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Cell Arrays

Cell Arrays. Definition Creating Cell Arrays Referencing Cell Arrays Augmenting Cell Arrays Use of Cell Arrays. Data Types. Recall the workspace frame in MATLAB. Currently, 3 types of data have been seen. They are called: This lecture teaches a new data type called cell arrays.

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Cell Arrays

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  1. Cell Arrays Definition Creating Cell Arrays Referencing Cell Arrays Augmenting Cell Arrays Use of Cell Arrays

  2. Data Types • Recall the workspace frame in MATLAB. Currently, 3 types of data have been seen. They are called: • This lecture teaches a new data type called cell arrays char (strings) double (float) or int8, int16… logical

  3. 1. Cell Arrays - Definition • A data type that stores values of different types in indexed data containers called cells. • A cell can hold any data type- string, integer, float, or even another cell array… Simply It is an ARRAY of CELLS

  4. Quick Vocabulary Parentheses ( ) Brackets [ ] Braces { }

  5. 2. Creating Cell Arrays • Cell arrays can be created by using the { } braces • Separate cells in a row with commas (or spaces); separate rows with semi-colons. • Likes arrays, cell arrays need to be rectangular Curly braces – not brackets!

  6. 2. Creating Cell Arrays, cont. • Visualize them using cellplot()!

  7. 2. Creating Cell Arrays, cont. • Cell arrays can be of higher dimensions a 2 by 2 cell array

  8. Question Is this cell array, A = {1:4; 2:3}, rectangular? Answer: Yes, it is rectangular. Its size is 2 by 1.

  9. 3. Referencing Cell Arrays • Like with arrays, row and column indices are used • Unlike arrays, there are 2 ways to reference a cell array, depending on the task: • Get the entire cell as a whole, use (). - to move the container - to extract/copy/replace the container - to delete the container • Get the content inside the cell, use {}. - To change/empty its content - To display/print its content

  10. 3. Referencing Cell Arrays Parentheses property of the cell is shown, not content

  11. 3. Referencing Cell Arrays A 1x1 Cell Array containing a 1x4 array of doubles Curly Braces Content in the cell

  12. 3. Referencing Cell Arrays >> x = cellmat(1,1); >> y = x+5; Undefined function 'plus' for input arguments of type 'cell'.

  13. 3. Referencing Cell Arrays >> x = cellmat(1,1); >> y = x+5; ✗ >> x = cellmat{1,1}; >> y = x+5; ✔ y = 6 8 10 12

  14. 3. Referencing Cell Arrays Cell indexing: ( ) Content indexing: { }

  15. 4. Cell Arrays – Augmenting • Add the string 'def'. ??

  16. 4. Cell Arrays – Augmenting • { } are not used to augment. They are used to create new cell-arrays from scratch. - ‘def’ is added OUTSIDE of the cell-array C NOT what we wanted...

  17. 4. Cell Arrays – Augmenting • Instead, augment using square brackets

  18. 4. Cell Arrays – Augmenting • Add a row? Of course! • Like with arrays, use ; to add a new row.

  19. 5. More Operations… • Given C = {1, 2, ‘Joe’, 3.4, ‘def’} • Delete the 5th cell • Emptying contents of the 2nd cell • Replace 3rd cell with the cell of content ‘sam’; • Change content of 1st cell to the number 8 • Transpose, ‘, still works. C(5) = [] C{2} = [] C(3)= cellstr(‘sam’) OR C{3} = ‘sam’ C{1}= 8

  20. 6. Why Cell Arrays? • To store information of mixed data types • To store arrays of different sizes • To store strings of different length Example: • Names and grades? • Daily temperature of 12 months. 28 days, 30 days or 31 days? • Names of different length?

  21. Introduction to File I/OHigh-Level Functions Data files “High level” File I/O dlmread() xlsread()

  22. 1.1. File Applications Databases Logs – attendance, events, history Journals / Diaries Address books Sensor data Documents Almost every program uses files! Shuttle ECO sensor Automotive O2 sensor

  23. 1.2 Data Files • Data files can be different types and with different data organization

  24. 1.2 Data Files, cont. • Flagler Property Sales

  25. 1.2 Data Files, cont. • Grade

  26. 1.3 File I/O • There are basically three operation modes on files: • Read from: to grab/load data from a file and pass them to variables (INPUT) • Write to: to store/save data to a file from the file beginning (OUTPUT) • Append to: to add/save data to the end of a file (OUTPUT) • In general, 3 steps are always involved: • MATLAB opens the file; • MATLAB reads from, writes to, or appends to the file; • MATLAB close the file;

  27. 2.1 High-level File I/O • A file I/O function is considered HIGH-LEVEL if in ONE SINGLE COMMAND, it • Opens the file • Reads from the file, writes to the file, or appends to the file • Closes the file • “Low-level” I/O functions are to be introduced next week. Those will require more lines of code!

  28. 2.2 Can High-level be used? • To decide if using a high level function is possible, evaluate the following: • What type of file is it? (Excel, text, jpg..) • Recognize the data types (all numerical? all strings? Or combination of both) • Find the organization overall (data in rows, or data in columns, data placed all over the place…) • Recognize the delimiters: What makes it obvious it is a new column? What makes it obvious it is a new row? • space, tabs, comma, new lines, dash, colon, /, any specific symbol!

  29. 2.2 Can High-level Be Used?

  30. 3.1 ASCII Delimited Files • “Neatly Organized” • Rows and Columns are “identifiable” • Always the same patterns per line • There is no mixes of delimiters (commas, spaces, tabs, dash.. ) A delimiter is a sequence of one or more characters used to specify the boundary between separate, independent regions in plain text or other data streams

  31. Questions • Can these files be read using dlmread()?

  32. The data files (.txt, .xls, .xlsx, .m) should all be in the same directoryfor function calls to work!

  33. 3.2 dlmread() Syntax M = dlmread(filename); Reads numeric data from the ASCII delimited filefilename, and returns the data in output matrix M. The input filename is a string enclosed in single quotes. The delimiter is inferredfrom the formatting of the file. M = dlmread(filename, delimiter); Reads numeric data from the ASCII delimited file filename using the delimiter delimiter such as '-',':'and etc. (Use '\t'to specify a tab.) • >>doc dlmread <enter> open further possible syntaxes

  34. 3.3 Specific Delimiters, cont. • Delimiter: other than the defaults Specify the delimiter as the 2nd argument.

  35. 3.3 Using Delimiters, cont. • BAD… Mix of delimiters. Two delimiters (spaces and colons) in the file. MATLAB is lost. >> “low-level” functions are necessary for this

  36. Example1: airfoils • The NACA airfoils are airfoils shapes for aircraft wings. Load the data (x and y coordinates) for this model of NACA airfoil and plot it. www.angelfire.com

  37. Example1: airfoils clc clear %load the numerical data file %slice the array to extract x and y coordinates % plot the airfoil and format the plot plot(x,y) title('Naca2410') %add plot title axis equal %make axis equal in scale grid on %put the grid on Remember those quotes and the extension. array = dlmread('naca2410.dat'); x = array(:,1); y = array(:,2);

  38. without files… clc clear %prompt how many sets of x-y coordinates sets = input('How many sets (>5)? '); while sets<=5 || mod(sets,1)~=0 %decimals sets = input('ERROR: How many sets (>5)? '); end %prompt user for x/y coordinates for k = 1:sets %ask for x fprintf('x%d: ',k); x(k) = input(''); %ask for y fprintf('y%d: ',k); y(k) = input(''); fprintf('\n'); end % plot the airfoil and format the plot plot(x,y) title('Naca2410') %add plot title axis equal%make axis equal in scale grid on%put the grid on

  39. 2. xlsread()

  40. 2. xlsread(), Syntax Syntax [num,txt,raw] = xlsread(filename) reads data from the first worksheet; [num,txt,raw] = xlsread(filename, sheet) reads the specified worksheet. Numeric data in the spreadsheet are returned to array num. Optional: Textual information in the spreadsheet is returned to cell array txt, and the unprocessed data (numbers and text) to cell array raw. filename is a string. If hardcoded, it must be in single quotes.

  41. Example: xlsread() • Load the grade data from a spreadsheet and find the name of the student who has the highest grade. >>[age_grade, text, raw] =xlsread('grades.xlsx’)

  42. Example: xlsread() >> [age_grade, myText, raw] = xlsread('grades.xlsx') age_grade = 19 78 22 83 98 99 21 56 23 89 19 51 myText= 'Name' 'Age' 'Grade' 'Fred' '' '' 'joe' '' '' 'SaLLy’ '' '' 'CharliE' '' '' 'mary' '' '' 'Ann' '' '' raw = 'Name' 'Age' 'Grade' 'Fred' [ 19] [ 78] 'joe' [ 22] [ 83] 'SaLLy' [ 98] [ 99] 'CharliE' [ 21] [ 56] 'mary' [ 23] [ 89] 'Ann' [ 19] [ 51] 6X2 double 7X3 cell 42 7X3 cell

  43. Example: xlsread() • variable names don’t matter to MATLAB. It respects its order. >> [myText, age_grade, raw] = xlsread('grades.xlsx‘) myText= 19 78 22 83 98 99 21 56 23 89 19 51 age_grade = 'Name' 'Age' 'Grade' 'Fred' '' '' 'joe' '' '' 'SaLLy’ '' '' 'CharliE' '' '' 'mary' '' '' 'Ann' '' '' raw = 'Name' 'Age' 'Grade' 'Fred' [ 19] [ 78] 'joe' [ 22] [ 83] 'SaLLy' [ 98] [ 99] 'CharliE' [ 21] [ 56] 'mary' [ 23] [ 89] 'Ann' [ 19] [ 51] 43

  44. Example: xlsread() • Now find student who has the highest grade. age_grade = 19 78 22 83 98 99 21 56 23 89 19 51 text= 'Name' 'Age' 'Grade' 'Fred' '' '' 'joe' '' '' 'SaLLy’ '' '' 'CharliE' '' '' 'mary' '' '' 'Ann' '' '' raw = 'Name' 'Age' 'Grade' 'Fred' [ 19] [ 78] 'joe' [ 22] [ 83] 'SaLLy' [ 98] [ 99] 'CharliE' [ 21] [ 56] 'mary' [ 23] [ 89] 'Ann' [ 19] [ 51]

  45. Example: xlsread() • Find the student who has the highest grade %load data from file [age_grade, text] = xlsread('grades.xlsx' ); %find the position of the maximum grade [trash row]= max(age_grade(:,2) ); %find whose name is associated with that position name = text{row+1,1} ; %+1 due to headers fprintf('%s got the highest grade\n' , name) • NOTE: raw would be useless here. We simply did not collect it…

  46. xlsread(), cont. • OMIT collecting the 2nd and 3rd return variables if only numerical values are of interest! age_grade = xlsread(‘grades.xlsx’); • If a project needs all the data together, collect the 1st and 2nd return values into a dummy variable. [trash trash data] = xlsread(‘grades.xlsx’); or since MATLAB R2009b, use tilde (~): [~, ~, data] = xlsread(‘grades.xlsx’); • If there happens to be ‘holes’ in the spreadsheet, MATLAB fills it with a NaN value (not a number). The function isnan()can help determine where those ‘holes’ are.

  47. Testing habits • Though the file may contain 1,000,000 lines, and ONE command does the job, it is best to test the analysis with a smaller file: • create a copy of the original file, where only 5-10 lines are present.

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