你好。 我是jsl的新手，并且有一种感觉，我正在做很多很长很难的事情，并且可能内置函数执行与我的代码相同的操作。 我编写的代码需要2个数据表并将它们转换为1个.mdf文件如果您知道实现下面任何代码段的更简单和/或更健壮的方法，请告诉我！示例数据已上传到此页面。 谢谢。
//************************************************************************************************************************************************************************************************************************************
//
// AUTHOR: Adam Jones DATE: 7 July 2019
//
// Edits: 15 July 2019, Adam Jones. Removed IdVd data from output.
// 16 July 2019, Adam Jones. Added functionality of allowing user to leave data windows on screen after script is finished or to clear all windows after script has finished
// Added ability to handle input files containing differnt processes or device numbers. Script saves output files as normal, but shows error window, leaving user to verify validity of output data
// xx July 2019, Adam Jones. Added functionality of allowing user to set lambda for each capacitor and/or iv spline.
//
// DESCRIPTION: Converts CV and IV data from 2 independent .jmp or .csv files into 1 .mdf file, for use in ADS/AWR.
//
// INPUTS: CV data (.jmp or .csv, must contain columns: serial_num, v_dut_volt, c_type, process, reticle )
// IV data (.jmp or .csv, must contain columns: serial_num, vg_volt, , process, reticle )
// Directory for output data
//
// OUTPUTS: 3 .mdf files, containing CV, IV and CV+IV data, seperated into blocks, based on curve (Cdg-V, Cgg-V, Cds-V, Id-Vg), process and device number
// 1 .csv file, for use by an ADS batch simulatior (CSV_list Sweep Module)
// WARNING: Output will overide any files in the output directory with the same name
//
// FAIL CASES: 1) Input file does not contain correct column names
// 2) Cell of columns named "process", "c_type", "sn", or "device_num" has been left blank
// 3) File contains IdVd data as well as IdVg data
// 4) Both input files contain different processes, sn's, device numbers
// 5) Incorrect user input
//
//************************************************************************************************************************************************************************************************************************************
// User input
DataIVname = Pick File( // Prompt user to choose a file and return a string of the filepath
"Select DCIV Data", // prompt message
"", // initial directory
{"All Files|*", "Excel Files|csv", "JMP Files|jmp;jsl;jrn"}, // file filter list
1, // intially selected item
0, // doesn’t prompt the user to save the file
"" // file that is selected by default
);
DataCV = Open( // Open file and assign it to variable
Pick File( // Prompt user to choose a file and return a string of the filepath
"Select CV Data", // prompt message
"", // initial directory
{"All Files|*", "Excel Files|csv", "JMP Files|jmp;jsl;jrn"}, // file filter list
1, // intially selected item
0, // doesn’t prompt the user to save the file
"" // file that is selected by default
)
);
prefilepath = Munger( Pick Directory( "Select Output Directory" ), 1, "/", "" ); // Prompt user to chose folder for data storage. Assign it to variable
filepath = Convert File Path( prefilepath, Windows ); // Convert prefilepath variable into a string, containing the filepath, in windows format
New Window( "Would you like to visually inspect data and lines of best fit for garbage or corruption?",
<< modal,
Text Box ("Would you like to visually inspect data and lines of best fit for garbage or corruption?"),
Button Box( "Yes" , inspect = 0 ),
Button Box( "No" , inspect = 1 )
);
//************************************************************************************************************************************************************************************************************************************
// Generate and save CV splines (curves of best fit) by combinations of :c_type and :process
Summarize( DataCV, processArrayCV = By( :process ) ); // Create array of manufacturing processes
Summarize( DataCV, deviceNumArrayCV = By( :device_num ) );
Summarize( DataCV, ctypeArray = By( :c_type ) ); // Create array of capacitance types
For( n = 1, n <= Length( ctypeArray ), n++, // Loop through ctypeArray
For( o = 1, o <= Length( deviceNumArrayCV ), o++, // Loop through deviceNumArrayCV
For( m = 1, m <= Length( processArrayCV ), m++, // Loop through processArrayCV
temp = Substitute( // Return Expr(), after substitutions have taken place
Expr( // Define expression containing variables to be substituted
biv = Bivariate( // Generate line of best fit
Y( :c_mm_deembed_pf ), // Set dependent variable
X( :v_dut_volt ), // Set independent variable
Where( :c_type == __ctype__ & :process == __process__ & :device_num == __deviceNum__ ), // Genearte lines based on 2D array: __ctype__ by __process__
Fit Spline( /*__lambda__*/ 0.01, standardized, {save predicteds} ) // Define type of fit (spline), define lambda, save predicted values
)
),
Expr( __process__ ), processArrayCV[m], // Substitute value of processArrayCV into Bivariate()
Expr( __deviceNum__ ), deviceNumArrayCV[o],
Expr( __ctype__ ), ctypeArray[n], // Substitute value of ctypeArray into Bivariate()
/*Expr( __lambda__ ), if(ctypeArray[n] == "Cgg", // If ctype is Cgg, set lambda to 0.001, othwerwise set to 10. lambda = 10 reduces noise but lambda <= 0.01 is needed to capture discontinuities in Cgg curves
0.001, 0.1
); */
);
Eval( temp );
)
)
);
//************************************************************************************************************************************************************************************************************************************
// Create new CV table, containing only useful columns
CVdata = (Data Table( DataCV ) << Tabulate(
Add Table(
Column Table( Analysis Columns( :Spline Predictor for c_mm_deembed_pf Where, /*:Spline Predictor for c_mm_deembed_pf Where 2*/ ) ), // Dependent variable goes here. 1 to 1 relationship with leaves of categorical tree
Row Table( Grouping Columns( :serial_num, :process, :device_num, :c_type, :v_dut_volt ) ) // Defines categorical tree, growing left to right, from :serial_num (trunk) to :v_dut_volt (leaves, independent variable)
)
)) << Make Into Data Table;
//************************************************************************************************************************************************************************************************************************************
// Throw out redundant CV data
CVdata << AddRows( 1 ); // Add empty last row so while loop knows when it's reached the end
q = 0; // End of data table flag
proc = "new"; // Check against every row of :process
dn = "new";
sn = 0;
i = 1; // Row number
Print( "flag1" );
while( q == 0, // Delete redundant :process x :c_type combinations
If( proc != :process[i] | dn != :device_num[i], // (1) If new process or device number has been detected, reset proc, sn and dn
proc = :process[i];
sn = :serial_num[i];
dn = :device_num[i];
i += 1;
);
If( proc == :process[i] & sn == :serial_num[i] & dn == :device_num[i], // (2) Iterate through all rows of the new :process x :device_num combination
i += 1
);
If( proc == :process[i] & dn == :device_num[i] & sn != :serial_num[i], // (3) If new sn has been encountered, with the same process and device num, delete row. Keep deleting until new process or device num has been detected (1)
CVdata << DeleteRows( i )
);
If( :process[i] == "", // (4) If end of table has been reached, exit loop
q = 1
)
);
CVdata << Delete Rows( i ); // Delete empty last row
//************************************************************************************************************************************************************************************************************************************
// Add blocks, seperated by VARs, BEGINNINGs and ENDs, for use by ADS/AWR
Column( "v_dut_volt" ) << set name( "independent" ); // Change name of column "v_dut_volt" to "Independent"
Column( "independent" ) << data type( character ); // Change column type from numerical to character so that later on, VARs, used for ADS/AWR indexing, can be inserted into this column
Column( "Sum(Spline Predictor for c_mm_deembed_pf Where)" ) << set name( "spline" ); // change name of column "Sum(Spline Predictor for c_mm_deembed_pf Where)" to "Spline"
Column( "spline" ) << data type( character ); // Change column type from numerical to character so that later on, VARs, used for ADS/AWR indexing, can be inserted into this column
batchList = {};
j = 0; // First block flag
cap = "new"; // Check against every row of :c_type
For( k = 1, k <= N Rows( CVdata ), k++, // Add VARs for ADS indexing
If( cap != :c_type[k] & j == 1, // Enter this if loop every time except for first time, where "END" is not required
CVdata << Add Rows( 4, k - 1 ); // Insert 6 new rows, above newly detected capacitor type
cap = :c_type[k + 4]; // set variable to newly detected capacitor type
proc = :process[k + 4]; // set variable to process of row containing new capacitor type
dn = :device_num[k + 4];
:independent[k] = "END"; // Mark end of a block
:independent[k + 1] = "VAR Index(2) = " || Char( proc ) || "/" || Char( dn ) || "/" || Char( cap ); // Index of .mdf block, for use by ADS/AWR
:independent[k + 2] = "BEGIN"; // Mark beginning of a block
:independent[k + 3] = "% ind(1)"; // Lable first column as independent variable, for use by ADS/AWR
:Spline[k + 3] = "dep(1)"; // Lable second column as dependent variable, for use by ADS/AWR
k += 3 // Move k past newly created rows
;
);
If( cap != :c_type[k] & j == 0, // Enter this if loop only once, at the beginning of the file, where "END"" is not required
CVdata << Add Rows( 3, k - 1 ); // Insert 5 new rows, above newly detected capacitor type
cap = :c_type[k + 3]; // Set variable to newld detected capacitor type
proc = :process[k + 3]; // Set variable to process of newly detected capacitor
dn = :device_num[k + 3];
:independent[k] = "VAR Index(2) = " || Char( proc ) || "/" || Char( dn ) || "/" || Char( cap ); // Index of .mdf block, for use by ADS/AWR
:independent[k + 1] = "BEGIN"; // Mark beginning of block
:independent[k + 2] = "% ind(1)"; // Lable first column as independent variable, for use by ADS/AWR
:Spline[k + 2] = "dep(1)"; // Lable second column as dependent variable, for use by ADS/AWR
k += 2; // Move k past newly created rows
j = 1 // Set flag to 1, so END will be included at end of blocks
;
);
);
CVdata << add rows( {:independent = "END"} ); // Insert "END" at very end of file
//************************************************************************************************************************************************************************************************************************************
// Clean and save CV data table. Clean windows
CVdata << delete columns( "c_type", "serial_num", "process", "device_num" ); // Delete all rows except for ind(1) and dep(1)
CVdata << Save As( Filepath || "CV_Output.csv" ); // Save as .csv file for concatenation to IV file
if(inspect == 1,
Close All( Data Tables, NoSave ) // Close pop-up windows
);
//************************************************************************************************************************************************************************************************************************************
// Generate and save IV splines (curves of best fit) by combinations of :process and :reticle_num
DataIV = Open( DataIVname ); // Open file containing IV data
Summarize( DataIV, processArrayIV = By( :process ) ); // Create array
Summarize( DataIV, deviceNumArrayIV = By( :device_num ) );
Print( "flag2" );
For( m = 1, m <= Length( processArrayIV ), m++, // Generates and saves all IdVg splines
For( n = 1, n <= Length( deviceNumArrayIV ), n++,
temp = Substitute(
Expr(
biv = Bivariate(
Y( :id_amp ),
X( :vg_volt ),
Where( :process == __process__ & :device_num == __deviceNum__ & :iv_type == "idvg" ),
Fit Spline( 0.001, standardized, {save predicteds} )
)
),
Expr( __process__ ), processArrayIV[m],
Expr( __deviceNum__ ), deviceNumArrayIV[n]
);
Eval( temp );
)
);
//************************************************************************************************************************************************************************************************************************************
// Create new IV table, containing only useful columns
IVdata = (Data Table( DataIV ) << Tabulate( // Create new table
Add Table(
Column Table( Analysis Columns( :Spline Predictor for id_amp Where ) ),
Row Table( Grouping Columns( :serial_num, :process, :device_num, :vg_volt, :iv_type ) )
)
)) << Make Into Data Table;
//************************************************************************************************************************************************************************************************************************************
// Throw out redundant IV data
IVdata << AddRows( 1 ); // Add an empty last row so while loop knows when it's at the end
q = 0;
dn = "new";
proc = "new";
sn = 0;
i = 1;
Print( "flag4" );
while( q == 0, // Delete redundant splines (:process x :reticle_num combinations)
If( proc != :process[i] | dn != :device_num[i] & :iv_type[i] == "idvg",
proc = :process[i];
dn = :device_num[i];
sn = :serial_num[i];
i += 1;
);
If( proc == :process[i] & dn == :device_num[i] & sn == :serial_num[i] & :iv_type[i] == "idvg",
i += 1
);
If( proc == :process[i] & dn == :device_num[i] & sn != :serial_num[i] | :iv_type[i] == "idvd",
IVdata << DeleteRows( i )
);
If( :device_num[i] == "",
q = 1
);
);
IVdata << Delete Rows( i ); // Delete empty last row
//************************************************************************************************************************************************************************************************************************************
// Add blocks, seperated by VARs, BEGINNINGs and ENDs, for use by ADS/AWR
Column( "vg_volt" ) << set name( "independent" );
Column( "independent" ) << data type( character );
Column( "Sum(Spline Predictor for id_amp Where)" ) << set name( "spline" );
Column( "spline" ) << data type( character );
j = 0;
dn = "new";
For( k = 1, k <= N Rows( IVdata ), k++, // Add VARs for ADS indexing
If( dn != :device_num[k] & j == 1,
IVdata << Add Rows( 4, k - 1 );
dn = :device_num[k + 4];
proc = :process[k + 4];
:independent[k] = "END";
:independent[k + 1] = "VAR Index(2) = " || Char( proc ) || "/" || Char( dn ) || "/IV"; // Index of .mdf block, for use by ADS/AWR
:independent[k + 2] = "BEGIN";
:independent[k + 3] = "% ind(1)";
:Spline[k + 3] = "dep(1)";
k += 3;
);
If( dn != :device_num[k] & j == 0,
IVdata << Add Rows( 3, k - 1 );
dn = :device_num[k + 3];
proc = :process[k + 3];
:independent[k] = "VAR Index(2) = " || Char( proc ) || "/" || Char( dn ) || "/IV"; // Index of .mdf block, for use by ADS/AWR
:independent[k + 1] = "BEGIN";
:independent[k + 2] = "% ind(1)";
:Spline[k + 2] = "dep(1)";
k += 2;
j = 1;
);
);
IVdata << add rows( {:independent = "END"} );
//************************************************************************************************************************************************************************************************************************************
// Clean and save IV data table
IVdata << delete columns( "device_num", "serial_num", "process", "iv_type" ); // Delete all rows except for ind(1) and dep(1)
IVdata << Save As( Filepath || "IV_Output.csv" ); // Save as .csv
if(inspect == 1,
Close All( Data Tables, NoSave ) // Close pop-up windows
);
//************************************************************************************************************************************************************************************************************************************
// Concatinate IV and CV data
Fulltable = New Table( "Combined Data table" ); // Create new table
IVtable = Open( Filepath || "IV_Output.csv" ); // Open IV data
CVtable = Open( Filepath || "CV_Output.csv" ); // Open CV data
Fulltable << Concatenate( Data Table( IVtable ), append to first table ); // Concatenate IV data to empty table
Fulltable << Concatenate( Data Table( CVtable ), append to first table ); // Concatenate CV data to IV data
FullTable << delete columns( "Column 1" ); // Throw out garbage column
//************************************************************************************************************************************************************************************************************************************
// Save concatinated data table in .MDF format
xptPref = Get Preferences( Export Settings );
Preferences(
ExportSettings( // .mdf format
End Of Line( CRLF ), // End of line marked by carrage return left field
End Of Field( Tab ), // Tab delineated
Export Table Headers( 0 ) // Do not include table headers
)
);
Fulltable << Save as( Filepath || "CV-IV_Output.mdf", "text" ); // Save combined IV and CV data as a .mdf file
//************************************************************************************************************************************************************************************************************************************
// Check that CV file contains exact same processes and device numbers as IV data
If( Length( processArrayCV ) != Length( processArrayIV ),
New Window( "Error",
<<MODAL></MODAL>
看起来很好的注释代码，不难维护。我并没有真正回答你提出的问题，因为我没有看到任何错误。
肤浅的想法：
Close All( Data Tables, NoSave )
对于对开放数据表进行重要修改的人来说，最后可能会有些意外。您可以将打开的表保存在列表中，然后只关闭您创建的表。
设置prefs时，您捕获了原始pref值，但没有使用捕获的值来恢复它们：
xptPref = Get Preferences( Export Settings );
我想你可以在保存之后在xptPref中评估表达式以进行恢复。
如果打开了多个表，则应使用带有列名的表变量;这对未来的维护者来说可能是一个很大的帮助：
If( proc != dtA:process[i] | dn != dtA:device_num[i],
如果使用当前表并且多个表具有process或device_num列，则事情会变得非常混乱。如果你能使用比我的dtA更好的名字，那也会有所帮助。
inspect变量的模态对话框应该处理取消的情况;如果您“X”对话框关闭而不是是/否则检查变量未定义。您应该在模态窗口之前将inspect设置为-1。此外，用于检查的0/1逻辑似乎与其名称相反。
感谢分享;我喜欢你使用“text”文件的制表符分隔/无标题输出来制作你需要的文件的方式。
