 xxxxxxxxxxxxxxxxxx
              c1          c2   
          __________    _______

    r1    0.00012471    0.13253
    r2       0.88615    0.79226

xxx TABLE:tensor_1 xxxxxxxxxxxxxxxxxx
             c1         c2         c3         c4         c5         c6         c7        c8   
          ________    _______    _______    _______    _______    _______    ______    _______

    r1    0.019363    0.34271    0.52167    0.53703    0.75756    0.68839    0.8345    0.26597
    r2    0.018091    0.33355    0.11738    0.77857    0.81933    0.28644    0.6157      0.368

xxx TABLE:tensor_2 xxxxxxxxxxxxxxxxxx
             c1         c2         c3         c4         c22        c23         c24         c25  
          ________    _______    _______    _______    _______    _______    _________    _______

    r1     0.51866    0.40495    0.48278    0.99731    0.46584    0.62976     0.035924    0.10505
    r2    0.028692    0.37408    0.24149    0.35201    0.66054    0.87243    0.0024293    0.81088
    r3     0.87339    0.19457    0.83212    0.15315    0.77859    0.96663       0.2501     0.8056

xxx TABLE:tensor_3 xxxxxxxxxxxxxxxxxx
            c1        c2        c3         c4   
          ______    ______    _______    _______

    r1    0.1219    0.5119    0.91553    0.14329

xxx TABLE:tesseract_1 xxxxxxxxxxxxxxxxxx
            c1         c2         c3          c4         c21        c22        c23        c24  
          _______    _______    _______    ________    _______    _______    _______    _______

    r1    0.64531    0.59299    0.32115     0.67653    0.90328    0.56911    0.52562    0.12014
    r2    0.74558     0.5007    0.46142     0.21384    0.35564    0.13732      0.155    0.23786
    r3    0.91137    0.46403    0.18118    0.049919    0.46246    0.46842    0.75348    0.64547

xxx TABLE:tesseract_2 xxxxxxxxxxxxxxxxxx
             c1         c2         c3         c4         c7         c8          c9         c10  
          ________    _______    _______    _______    _______    _______    ________    _______

    r1     0.28898    0.48211    0.44359    0.97146    0.61782    0.65121     0.80715    0.11605
    r2    0.094493    0.34941    0.17595    0.14192    0.16754    0.57097    0.043114    0.70518

xxx TABLE:tesseract_bl_3 xxxxxxxxxxxxxxxxxx
           c1       c2       c3       c4       c7       c8       c9       c10 
          _____    _____    _____    _____    _____    _____    _____    _____

    r1    false    false    true     true     false    true     false    false

----------------------------------------
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
 Scalars
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                      i    idx     value 
                      _    ___    _______

    boolean_1         1     1           1
    empty             2     2         NaN
    mat_4             3    11     0.74898
    string_float_1    4    13      1021.1
    string_int_1      5    14        1021

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 String
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                      i     idx            string        
                     ___    ____    _____________________

    list_string_1    "1"    "5"     "col1;col2;col3;col4"
    list_string_2    "2"    "6"     "row1;row2;row3;row4"
    string_1         "3"    "12"    "Table Name"         

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 Functions
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              i     idx      functionString   
             ___    ___    ___________________

    func1    "1"    "3"    "@(x)1+2+x"        
    func2    "2"    "4"    "@(x,y)x*1+sqrt(y)"

7.1.2 Test FF_CONTAINER_MAP_DISPLAY summarize Matrix Only

Three large matrixes, show summaries

% Create Container
mp_container_map = containers.Map('KeyType','char', 'ValueType','any');
rng(123);
mp_container_map('mat_1') = rand(100,100);
mp_container_map('mat_2') = rand(100,100)*2 + 1;
mp_container_map('mat_2_boolean') = (rand(100,100) > 0.5);
% Will only print 
ff_container_map_display(mp_container_map);

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CONTAINER NAME: mp_container_map ND Array (Matrix etc)
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                     i    idx    ndim    numel    rowN    colN     sum       mean        std      coefvari       min          max  
                     _    ___    ____    _____    ____    ____    ______    _______    _______    ________    __________    _______

    mat_1            1     1      2      10000    100     100     4982.3    0.49823    0.28829    0.57863     6.7838e-05    0.99989
    mat_2            2     2      2      10000    100     100      20029     2.0029    0.57632    0.28774         1.0003     2.9993
    mat_2_boolean    3     3      2      10000    100     100       4995     0.4995    0.50002     1.0011              0          1

7.1.3 Test FF_CONTAINER_MAP_DISPLAY Show Matrix Subset

A container map with three small matrixes, print only only 2 rows and 3 columns.

% Create Container
mp_container_map = containers.Map('KeyType','char', 'ValueType','any');
rng(789);
mp_container_map('mat_1') = rand(3,4);
mp_container_map('mat_2') = rand(50,53);
mp_container_map('mat_2_boolean') = (rand(50,53) > 0.5);
% Will only print 
ff_container_map_display(mp_container_map, 2, 3);

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xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
CONTAINER NAME: mp_container_map ND Array (Matrix etc)
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
                     i    idx    ndim    numel    rowN    colN     sum       mean        std      coefvari       min          max  
                     _    ___    ____    _____    ____    ____    ______    _______    _______    ________    __________    _______

    mat_1            1     1      2        12       3       4     4.9876    0.41564    0.33586    0.80805        0.01062    0.97541
    mat_2            2     2      2      2650      50      53     1324.3    0.49973    0.28834    0.57699     0.00046692    0.99985
    mat_2_boolean    3     3      2      2650      50      53       1350    0.50943    0.50001    0.98149              0          1

xxx TABLE:mat_1 xxxxxxxxxxxxxxxxxx
            c1         c2         c3         c4   
          _______    _______    _______    _______

    r1    0.32333    0.62442    0.01062    0.53815
    r3    0.79378    0.75889    0.11104    0.55157

xxx TABLE:mat_2 xxxxxxxxxxxxxxxxxx
             c1         c2         c52        c53  
           _______    _______    _______    _______

    r1     0.72837    0.20976    0.74583    0.22321
    r50    0.52812      0.545    0.49521    0.29826

xxx TABLE:mat_2_boolean xxxxxxxxxxxxxxxxxx
            c1       c2       c52      c53 
           _____    _____    _____    _____

    r1     false    true     true     true 
    r50    true     false    false    true