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1. rec_surl I EGER rec_sur2 I EGER rec_sur3 INTEGER rec_sur4 I EGER rec_sur5 INTEGER rec_sur6 INTEGER rec_sur7 I EGER rec_sur8 INTEGER rec_sur9 INTEGER rec_surl0 INTEGER rec_surll INTEGER rec_surl2 INTEGER rec_surl3 INTEGER rec_surl4 INTEGER rec_surl5 INTEGER rec_surl6 INTEGER rec surl7 INTEGER rec surl18 INTEGER rec surl19 INTEGER rec sur20 INTEGER rec sur21 INTEGER rec sur22 INTEGER rec sur23 INTEGER rec sur24 INTEGER rec sur25 INTEGER 2 9 1 Same as 2 9 but with unique plates 2 9 2 Same as 2 9 but with plates with just one spot removed 2 40 Table species spots 2 in the local database containing the SETL records for the second selection of species and locations This table does not contain the complete records but just the plate ID and the 25 record surfaces SQLite query CREATE TABLE species spots 2 id INTEGER PRIMARY KEY rec pla id INTEGER rec suri I EGER rec sur2 I EGER rec sur3 INTEGER rec sur4 I EGER rec sur5 INTEGER rec sur6 INTEGER rec sur 7 I EGER rec sur8 INTEGER rec sur9 INTEGER rec surlO0 INTEGER rec surll INTEGER rec surl12 INTEGER
2. 2 2 User Manual 11 SETLyze Documentation Release 1 0 1 Analysis Spot preference me Q0 w t e Locations Selection Below are the available locations Please select the locations from which you want to select species By default the data is loaded from the remote SETL database To load data from a different data source click the Change Data Source button below Tip Hold Ctrl or Shift to select multiple items To select all items press Ctrl A Locations v Aquadome Grevelingen Bommenede harbor boat Grevelingen Bommenede harbor Grevelingen Breskens harbor Breskens on floating dock NOT SETL Colijnsplaat floating dock Oosterschelde Colijnsplaat jetty Qosterschelde Den Helder port Eemshaven port Hompelvoet Grevelingen Ijmuiden Change Data Source Back Continue Fig 2 9 Locations Selection dialog 12 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Making a selection Just click on one of the locations to select it To select multiple locations hold Ctrl or Shift while selecting To select all locations at once click on a location and press Ctrl A Species Selection dialog Analysis Spot preference a G amp t 9 Species Selection Below are the available species for the selected location s Please selectthe species to be included for the analysis Tip Hold Ctrl or Shift to select multiple items To select all items
3. English text retrieval Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents This module is for storing and retrieving messages used in SETLyze The purpose is to have a standard place for storing these messages This was basically meant for convenience so the developer doesn t have to browse through SETLyze s code base just to change a sentence This module wasn t created for adding multi language support though it can be easily expanded to do so setlyze locale text key args Return the text string from the ENGLISH dictionary where key is key A simple example gt gt gt import setlyze locale gt gt gt setlyze locale text analysis spot preference descr Determine if a species has preference for a specific area on SETL plates Substitution is also supported gt gt gt import setlyze locale gt gt gt setlyze locale text dummy windy with a slight chance of rain And tomorrow s forecast is windy with a slight chance of rain setlyze report Generate analysis reports Author Serrano Pereira Release 1 0 1 Date July 17 2015 46 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Module Contents setlyze std Standard functions and classes Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents Analysis Modules The modules descr
4. Intra specific spot distances Spot Distance Probability 1 40 300 1 41 32 300 2 30 300 2 24 48 300 2 83 18 300 3 20 300 3 16 32 300 3 61 24 300 4 10 300 4 12 16 300 4 24 8 300 4 47 12 300 5 8 300 5 66 2 300 Inter specific spot distances Spot Distance Probability 0 25 625 1 80 625 1 41 64 625 2 60 625 2 24 96 625 2 83 36 625 3 40 625 3 16 64 625 3 61 48 625 4 20 625 4 12 32 625 4 24 16 625 4 47 24 625 5 16 625 5 66 4 625 Depending on the analysis the records matching the species selection are first grouped by positive spots number analysis Attraction within Species or by ratios group analysis Attraction between Species See section Record Grouping Each row for the results of the Chi squared tests contains the results of a single test on a spots ratios group Each row can have the following elements Positive Spots A number representing the number of positive spots For this test only records matching that number of positive spots were used Ratios Group A number representing the ratios group For this test only records grouped in that ratios group were used n plates The number of plates that match the number of positive spots n distances The number of spot distances derived from the records matching the positive spots number P value The P value for the test
5. The Python on Windows FAQ explains how to do this Search for PATH environment variable on that page Ctrl F type PATH environment variable hit Enter This should create a new folder called src dist Open this folder in Windows Explorer You should now see a whole bunch of files including set lyze exe Go ahead and see if set lyze exe runs Double clicking set lyze exe should open up SETLyze s main win dow You might notice something different though The dialogs look really ugly Remember that this Windows executable doesn t need to have Python etc installed The executable is now actually using its own copy of Python python27 d11 GTK 1ibgtk win32 2 0 0 d11 and all the other stuff it requires Py2exe has automat ically collected all the files required to run SETLyze and put them in one folder But the GTK Runtime requires some extra files to make the GTK dialogs look nice py2exe doesn t include these files automatically So we need to manually copy these files to the src di st folder First figure out where the PyGTK installer installed the GTK Runtime files Open a Python interpreter and enter these commands gt gt gt import sys gt gt gt import gtk module gtk from c Python27 lib site package gt gt gt m sys modules gtk gt gt gt print m path 0 co Python27 lib site packages gtk 2 0 gtk The example output tells us that the runtime files can be found i
6. Plate area D Plate area A B Plate area B C Plate area A B C Plate area B C D oN OA Nn A For each group the number of positive spots for all plates and that specific plate area are calculated These make up the observed values Record grouping by number of positive spots This type of grouping is done in the case of calculated spot distances for a single species or multiple species grouped together on SETL plates analysis Attraction within Species A record has a maximum of 25 positive spots so this results in a maximum of 25 record groups Group 1 contains records with just one positive spot group 2 contains records with two positive spots et cetera Records of group 1 and 25 are left out however Group is skipped because it is not possible to calculate spot distances for records with just one positive spot And group 25 is excluded because a significance test on records of this group will always result in a p value of 1 This makes sense because both the observed and expected distances are based on records with 25 positive spots which is a full SETL plate As a result the observed and expected spot distances will be exactly the same 24 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 The test is also performed on a group with number 24 Of course there is no such thing as records with minus 24 positive spots Actually the minus sign should be read as up to So this test is also pe
7. rec surl13 INTEGER rec surl4 INTEGER 38 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 rec_surl5 INTEGER rec_surl6 INTEGER rec_surl7 INTEGER rec_surl8 INTEGER rec_surl9 INTEGER rec_sur20 INTEGER rec_sur21 INTEGER rec_sur22 I EGER rec_sur23 INTEGER rec_sur24 INTEGER rec_sur25 INTEGER 2 10 1 Same as 2 0 but with unique plates 2 10 2 Same as 2 0 but with plates with just one spot removed 2 12 Table spot_distances_observed in the local database containing the observed spot distances Contains the spot distances for the records in 2 9 if created by calculate_distances_intra If the table is created by calculate_distances_inter the table contains the distances between spots in 2 9 and 2 0 SQLite query CREATE TABLE spot_distances_observed id INTEGER PRIMARY KEY rec_pla_id INTEGER distance REAL 2 43 Table spot distances expectedin the local database Has the same design as 2 2 but contains ran dom generated spot distances instead These random generated spot distances will serve as the expected spot distances SQLite query CREATE TABLE spot distances expected id INTEGER PRIMARY KEY rec pla id INTEGER distance REAL 2 14 Table info in
8. rec_sur6 BOOLEAN rec_sur7 BOOLEAN rec_sur8 BOOLEAN rec_sur9 BOOLEAN rec_surl0 BOOLEAN rec_surll BOOLEAN rec_surl2 BOOLEAN rec_surl13 BOOLEAN rec_surl4 BOOLEAN rec_surl5 BOOLEAN rec_surl6 BOOLEAN rec_surl7 BOOLEAN rec_surl8 BOOLEAN rec_surl9 BOOLEAN rec_sur20 BOOLEAN rec sur21 BOOLEAN rec sur22 BOOLEAN rec sur23 BOOLEAN rec sur24 BOOLEAN rec sur25 BOOLEAN rec 1st BOOLEAN rec 2nd BOOLEAN rec v BOOLEAN rec photo nrs VARCHAR 100 rec remarks VARCHAR 100 CONSTRAINT rec id pk PRIMARY KEY rec ig 34 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 CONSTRAINT rec_pla_id_fk FOREIGN KEY rec_pla_id REFERENCES setl_plates pla_id ON DELETE NO ACTION ON UPDATE NO ACTION CONSTRAINT rec_spe_id_fk FOREIGN KEY rec_spe_id REFERENCES setl_species spe_id ON DELETE NO ACTION ON UPDATE NO ACTION 2 1 Table set1_species in the SETL database The SETL database can be either the MS Access database or the PostgreSQL database This table contains the SETL species records PostgreSQL query CREATE TABLE setl_species spe_id SERIAL spe_name_venacular VARCHAR 100 UNIQUE spe_name_latin VARCHAR 100 NOT NULL UNIQUE spe_invasive_in_nl BOOLEAN spe_description VARCHAR 300 spe_remarks VARCHAR 160 spe_picture OID CONSTRAINT spe_id_pk PRIMARY KEY
9. 2 33 The element area_totals_expected in the XML DOM report that contains the expected species totals per plate area 2 3 SETLyze Developer Guide 43 SETLyze Documentation Release 1 0 1 2 34 The element statistics_normality in the XML DOM report that contains the statistic results for the normality tests 2 35 The element statistics_significance in the XML DOM report that contains the statistic results for the significance tests 2 36 Analysis variable that contains the statistic results for the normality tests Namespace setlyze analysis attraction_intra Begin statistics normality 2 37 Analysis variable that contains the statistic results for the significance tests Namespace setlyze analysis attraction_intra Begin statistics significance 2 38 The element analysis in the XML DOM report that contains the name of the analysis 2 39 Table plate_spot_totals in the local database for the number of positive spots for each plate ID in the tables 2 9 and or 2 10 Column n spots ais for the spots in 2 9 and column n spots b for the spots in 2 10 SQLite query CREATE TABLE plate_spot_totals pla_id INTEGER PRIMARY KEY n_spots_a INTEGER n_spots_b INTEGER 2 40 A XML file containing all data elements from 2 17 2 41 Table plate area totals observedin the local SQLite database This table contains the number of positive
10. lt selection 1 gt and lt selection 2 gt are lists of integers representing location IDs These IDs are the same as the IDs in column loc_id in 2 2 and 2 4 If no location selections are made yet this variable has the value None None Get the value with set lyze config ConfigManager get setlyze config cfg get locations selection slot int Set the value with set lyze config ConfigManager set setlyze config cfg set locations selection list slot int 2 7 A list lt selection 1 gt lt selection 2 gt for storing a maximum of two species selections lt selection 1 gt and lt selection 2 gt are lists of integers representing species IDs These IDs are the same as the IDs in column spe_idin 2 and 2 3 Get the value with set lyze config ConfigManager get setlyze config cfg get species selection slot int Set the value with set lyze config ConfigManager set setlyze config cfg set species selection list slot int 2 9 Table species spots 1in the local database containing the SETL records for the first selection of species and locations This table does not contain the complete records but just the plate ID and the 25 record surfaces SQLite query CREATE TABLE species spots 1 id INTEGER PRIMARY KEY rec pla id INTEGER 2 3 SETLyze Developer Guide 37 SETLyze Documentation Release 1 0 1
11. 1 20 setlyze database AccessDBGeneric make plates unique 1 22 setlyze analysis attraction intra Analysis calculate distances intra 1 23 setlyze analysis attraction intra Analysis calculate distances intra expectec 1 24 setlyze analysis attraction intra Analysis calculate significance 1 27 setlyze analysis attraction inter Analysis calculate distances inter 1 28 setlyze database AccessLocalDB 1 29 setlyze database AccessRemoteDB 1 31 setlyze database MakeLocalDB run 1 32 setlyze database MakeLocalDB insert from data files 1 33 setlyze database MakeLocalDB insert from db 1 34 1 setlyze database MakeLocalDB insert locations from csv 1 34 2 setlyze database MakeLocalDB insert locations from xls 1 35 1 setlyze database MakeLocalDB insert species from csv 1 35 2 setlyze database MakeLocalDB insert species from xls 1 36 1 setlyze database MakeLocalDB insert plates from csv 1 36 2 setlyze database MakeLocalDB insert plates from xls 1 37 1 setlyze database MakeLocalDB insert records from csv 1 37 2 setlyze database MakeLocalDB insert records from xls 1 38 setlyze database MakeLocalDB create new db 1 39 setlyze gui SelectionWindow update tree 1 41 1 setlyze database AccessLocalDB get record ids 1 42 setlyze gui SelectLocations create model 1 43 setlyze gui SelectSpecies create model 1 44 setlyze gui SelectionWindow on continue 1 45 setlyze gui SelectionWindow on back 1 48 setlyze report Rep
12. 1 70 setlyze report Report set statistics 1 72 setlyze report Report set analysis 1 73 setlyze database AccessDBGeneric fill plate spot totals table 1 74 setlyze analysis attraction inter Analysis calculate significance 1 75 setlyze database MakeLocalDB create table info 1 76 setlyze database MakeLocalDB create table localities 1 77 setlyze database MakeLocalDB create table species 1 78 setlyze database MakeLocalDB create table plates 1 79 setlyze database MakeLocalDB create table records 1 80 setlyze database AccessLocalDB create table species spots 1 1 81 setlyze database AccessLocalDB create table species spots 2 1 83 setlyze database AccessLocalDB create table spot distances observed 1 84 setlyze database AccessLocalDB create table spot distances expected 1 85 setlyze database AccessLocalDB create table plate spot totals 1 86 setlyze gui SelectAnalysis 1 87 setlyze gui SelectLocations 1 88 setlyze gui SelectSpecies 1 89 setlyze gui Report 1 90 setlyze gui LoadData 1 91 setlyze gui DefinePlateAreas 1 92 setlyze gui ProgressDialog 1 93 setlyze database get database accessor 1 94 setlyze std Sender 1 95 setlyze database AccessDBGeneric get locations 1 96 setlyze database AccessLocalDB get species 1 98 setlyze analysis spot preference Analysis calculate significance wilcoxon 1 99 setlyze analysis spot preference Analysis calculate significance chisq 1 100 setlyze analysis spot prefer
13. B were combined Summary Report Attraction within Species Species Name of the species Explanation of the columns n plates The total number of plates for the species selection The real number of plates used for each data group may be smaller Use the Save All button to see the number of plates used for each data group 2 24 2 3 positive 24 In this report the results are grouped by positive spot numbers see Record grouping by number of spots Summary Report Attraction between Species Example report Wilcoxon rank sum test Chi squared test SpecieSpecies 1 1 2 3 4 5 1 5 1 2 3 4 5 A B plates Obeli4 Obelia 12 ns ns at ns na na ns Tp at ns na na di genic p 0 83680 036 0 0G891 0000 12 16 9012 35 36 x 38 1212 7 21 chotoma p 0 2615p 0 0013p 0 0005p 0 9263 lata Obeliq Obelia 81 rp ns Ip rp rp Ip Ip Ip Ip di longis p 0 0Q8 0 loo 0q 0 0Q680 0Q0 0 009 420 6822134 342 164 862 170 0 2 96 4852 43 53 chotomaima p 0 0000p 0 00G0p 0 0000p 0 0000p 0 0000p 0 000 1 Obelig4 Obelid 39 rp ns ns ns ns rp rp Ip Ip Ip ns Ip genic longis p 0 0Q6 0 936 0 9 36960 5 5060 9 3860 0008 21 1 03 2239 4652 28 69532 105 262 8 14 X2 141 194 u sima p 0 0000p 0 0003p 0 0115p 0 0000p 0 882 Ip 0 0000 lata In this example the columns containing numbers 1 2 represent Explan
14. R version 2 12 1 This is because the RPy module must correspond to the version of R and Python you have installed The latest version of RPy at the time of writing this is version 1 0 3 which has the filename rpy 1 0 3 win32 py2 7 R 2 12 1 exe This means it requires R version 2 12 1 There 2 3 SETLyze Developer Guide 55 SETLyze Documentation Release 1 0 1 SETLyze 0 3 Setup Welcome to the SETLyze 0 3 Setup Wizard This wizard will guide you through the installation of SETLyze 0 3 It is recommended that you close all other applications before starting Setup This will make it possible to update relevant system files without having to reboot your computer Click Next to continue Fig 2 22 Screenshot of the Windows installer for SETLyze 56 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 is also RPy2 a redesign and rewrite of RPy During the development of the initial version of SETLyze it was too hard to get RPy2 working well on Windows which is why was decided to use the older but stable RPy It is possible to migrate to RPy2 and newer versions of R but this requires changes in the source code of SETLyze as RPy2 works slightly different Running and Testing SETLyze Now that you have installed all of SETLyze s pre requisites you can try to run SETLyze First obtain a copy of SETLyze s Git repository see Obtaining the source code We will use the SETLyze Git repository to build the
15. REC REC O REC R REC C REC A REC E REC sur REC surl REC sur2 REC sur3 2 202 A string variable representing the current data source Can be either set 1 database or data files Several application functions check this variable to figure out where to obtain data from The first means the PostgreSQL SETL database and the second from user selected CSV files exported from the MS Access SETL database This variable should be set whenever the data source has changed Get the value with set1yze config ConfigManager get setlyze config cfg get data source Set the value with set1yze config ConfigManager set setlyze config cfg set data source value 2 3 SETLyze Developer Guide 41 SETLyze Documentation Release 1 0 1 2 23 Table spot_distances in the local database containing all possible pre calculated spot distances SQLite query CREATE TABLE spot_distances id INTEGER PRIMARY KEY delta_x INTEGER delta_y INTEGER distance REAL Each distance in this table is coupled to a horizontal and a vertical spot difference The distances are pre calculated by setlyze std distance In other words if we have two spots and we know the horizontal difference Ax and the vertical difference Ay we can look up the corresponding distance in the spot distances table Deprecated since version 0 1 A performance test showed th
16. Windows installer Note It is important that you get the Git repository not just the code from a source package The Git repository contains a file src setlyze pyw This is the executable for SETLyze On Windows you should run it with the command python d src setlyze pyw from a DOS window so you can see any error debug messages returned by SETLyze After you have thoroughly tested SETLyze and found no problems or error messages you can continue with the next step Preparing the Distribution Folder Not all files required for creating a Windows installer are included in the Git repository for SETLyze So you need to manually copy some extra files to the folder First I will explain some of the important files and folders win32 This folder contains some files required for creating the Windows installer win32 dependencies This folder is for third party Windows installers of some of SETLyze s pre requisites that will be incorporated in SETLyze s Windows installer For SETLyze 1 0 this folder must just contain the installer for R 2 12 1 win32 setlyze_setup_modern nsi This is the NSIS script we will use to build SETLyze s Windows installer This script is a regular text file You can open it in a text editor e g Notepad or gedit This script contains all the information required for building the Windows installer src This folder contains SETLyze s main code base src build win32 exe py This script is used to build the W
17. because it s not significant Remember that these are the results of the non repeated tests The results with very low P values are pretty solid even though the expected values were calculated randomly But this cannot be said for P values that are close to the alpha level 5 by default In that case the significance result could be a coincidence This is why the results of repeated tests are included as well The Wilcoxon test was repeated a number of times And before each repeat the expected values are re calculated By default the number of repeats is set to 10 Let s have a look at the results of the repeated tests If you look at the repeat results for plate area A you ll see that out of 10 repeats 10 were found to be significant P lt 5 And out of these 10 significant results all 10 showed a preference for the area Based on this result we can almost safely say that the results we found are not a coincidence I say almost because a total of 10 repeats is very low To be even more sure you can set the number of repeats to a higher value in the Preferences dialog Conclusion The species of the genus Obelia have a strong preference for the corners area A of SETL plates and a strong rejection for the middle areas C D of SETL plates The species don t seem to have a preference for the borders area B Use Case 2 Attraction of Species intra specific Research Question Does Balanus crenatus from the location Aquadome G
18. dialog descriptions are also accessible from SETLyze s dialogs itself by clicking the Help button on a dialog Definition List This part of the user manual describes some terminology often used throughout the application and this manual Intra specific Within a single species Inter specific Between two different species Plate area The defined area on a SETL plate By default the SETL plate is divided in four plate areas A B C and D Fig 2 2 Default plate areas Plate areas can be customized during an analysis see Define Plate Areas dialog Positive spot Each record in the SETL database contains data for each of the 25 spots on a SETL plate The spots are stored as booleans meaning they can have two values 1 True means that the species was present on that spot 0 False means that the species was absent on that spot A spot is positive if the spot value is 1 or True Each record can thus have up to 25 positive spots SETL plate In the SETL project standardized PVC plates are used to detect invasive species and other fouling com munity organisms In this project 14x14 cm PVC plates are hung 1 meter below the water surface and refreshed and checked for species at least every three months 6 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Spot To analyze SETL plates photographs of the plates are taken The photographs are then analyzed on the computer by applying a 5x5 grid to the
19. it needs access to a data source containing SETL data Currently two data sources are supported Text csv or Excel xls files exported from the Microsoft Access SETL database This means 2 2 User Manual 5 SETLyze Documentation Release 1 0 1 that the user must first export the tables of the SETL database from Microsoft Access to these files This would result in four files one for each table The user is then required to load these files into SETLyze First follow the steps to export the SETL data You can perform an analysis once you have loaded the four data files containing the SETL data Start SETLyze and you should be presented with the Analysis Selection dialog Select an analysis and press OK to begin A new dialog will be displayed most likely the Locations Selection dialog If this is your first time running SETLyze the locations selection dialog will show an empty locations list because no data has been loaded yet To load SETL data click on the Change Data Source button to open the change data source dialog This dialog allows you to load data from CSV or XLS files exported from the Microsoft Access SETL database Once the data has been loaded the locations selection dialog will automatically update the list of locations From here on it s just a matter of following the instruction one the screen Should you need more help scroll down to the SETLyze dialogs section for a more extensive description of each dialog The
20. photographs This divides the SETL plate into 25 equal surface areas see SETL plate with digitally applied grid Each of the 25 surface areas are called spots Species are scored for presence absence for each of the 25 spots on each SETL plate and the data is stored in the SETL database in the form of records So each SETL record in the database contains presence absence data of one species for all 25 spots on a SETL plate Spot distance Spot distances are the distances between positive spots on a SETL plate The spot distances are calcu lated from observed and expected positive spots data and are used to define whether species attract or repel Observed spot distances intra specific All possible distances between the spots on each plate are calculated using the Pythagorean theorem Consider the case of species A and the following plate Fig 2 3 Spot distances on SETL plate intra specific As you can see from the figure three positive spots results in three spot distances a b and c The distance from one spot to the next by moving horizontally or vertically is defined as 1 The distances from the figure are calculated as follows spot_distance a V3 2 3 61 spot_distance b V3 1 3 16 spot_distance c V0 3 3 This is done for all plates of an analysis Note that there can be no distance 0 in contrast to inter specific spot distances see below Observed spot distances inter specific To obtai
21. spe_id 2 2 Table set1_localities in the SETL database The SETL database can be either the MS Access database or the PostgreSQL database This table contains the SETL locality records PostgreSQL query CREATE TABLE setl localities loc id SERIAL loc name VARCHAR 100 NOT NULL UNIQUE loc nr INTEGER loc coordinates VARCHAR 100 loc description VARCHAR 300 CONSTRAINT loc id pk PRIMARY KEY loc id 2 3 Table species in the local SQLite database This table is automatically filled from 2 when the user starts a SETLyze analysis 2 3 1 Same as 2 5 but filled from 2 7 2 3 2 Same as 2 3 but filled from 2 19 SQLite query 2 3 SETLyze Developer Guide 35 SETLyze Documentation Release 1 0 1 CREATE TABLE species spe_id INTEGER PRIMARY KEY spe_name_venacular VARCHAR spe_name_latin VARCHAR spe_invasive_in_nl INTEGER spe_description VARCHAR spe_remarks VARCHAR 2 4 Table localities in the local SQLite database This table is automatically filled from 2 2 when the user starts a SETLyze analysis SQLite query CREATE TABLE localities loc_id INTEGER PRIMARY KEY loc_name VARCHAR loc_nr VARCHAR loc_coordinates VARCHAR loc_description VARCHAR 2 4 1 Same as 2 4 but filled from 2 2 2 4 2 Same as 2 4 but filled from 2 18 2 5 Table records in t
22. spots for each default plate area A B C and D for each plate that matches the species selection This table is filled by set plate area totals observed SQLite query CREATE TABLE plate area totals observed pla id INTEGER PRIMARY KEY area a INTEGER area b INTE area c INTE area d INTE R ER R 0000 2 42 Table plate_area_totals_expected in the local SQLite database This table contains the number of expected positive spots for each default plate area A B C and D per plate that matches the species selection The expected spots are calculated with a random generator The random generator randomly puts an equal number of positive spots on a virtual plate then calcualtes the number of positive spots for each plate area This is done for all plates mathching a species selection 44 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 This table is filled by set_plate_area_totals_expected SQLite query CREATE TABLE plate_area_totals_expected pla_id INTEGER PRIMARY KEY area_a INTEGER area_b INTEGER area_c INTEGER area_d INTEGER i Design Part Reference 3 0 Analysis Selection dialog 3 1 Locations Selection dialog 3 2 Species Selection dialog 3 x Graphical User Interfaces 3 3 Analysis Report dialog 3 4 Load Data di
23. the local SQLite database for storing basic information about the local database SQLite query CREATE TABLE info id INTEGER PRIMARY KEY name VARCHAR value VARCHAR 2 3 SETLyze Developer Guide 39 SETLyze Documentation Release 1 0 1 This information includes its creation date the data source and a version number The data source is a string which has the same design as 2 22 You can insert the data source with the following SQLite query INSERT INTO info VALUES cursor execute null source 2 setlyze config cfg get data source Giving a version number to the local database could be useful in the future We can then notify the user if the local database is too old followed by creating a new local database This would only work if the version for the database is incremented each time you change the design of the local database To do this edit the version number in create_table_info The version number can be inserted with cursor execute INSERT INTO info VALUES null version 2 db version The creation date and data source is inserted by the methods insert from csv and insert from db The date can be inserted with INSERT INTO info VALUES cursor execute null date date now 2 15 Table set1_plates in the SETL database The SETL database can be either the MS Acce
24. 2 2 User Manual 21 SETLyze Documentation Release 1 0 1 Chi squared The value the Chi squared test statistic df The degrees of freedom of the approximate chi squared distribution of the test statistic Mean Observed The mean of the observed spot distances This is calculated separately Mean Expected The mean of the expected spot distances This is calculated separately Remarks A summary of the results Shows whether the p value is significant and if so how significant and decides based on the means if the species attract observed mean lt expected mean or repel observed mean gt expected mean Some spots ratios groups might me missing from the list of results This is because spots ratios groups that don t have matching records are skipped so they are not displayed in the list of results Plate Areas Definition for Chi squared Test Describes the definition of the plate areas set with the Define Plate Areas dialog See the description for that dialog to get the meaning of the letters A B C and D Species Totals per Plate Area for Chi squared Test Area ID See the Plate Areas Definition for Chi squared Test section of the report to see the definition of each area Observed Totals How many times the selected species was found present in each of the plate areas Expected Totals The expected totals for the selected species Summary Report A summary report contains basic information from multiple standard reports Such a summa
25. 8 4 19 4 20 5 16 5 17 5 18 5 19 5 20 6 16 6 17 6 18 6 19 6 20 7 16 7 17 7 18 7 19 7 20 8 16 8 17 8 18 8 19 8 20 9 16 9 17 9 18 9 19 9 20 10 16 10 17 10 18 10 19 10 20 11 16 11 17 11 18 11 19 11 20 12 16 12 17 12 18 12 19 12 20 13 16 13 17 13 18 13 19 13 20 14 16 14 17 14 18 14 19 14 20 15 16 15 17 15 18 15 19 15 20 16 16 16 17 16 18 16 19 16 20 17 17 17 18 17 19 17 20 18 18 18 19 18 20 19 19 19 20 20 20 Ratios group 5 comb seq 1 25 comb seq 1 21 1 21 1 22 1 23 1 24 2 21 2 22 2 23 2 24 3 21 3 22 3 23 3 24 4 21 4 22 4 23 4 24 5 21 5 22 5 23 5 24 6 21 6 22 6 23 6 24 7 21 7 22 7 23 7 24 8 21 8 22 8 23 8 24 9 21 9 22 9 23 9 24 10 21 10 22 10 23 10 24 11 21 11 22 11 23 11 24 12 21 12 22 12 23 12 24 13 21 13 22 13 23 13 24 14 21 14 22 14 23 14 24 15 21 15 22 15 23 15 24 16 21 16 22 16 23 16 24 17 21 17 22 17 23 17 24 18 21 18 22 18 23 18 2 2 User Manual 25 SETLyze Documentation Rele
26. ETLyze is released under the GNU General Public License version 3 INSTALL Text file with installation instructions for SETLyze Technical Design SETLyze comes with a Technical Design a visual representation of SETLyze s design parts func tions classes GUI s interconnected by arrows representing the application s functions and work flow All design parts are numbered The same numbers can be found in the SETLyze s source code This means that the different design parts of the Technical Design can be easily linked to the corresponding source code The Technical Design provides an easy to understand overview of the application for users but is also of great value to developers It makes it easier to get a basic understanding of how the application works by looking at the Tech nical Design If the developer is interested in a specific part of the application he or she can easily navigate to the corresponding description and source code by the reference numbers used in the Technical Design Both the descriptions and source codes for the design parts in the Technical Design are browsable using this documen tation Read the Design Parts section below Design Parts The links below will guide you to the different design parts present in the Technical Design You just have to click in the the number for that design part Clicking on a design part will show you its description Next to the description is a link source which links to
27. GiMaRIS Responsible for the intial de velopment of the application then called Sesprere Implemented analysis Spot preference Documentation user manual programmer s manual and technical design 2 6 3 Serrano Pereira Internship bioinformatics Leiden University of Applied Science student at GiMaRIS September to November 2010 Optimization of the overall application renamed SETLyze Moved from Tkinter to GTK for creating the graphical user interfaces Optimization of analysis Spot preference Implementation of analysis Attraction within species and analysis Attraction between species Sphinx documentation user manual developer guide Technical design Distribution packages source package Windows installer Continued work on SETLyze in January 2013 Code repository moved from Bazaar to Git Implementation of batch mode for analyses Spot preference Attraction within species and Attraction be tween species This has been parallelized with the multiprocessing module from Python s standard library Overall optimization of the code Dropped the XML report exporter in favor of an improved reStructuredText report exporter Use a configuration file to save user preferences Release of version 1 0 in April 2013 2 6 4 Adam van Adrichem and Fedde Schaeffer Minor project internship bioinformatics Leiden University of Applied Science students at GiMaRIS Reo
28. Microsoft Access You ll see four tables in the left column SETL_localities SETL_plates SETL_records and SETL_species 2 To export a table right click on it to open the drop menu From the menu select Export gt Text file Then give the filename of the output file Make sure to include the table name in the filename e g setl_localities csv for the SETL_localities table Uncheck all other options and press OK 3 In the next dialog that appears select the option that separates fields with a character The separator character 99499 must be a semicolon If it s not change it by clicking the Advanced button Then click Finish to export the data to a CSV file 4 Repeat steps 2 and 3 for all tables 5 You should end up with four files one CSV file for each table Put these files in one folder Export to Excel files The database tables can also be exported to Excel files Only the import of Excel 97 2000 XP 2003 xls files are supported by SETLyze so be sure to select the right format 2 2 5 Use Cases Possible use cases which describe how SETLyze can be used to find answers to biological questions regarding the settlement of species on SETL plates Use Cases for SETLyze This document describes some possible use cases which describe how SETLyze can be used to find answers to biolog ical questions regarding the settlement of species on SETL plates 26 Chapter 2 Documentations SETLyze Documentation
29. Release 1 0 1 Use Case 1 Spot Preference Research Question Do species of the genus Obelia have a preference for specific locations on SETL plates Performing the analysis Analysis Spot preference was designed to analyse a species preference for a specific location on a SETL plates For this analysis we can define the following hypotheses Null hypothesis The species in question settles at random areas of SETL plates Alternative hypothesis The species in question has a preference for a plate area observed mean gt expected mean or has a rejection for a plate area observed mean lt expected mean The analysis uses the P value to decide which hypothesis is true P gt alpha level Assume that the null hypothesis is true P lt alpha level Assume that the alternative hypothesis is true To find an answer to the research question we re going to run the analysis on all species of the genus Obelia from all available locations Start SETLyze and from the main window select Analysis 1 Then click the OK button to start the selected analysis The Locations Selection dialog will now show up If this is your first time running SETLyze then the list of locations will be empty Clicking the Load Data button opens the Load Data dialog Use this dialog to load your SETL data For this example we ll use the test data provided with SETLyze Note On Windows the test data can be found in the sub folder test
30. SETLyze Documentation Release 1 0 1 GiMaRIS July 17 2015 Contents 1 About SETLyze 1 2 Documentations 3 DA Installation ee 3 2 2 User Manual 125 ure ee at Ree wc eb a he OS ca dics e Ran etd Bie tos ao eG 4 2 3 SEVLyze Developer Guide oko A mb oo hah wa A ed eat A 30 PO NIE NC ESSO ERE O e e ee hd a ee to pel ee ee eh edn ee A 60 2 9 JLegallnformation 2 2 044 554 4248624 wow E OX4e De xe 3e ROS Pay VOX RR 60 2 60 AboutUS 6 ue a E XUPIA EUER S we ARGUS Rau AE UE RR E ur P done 61 3 Indices and tables 65 Python Module Index 67 CHAPTER 1 About SETLyze The purpose of SETLyze is to provide the people involved with the SETL project an easy and fast way of getting useful information from the data stored in the SETL database The SETL database at GiMaRIS contains data about the settlement of species in Dutch waters SETLyze helps provide more insight in a set of biological questions by analyzing this data SETLyze can perform the following set of analyses Spot Preference Determine a species preference for a specific location on a SETL plate Species can be combined so that they are treated as a single species Attraction within Species Determine if a species attracts or repels individuals of its own kind Species can be com bined so that they are treated as a single species Attraction between Species Determine if two different species attract or repel each other Species can be combined so that they are t
31. This was done for both intra specific and inter specific spot distances The results were then loaded into R and visualised in a histogram see Distribution for intra specific spot distances and Distribution for inter specific spot distances Spot Distance Frequencies intra c t a bue E m D LL a Od e re e apot distance Fig 2 20 Distribution for intra specific spot distances The frequencies were obtained by calculating all possible distances between two spots if all 25 spots are covered The same test was done with different numbers of positive spots randomly placed on a plate with 100 000 repeats All resulting distributions are very similar to this figure 2 3 SETLyze Developer Guide 51 SETLyze Documentation Release 1 0 1 Spot Distance Frequencies inter ca e 4 uc D E m c T E g eg ce ho T 1 TI 1 0 1 2 3 4 5 Spot distance Fig 2 21 Distribution for inter specific spot distances 52 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 The frequencies were obtained by calculating all possible distances between two spots with ratio 25 25 species A and B have all 25 spots covered The same test was done with different positive spots ratios spots randomly placed on a plate 100 000 repeats All resulting distributions are very similar to this figure The histograms show that there is a tendency towards a normal distrubution but this is obstru
32. al tests Sets the alpha level The alpha level must be a number between O and 1 The default value O 05 means an alpha level of 5 10 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Preferences e ey x Alpha level a for statistical tests 0 05 Number of repeats for statistical tests 100 gt Number of concurrent processes for batch mode l4 Help Cancel E OK Fig 2 8 Preferences dialog This alpha level is translated to a confidence level with the formula con f level 1 o This confidence level is used for some statistical tests to calculate the confidence interval At this moment this is just the t test not used in any analysis at this point The alpha level is also used to determine if a P value returned by statistical tests is considered significant The P value is considered significant if the P value is equal or less than the alpha level Number of repeats for statistical tests Sets the number of repeats to perform on some statistical tests Some statis tical tests used in SETLyze use expected values that are randomly generated This means you can t draw a solid conclusion from the result of just one test There is a change that the found result was a coincidence To account for this these test are repeated a number of times The default value is 20 repeats This value is very low but good enough for testing purposes When you need to draw solid conclusions this value need
33. alog 3 5 Define Plate Areas dialog 3 6 Preferences dialog 3 7 Batch Mode dialog 4 x Documents Design Parts Documents The design parts in this overview describes all technical design parts representing docu ments created by SETLyze 4 x Documents 4 0 The analysis report The report can be exported in reStructuredText format Navigating the SETLyze Code Base SETLyze s many functions and classes are stored in different modules Classes and functions with similar functions are placed in the same module Below is an overview of all modules for SETLyze You can click on a module to get a description of that module and all its elements You can even view the source code for a specific function or class by clicking the source link on the right side of the description SETLyze modules SETLyze Standard Modules This reference manual describes the modules that are part of SETLyze setlyze config Configuration manager Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 2 3 SETLyze Developer Guide 45 SETLyze Documentation Release 1 0 1 Module Contents setlyze database Database access Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents setlyze gui Graphical interfaces Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents setlyze locale
34. are explained below 22 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Summary Report Spot Preference Example report Wilcoxon rank sum test Chi sq Species n A B C D A B C D A B C B C D A B C D plates Obelia 177 pr ns rj ns ns rj ns ns S di p 0 000P p 1 0000 p 0 0000p 0 050P p 0 3500 p 0 0000p 1 000P pz1 0000 12 103 98 chotoma p 0 0000 Obelia 91 ns ns rj ns ns rj ns ns s x2262 30 genicu p 0 450P p 1 0000 p 0 0000p 0 100P p 1 0000 p 0 0000p 1 000P p 1 0000 p 0 0000 lata Obelia 341 pr ns rj rj pr rj ns rj S longis p 0 000P p 1 0000 p 0 0000p 0 000P p 0 0000 p 0 0000p 1 000P p 0 0000 12 435 22 sima p 0 0000 Explanation of the columns Species Name of the species n plates The total number of plates for the species selection The real number of plates used for each data group may be smaller Use the Save All button to see the number of plates used for each data group A B C D A B C D A B C and B C D In this report the results are grouped by plate area see Grouping by Plate Area For the Wilcoxon rank sum test the test is performed on each of the four plate areas plus the combinations A B C D A B C and B C D For the Chi squared test the user defined plate areas are used The user defined plate areas can be seen in the column name e g A B C D means that areas A and
35. ase 1 0 1 24 19 21 19 22 19 23 19 24 20 21 20 22 20 23 20 24 21 21 21 22 21 23 21 24 22 22 22 23 22 24 23 23 23 24 24 24 Ratios where one species has covered all 25 spots are excluded from this group because the p value would be insignificant for such ratios You can imagine that the results of the statistical test performed on records from ratios group 1 has a higher reliability than the results for ratios group 5 Records from ratios group 1 have fewer positive spots Finding that species A is often close to species B on records of group 5 doesn t say much The high number of positive spots naturally results in spots sitting close to each other This is however not the case for records of group 1 where there is enough space for the species to sit Finding them next to each other in group 1 probably means something The significance test is also performed on ratios group with number 5 This group includes ratios from all 5 groups still excluding ratios with 25 The results of the significance tests are presented in rows Each row contains the result of the test for one group The Ratios Group column tells you to which group each result belongs 2 2 4 Exporting SETL data from the Access database Export to CSV files This section describes how to export the SETL data from the Microsoft Access database to CSV files 1 Open the SETL database file mdb in
36. ase 2 Wilcoxon tests 2 2 User Manual 29 SETLyze Documentation Release 1 0 1 Let s first look at the results of the non repeated tests You ll see that most results are non significant There might be a few exceptions but these could have other causes then attraction repuslion For example some parts of the SETL plates might be coverd with another species making it simply impossible for Balanus crenatus to settle there So these are the results of the non repeated tests The results with very low P values are pretty solid even though the expected values were calculated randomly But this cannot be said for P values that are close to the alpha level 5 by default In that case the significance result could be a coincidence This is why the results of repeated tests should be taken into account as well The Wilcoxon test was repeated a number of times And before each repeat the expected values are re calculated By default the number of repeats is set to 10 Let s have a look at the results of the repeated tests Notice that sometimes the test does return significant If you however find that the test returns non significant far more often than significant you could conclude that there is no significance and therefor assume that the null hypothesis is true Then there are the results of the Chi squared tests While the Wilcoxon test looks at the distribution of spot distances the measurements the Chi quared test looks at th
37. at retrieving pre calculated spot distances from the database is much slower than calculating them on run time 2 24 Variable of type dict containing the plate areas definition for analysis 1 The dictionary has the format areal list area2 list area3 list area4 list Where list is a list of strings The possible strings are A B C and D Each letter represents a surface on a SETL plate For a clearer picture refer to Default plate areas The default value for the plate areas definition is areal A area2 B area3 C area4 D Using setlyze gui DefinePlateAreas the user can change this definition The user could for example combine the surfaces A and B meaning the value for this variable becomes Keep in mind that the dictionary keys areal area2 don t have any meaning They just make it possible to destinct between the plate areas Get the value with set lyze config ConfigManager get setlyze config cfg get plate areas definition Set the value with set1yze config ConfigManager set 42 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 setlyze config cfg set plate areas definition value 2 25 An application variable that contains the observed species totals for each user defined plate area Keep in mind that this is not the number of individual organisms found on
38. ation of the columns 2 2 User M anual 23 SETLyze Documentation Release 1 0 1 Species A Name of the first species Species B Name of the species the first species was compared with n plates The total number of plates for the species selection The real number of plates used for each data group may be smaller Use the Save All button to see the number of plates used for each data group 1 5 1 2 3 4 5 In this report the results are grouped by positive spot ratio groups see Record grouping by ratios groups Record Grouping SETLyze performs statistical tests to determine the significance of results The key statistical tests used to determine significance are the Wilcoxon rank sum test and Pearson s Chi squared test The tests are performed on records data that match the locations and species selection It is however not a good idea to just perform the test on all matching records For this reason the matching records are first grouped by a specific property The tests are then performed on each group Two methods for grouping records have been implemented One is by positive spots number and the other is by positive spots ratio We ll describe each grouping method below Grouping by Plate Area This type of grouping is done for analysis Spot Preference Each group is a plate area or a combination of plate areas The following groups are defined 1 Plate area A 2 Plate area B 3 Plate area C
39. be found in the sub folder test data of the directory to where you installed SETLyze e g C Program FilesNGiMaRISNSETLyzeNtest dataY On Linux the test data folder can be found in the source package Once the SETL data is loaded you should see a list of all locations You can now select the locations from which you want to select species For this example we re just interested in data from the location Aquadome Grevelingen Select Aquadome Grevelingen from the list Press the Continue button The Species Selection dialog should now be displayed By default the species are sorted by their scientific name Select the species Balanus crenatus Press the Continue button to start the calculations for this analysis In a few seconds you should be presented with the Analysis Report dialog This dialog shows the results for the analysis Results For this analysis two different statistical hypothesis tests are performed the Wilcoxon rank sum test and Pearson s Chi squared test The following sections should be present in the report dialog Wilcoxon rank sum test with continuity correction Wilcoxon rank sum test with continuity correction repeated Chi squared test for given probabilities Let s first have a look at the results of the Wilcoxon tests Click on both Wilcoxon sections to reveal the results You should see something similar to the screenshot below o Fig 2 18 Analysis Report for Use C
40. between the keyword name and the value call 1 3 cheese quark Module Imports mports should be done at the top level of the file unless there is a strong reason to have them lazily loaded when a particular function runs Import statements have a cost so try to make sure they don t run inside hot functions Naming Functions methods or members that are relatively private are given a leading underscore prefix We prefer class names to be concatenated capital words TestCase and variables methods and functions to be lowercase words joined by underscores revision id get revision For the purposes of naming some names are treated as single compound words filename revno purp 8 8 P Consider naming classes as nouns and functions methods as verbs Try to avoid using abbreviations in names because there can be inconsistency if other people use the full name Standard Names revision_idnot rev_idor revid Functions that transform one thing to another should be named x_to_y not x2y as occurs in some old code Event and Signal Handling A large part of SETLyze is controlled with signals and signal handlers To emit custom ap plication signals we use setlyze std sender emit And to connect a signal to a sig nal handler we use setlyze std sender connect When signal handlers are no longer needed use setlyze std sender disconnect to disconnect the handler from the signal Call ing setlyze std sende
41. binary packages are ready for distribution Do make sure to test the resulting packages first 2 4 References All references used in the documentation are listed here 2 4 1 Reference List 2 5 Legal Information 2 5 1 Copyright Documentation The content of this documentation is property of their authors Some contents of this documentation was produced elswhere and reproduced here with permission You are welcome to display on your computer download and print pages from this documentation provided the content is only used for personal educational and non commercial use You must retain copyright and other notices on any copies or printouts you make The content of this documentation is subject to the GNU General Public Licence GPL unless otherwise stated 60 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 SETLyze SETLyze is free software you can redistribute it and or modify it under the terms of the GNU General Public License as published by the Free Software Foundation either version 3 of the License or at your option any later version SETLyze is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE See the GNU General Public License for more details You should have received a copy of the GNU General Public License along with the program If not see http www gnu org lice
42. ch value x is a number representing the number of encounters of a species on a plate area for a specific record in the database So a value x 4 means that the species was found on four spots of the area in question for a specific plate If the area in question was A then the maximum value for x would be 4 because area A consists of four spots This is done for all records matching that species and plate area resulting in a sequence of numbers e g 1 0 0 3 12 4 8 0 Son is the number of values x 2 2 User Manual 19 SETLyze Documentation Release 1 0 1 n observed species The number of times the species was found on the plate area in question This is for all plates summed up n expected species The number of times you d expect the species to be found on the plate area in question The expected values are calculated per plate with a random generator For each plate the same number of positive spots are generated randomly on a virtual plate The number of positive spots are then counted for the plate area in question n plates The number of plates that match the number of positive spots n distances The number of spot distances derived from the records matching the positive spots number P value The P value for the test Mean Observed The mean of the observed spot distances This is calculated separately Mean Expected The mean of the expected spot distances This is calculated separately Remarks A summary of t
43. combined so that they are treated as a single species Attraction within Species Determine if a species attracts or repels individuals of its own kind Species can be com bined so that they are treated as a single species Attraction between Species Determine if two different species attract or repel each other Species can be combined so that they are treated as a single species Additionally any of the above analyses can be performed in batch mode meaning that the analysis is repeated for each species of a species selection Thus an analysis can be easily performed on an entire data set without intervention Batch mode for analyses are parallelized such that the computing power of a computer is optimally used Data Collection First let s have a look at how the data for the SETL project is being collected When the SETL plates are checked each plate is first carefully pulled out of the water and then photographed This is done by a standard procedure described on the ANEMOON foundation s website First an overview photograph is taken of each plate Then some more detailed photographs are taken of the species that grow on each plate Indivdual plates are recognized by their tags The pictures are then carefully analyzed For each plate the SETL monitoring form is filled in For each species the absence or presence abundance and area cover are filled in For this a 5x5 grid is digitally applied over the photograph SETL plate with digitally appl
44. cted because of the limited number of possible spot distances To test if the distribution of spot distances really don t follow a standard normal distribution we performed the One sample Kolmogorov Smirnov test on both intra and inter spot distance samples This was again done with the use of R The results are as follows gt ks test dist intra 1 pnorm mean mean dist_intra 1 sd sd dist_intra 1 One sample Kolmogorov Smirnov test data dist intra 1 D 0 1419 p value 1 133e 05 alternative hypothesis two sided Warning message In ks test dist intra 1 pnorm mean mean dist intra 1 cannot compute correct p values with ties gt ks test dist inter 1 pnorm mean mean dist_inter 1 sd sd dist_inter 1 One sample Kolmogorov Smirnov test data dist inter 1 D 0 1188 p value 4 403e 08 alternative hypothesis two sided Warning message In ks test dist inter 1 pnorm mean mean dist inter 1 cannot compute correct p values with ties So the p values can t be correctly computed which might render the results unreliable So the Shapiro Wilk normality test was performed as well gt shapiro test dist intra 1 Shapiro Wilk normality test data dist intra 1 W 0 9512 p value 1 955e 08 gt shapiro test dist inter 1 Shapiro Wilk normality test data dist inter 1 W 0 9725 p value 1 957e 09 Again very low p values are fo
45. d optimize SETLyze Testing and Optimization This document describes the steps taken to test and optimize SETLyze Testing Calculation of expected spot distances Analyses 2 and 3 have a built in consistency check In all cases must the number of calculated expected spot distances be equal to the number of observed spot distances If this is not the case than this indicates a bug in the application This is what the check looks like Perform a consistency check The number of observed and expected spot distances must always be the same count observed len observed count expected len expected if count_observed count_expected raise ValueError Number of observed and expected spot distances are not equal This indicates a bug in the application Testing spot distances for normal distribution This part describes the method used to test if the spot distances on a SETL plate follow a standard normal distribution The choice of the statistical tests used for some analyis is based 50 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 on the results of this test This is because some statistical tests assume that the samples follow a normal distribution while some do not First step was to calculate the probabilities for the spot distances on a SETL plate A Python script was written to calculate the probabilities for all possible spot distances on a single SETL plate
46. data of the directory to where you installed SETLyze e g C Program FilesNGiMaRISNSETLyzeNtest dataY On Linux the test data folder can be found in the source package Once the SETL data is loaded you should see a list of all locations You can now select the locations from which you want to select species For this example we want to use all data available for the genus Obelia so we ll select all locations Select a location and then press Ctrl A to select all locations Press the Continue button The Species Selection dialog should now be displayed By default the species are sorted by their scientific name Scroll down until you find the species who s name start with Obelia You should find the following six species Obelia not geniculata Obelia geniculata Obelia dichotoma Obelia longissima Obelia bidentata Obelia sp Select all six species by holding down the Shift key Then press the Continue button The Define Plate Areas dialog should now be displayed This dialog allows you to define the SETL plate areas for the Chi squared test The result of the Chi squared test for this analysis is only useful if you have large amounts of data for the species you re analyzing Because the Wilcoxon test for this analysis gives more specific information about the plate areas we ll focus on that instead So we ll skip the details of this dialog and leave the default plate areas setting for the Chi squared test Press th
47. e Continue button to start the calculations for this analysis In a few seconds you should be presented with the Analysis Report dialog This dialog shows the results for the analysis For this example we ll skip the results of the Chi squared test and focus on the results of the Wilcoxon tests 2 2 User Manual 27 SETLyze Documentation Release 1 0 1 Results You should see two sections for the results of the Wilcoxon test Wilcoxon rank sum test with continuity correction Wilcoxon rank sum test with continuity correction repeated Click on both sections to reveal the results You should see something similar to the screenshot below a o tre en Fig 2 17 Analysis Report for Use Case 1 Let s first look at the results of the non repeated tests You can see that there seems to be a strong preference for the corners of a SETL plate see Default plate areas for an overview of the plate areas I say strong because the P value is very low P lt 0 1 At the same time this species seems to reject the middle areas of the plates areas C and D There is no significance for area B so it makes sense that the combination A B returns significant preference This significance is caused by area A and not B The same can be said for B C D The significance is caused by the areas C D Area A B C returns non significant This is because both A and C have a significance but in the opposite directions B has again no influence
48. e Install System Once NSIS is installed you can build the Windows installer by simply right clicking setlyze setup modern nsi and choosing Compile NSIS Script Give NSIS a moment to process the script and compile the installer If the script is correct it should produce the Windows installer in the same folder called something similar to set1yze x x bundle win32 exe Last but not least you should test the installer The best way to do this is on a clean installation of Windows Meaning you should test this on a Windows machine where no other software has been installed because only then can you really say that the installer and the resulting SETLyze executable works An easy way to get a clean installation is to install Windows on a virtual machine e g VirtualBox and test the installer before any other software is installed Building Source and Linux Binary Packages The source package is nothing more than an archive tar gz on Linux zip on Windows containing the application s source code Distributing the application s source code is what defines open source software This allows everyone to see how SETLyze was created but also to edit use and learn from it This package can also be used to install SETLyze on all supported operating systems including Windows and GNU Linux This part of the guide explains how to create source packages and installation packages for GNU Linux From now on well need a Linux system Open a termina
49. e frequencies at which spot distances occur The observed frequen cies are being compared to the expected frequencies This again leads to P values which can be used to determine which hypothesis is true Because the expected values are fixed repeats aren t necessary for this test Analysis Report Fig 2 19 Analysis Report for Use Case 2 Chi squared tests In this case the Chi squared test gives similar results to the Wilcoxon test It turns out however that this method is less sensitive to differences in samples Conclusion Balanus crenatus doesn t seem to attract or repel individuals of its own kind 2 3 SETLyze Developer Guide Welcome to the Developer Guide for SETLyze This document describes the SETLyze internals It s meant for people who are involved in the development process of SETLyze It should be easy for a new developer to pick up where the last SETLyze developer left off The purpose of this guide is to give the new developer full understanding of SETLyze s internals its programming style what s unfinished et cetera 2 3 1 Getting Started Obtaining the source code The source code for SETLyze is currently hosted on GitHub The project page can be found at the following URL https github com figure002 setlyze 30 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 The source code is version controlled with Git You ll need to install Git before you can start work
50. ence Analysis wilcoxon test for repeats 1 101 setlyze analysis spot preference Analysis get area probabilities 1 102 setlyze analysis attraction intra Analysis wilcoxon test for repeats 1 103 setlyze analysis attraction intra Analysis repeat wilcoxon test 1 104 setlyze analysis attraction inter Analysis wilcoxon test for repeats 1 105 setlyze analysis attraction inter Analysis repeat wilcoxon test 1 x Modules Classes amp Functions 2 3 SETLyze Developer Guide 33 SETLyze Documentation Release 1 0 1 2 x Data Storage Places Design Parts Data The design parts in this overview describes all technical design parts representing data used in SETLyze This includes database tables application variables and data files 2 x Data Storage Places 2 0 Table set1_records in the SETL database The SETL database can be either the MS Access database or the PostgreSQL database This table contains the SETL records PostgreSQL query CREATE TABLE setl_records rec_id SERIAL rec_pla_id INTEGER NOT NULL rec_spe_id INTEGER NOT NULL rec_unknown BOOLEAN rec_o BOOLEAN rec_r BOOLEAN rec_c BOOLEAN rec_a BOOLEAN rec_e BOOLEAN rec_sur_unknown BOOLEAN rec_surl BOOLEAN rec_sur2 BOOLEAN rec_sur3 BOOLEAN rec_sur4 BOOLEAN rec_sur5 BOOLEAN
51. ent Ob ject Model object containing the analysis settings and results This XML DOM object is generated by setlyze report ReportGenerator Get the value with set1yze config ConfigManager get setlyze config cfg get analysis report Set the value with set lyze config ConfigManager set setlyze config cfg set analysis report value 2 18 CSV file containing the locality records exported from the MS Access SETL database If exported from the MS Access SETL database the CSV file must have the format LOC_id LOC_name LOC_nr LOC_coordinates LOC_description 2 19 CSV file containing the species records exported from the MS Access SETL database If exported from the MS Access SETL database the CSV file must have the format SPE_id SPE_name_venacular SPE_name_latin SPE_invasive_in_NL SPE_description SPE_remarksjSPE_picture 2 20 CSV file containing the plate records exported from the MS Access SETL database If exported from the MS Access SETL database the CSV file must have the format PLA_id PLA_LOC_id PLA_SETL coordinator PLA nr PLA deployment date PLA retrieval date PL water tempe 2 21 CSV file containing the SETL records exported from the MS Access SETL database If exported from the MS Access SETL database the CSV file must have the format REC id REC PLA id REC SPE id
52. evelopers instructions on how to distribute SETLyze This includes building an installer for Windows and source packages mainly for GNU Linux users and developers New developers will have to do this at some point so this document was created for their convenience Building a Windows Installer SETLyze should be as easy as possible to install on Windows machines and most users don t want to worry about downloading and installing SETLyze s pre requisites Thus a Windows installer also called a setup which installs SETLyze along with all its pre requisites is required This section explains how to create the Windows installer for SETLyze using Nullsoft Scriptable Install System NSIS a professional open source system to create Windows installers To start off you ll need a Windows machine preferably Windows XP or higher to build the installer Once you have that read on to the next part Preparing your Windows environment Before you can start building the installer we need to make some prepara tions You first need to make sure that SETLyze runs flawlesly on your Windows machine Let s try to get SETLyze running using only the source code Do not use the Windows installer to get SETLyze running on your system First you need to download and install all of SETLyze s pre requisites on the Windows machine You ll need to download and install the tools in the order of this list below Actually the order doesn t matter much but
53. hat this step is not needed if you have the Windows installer for SETLyze which comes bundeled with the requirements 2 1 2 Installation Windows users can use the Windows installer for SETLyze which installs all dependencies and creates shortcuts in the Start menu and on the desktop SETLyze Documentation Release 1 0 1 If you want to install SETLyze from the GitHub repository git clone https github com figure002 setlyze git pip install setlyze Or if you have a source archive file pip install setlyze x x tar gz Once installed the set lyze executable should be available 2 1 3 Contributing Please follow these steps to start working on the SETLyze code base 1 Fork the project on github com 2 Create a new branch 3 Commit changes to the new branch 4 Send a pull request First make sure that all dependencies are installed as described above Then follow the next steps to run and develop SETLyze within a virtualenv isolated Python environment git clone https github com figure002 setlyze git cd setlyze virtualenv system site packages env source env bin activate env pip install r requirements txt env python setup py develop env setlyze 2 2 User Manual Welcome to the user manual for SETLyze This manual explains the usage of SETLyze 2 2 1 Introduction SETLyze is a part of the SETL project a fouling community study focussing on mari
54. he local SQLite database This table is only filled if the user selected CSV files to import SETL data from By default this table is empty and the records data from 2 0 is used SQLite query CREATE TABLE records rec id INTEGER PRIMARY KEY rec pla id INTEGER rec spe id INTEGER rec unknown INTEGER rec o INTEGE rec r INTEGE rec c INTEGE rec a INTEGE rec e INTEGER rec sur unknown INTEGER rec s ri I EGER rec sur2 I EGER rec sur3 INTEGER rec sur4 I EGER rec sur5 INTEGER rec sur6 INTEGER rec sur 7 I EGER rec sur8 INTEGER rec sur9 INTEGER rec surl10 INTEGER 36 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 rec_surll INTEGER rec_surl2 INTEGER rec_surl3 INTEGER rec_surl4 INTEGER rec_surl5 INTEGER rec_surl6 INTEGER rec_surl7 INTEGER rec_surl8 INTEGER rec_surl9 INTEGER rec_sur20 INTEGER rec_sur21 INTEGER rec_sur22 INTEGER rec_sur23 INTEGER rec_sur24 I EGER rec_sur25 INTEGER rec_lst INTEGER rec_2nd INTEGER rec_v INTEGER 2 6 A list lt selection 1 gt lt selection 2 gt for storing a maximum of two location selections
55. he results Shows whether the p value is significant p value lt alpha level and if so how significant and decides based on the means if the species attract species reject a plate area observed mean lt expected mean or repel species prefer a plate area observed mean gt expected mean Some data groups might me missing from the list of results This is because groups that don t have matching records are skipped so they are not displayed in the list of results Wilcoxon rank sum test with continuity correction repeated Shows the significance results for the repeated Wilcoxon tests For more information about the Wilcoxon rank sum test results see Wilcoxon rank sum test with continuity correction The number of repeats to perform can be set in the Preferences dialog Each row for the results of the repeated Wicoxon test contains the results of repeated tests on a data group Each row can have the following elements Plate Area See description for Wilcoxon rank sum test with continuity correction n totals See description for Wilcoxon rank sum test with continuity correction n observed species See description for Wilcoxon rank sum test with continuity correction n significant Shows how many times the test turned out significant for the repeats P value lt alpha level n non significant Shows how many times the test turned out to be not significant for the repeats P value gt alpha level n preference Shows how
56. ibed in this chapter all perform one of SETLyze s analysis setlyze analysis attraction inter Analysis Attraction between Species Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents setlyze analysis attraction intra Analysis Attraction within Species Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents setlyze analysis batch Batch mode Author Serrano Pereira Release 1 0 1 Date July 17 2015 Module Contents setlyze analysis common Shared routines for analysis modules Author Serrano Pereira Release 1 0 1 Date July 17 2015 Module Contents 2 3 SETLyze Developer Guide 47 SETLyze Documentation Release 1 0 1 setlyze analysis relations Analysis Relations between Species Author Serrano Pereira Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents setlyze analysis spot_preference Analysis Spot Preference Author Serrano Pereira Jonathan den Boer Adam van Adrichem Fedde Schaeffer Release 1 0 1 Date July 17 2015 Module Contents 2 3 2 Coding Style Guidelines Code layout Please write PEP 8 compliant code One often missed requirement is that the first line of docstrings should be a self contained one sentence summary We use 4 space indents for blocks and never use tab characters Trailing white space should be avoided but is allowed If
57. ied grid For each species the presence or absence on each of the 25 plate surfaces are filled in and saved to the database Fig 2 1 SETL plate with digitally applied grid Each record in the database contains a species ID a plate ID and the 25 plate surfaces The species ID links to the species that was found on the plate The plate ID links to the plate on which that species was found The plate ID is also linked to the location where this plate was deployed The 25 plate surfaces spots are stored in each record as booleans meaning they can have a value of True or False The value 1 True for a spot means that the species in question was present on that spot of the plate The value O False means that the species was absent from that spot With 25 spots x 2500 records 625000 booleans for the presence absence of species automatic methods of analyzing this data are required Hence SETLyze was developed a tool for analyzing the settlement of species on SETL plates 2 2 2 Using SETLyze SETLyze comes with a graphical user interface GUI The GUI consists of dialogs which all have a specific task These dialogs will guide you in performing the set of analyses it provides Most of SETLyze s dialogs have a Help button which when clicked should point you to the corresponding dialog description on this page All dialog descrip tions can be found in the SETLyze dialogs section of this manual Before SETLyze can perform an analysis
58. indows executable for SETLyze This script uses py2exe for that This script is not intended for installing SETLyze FYI It would make more sense to put this file in the win32 folder but SETLyze s module folder src setlyze needs to be in the same folder as this script src doc src source This folder contains the source files of the documentation The source files end with the extension rst You can edit these with a text editor After editing the source files x rst for the documentation you can use the make files Makefile on Linux make bat on Windows to generate the actual HTML documen tation Refer to the Sphinx documentation for instructions The Makefile contains a custom target htm12 which is similar to the default html target but uses the E switch of sphinx build so that all source files are read This is useful when some parts of the documentation aren t fully updated The generated documentation is put in src setlyze docs To prepare the folder containing SETLyze s Git repository for creating distributions you need to copy the Windows installer for R 2 12 1 in the win32 dependencies folder The installer is called R 2 12 1 win exe and can be downloaded from the R website Building the Windows Executable for SETLyze The next step is to create a Windows executable for SETLyze From now on you need to be at a Windows machine notice the use of backslashes At this point one can start SETLyze by runn
59. ing on SETLyze Go to http git scm com to get started with Git If you are new to using Git there is a well written online book Pro Git which explains everything you need to know about using Git At least read through the Getting Started section Once you have Git installed and properly setup you can obtain a copy of the source code for SETLyze with the following command git clone git github com figure002 setlyze git Navigating the SETLyze folder The key files in SETLyze s root folder are src setlyze This is SETLyze s main code base This package folder contains all of SETLyze s modules This is the folder where you ll be editing most Python source files for SETLyze src setlyze pyw This is SETLyze s executable This is what you ll run to start SETLyze src setlyze docs html This folder contains the documentation for SETLyze This includes the User Manual and the Developer Guide You can view the manual by double clicking index html This should open the documenta tion in your web browser src doc src This folder contains the files used to build the documentation This is done using Sphinx Some parts of the documentation are from rst files within this folder others are extracted from the documentation strings within the program source code README md This text file contains a short description of the program and directs you to other documentation COPYING This text file contains the license for SETLyze S
60. ing setlyze pyw from the Git repository So setlyze pyw is SETLyze s executable but it is a regular Python script and one needs to have Python and all of SETLyze s pre requisites installed to run the script 2 3 SETLyze Developer Guide 57 SETLyze Documentation Release 1 0 1 We don t want Windows users to have to download and install all these extra tools So before creating the installer we re going to create a special Windows executable set lyze exe which does not require users to have Python and all the pre requisites installed with one exception For this purpose we re going to use py2exe Download the latest py2exe for Python 2 7 from here and install it on your Windows machine Once you have py2exe installed building the Windows executable should be a breeze with the provided src build win32 exe py Open up a DOS window and run the following command cd src python build win32 exe py py2exe Note Running Python from the command line or DOS requires that you have Python in your PATH environment variable Python is not added to PATH by default If the above command gives you a message like python is not recognized as an internal or external command operable program or batch file then you need to make sure that your computer knows where to find the Python interpreter To do this you will have to modify a variable called PATH which is a list of directories where Windows will look for programs
61. l window and cd to the root folder of the Git repository The command for this looks something like this cd path to setlyze 2 3 SETLyze Developer Guide 59 SETLyze Documentation Release 1 0 1 Of course you need replace that path with the path to the repository folder Now list all files in that folder by typing 1s You might notice a file CMakeLists txt This is a CMake configuration file and there are more of these files in subfolders We use CMake for creating distribution packages Here follow a few examples Before we continue create a build folder mkdir build cd build Now run the following command to generate the make files ccmake This command actually reads the CMakeLists txt file mentioned earlier Press c to configure the make file Set the CMAKE_INSTALL_PREFIX option to usr Press c again to confirm the settings Then press g to generate the make files There should now be a file called Makefile in the build folder This Makefile can do awesome things which will be demonstrated by some examples To install SETLyze system wide run this command as root make install To uninstall SETLyze from the system run this command as root make uninstall To build a source package make package_source To build a binary packages e g DEB and RPM packages make package The resulting source or
62. lta y h v distance cursor fetchone def test2 Calculate spot distances on run time combos setlyze std get spot combinations from record test record for spotl spot2 in combos h v setlyze std get spot position difference spotl spot2 distance setlyze std distance h v Time both tests runs 1000 t timeit Timer test1 from main import testl print testl f seconds t timeit runs runs t timeit Timer test2 from main import test2 print test2 f seconds t timeit runs runs cursor close connection close The first test in the script gets pre calculated spot distances from the database and the second test calculates spot distances on run time The output was as follows testl1 0 011350 seconds test2 0 003097 seconds This shows that calculating spot distances on run time is almost 4 times faster than retrieving pre calculated spot distances from the database So the use of the spot distances table was dropped and spot distances are now calculated on run time 54 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 2 3 4 Distribution The following document describes how to create the distribution packages and installers for SETLyze Distribution of SETLyze This guide shows the developer how to distribute SETLyze making it available for the user The purpose of this document is to give the d
63. many times there was a significant preference for the plate area in question n rejection Shows how many times there was a significant rejection for the plate area in question n attraction Shows how many times there was a significant attraction for the species in question n repulsion Shows how many times there was a significant repulsion for the species in question Chi squared test for given probabilities Shows the results for Pearson s Chi squared Test for Count Data Pearson s chi square x2 test is the best known of several chi square tests It tests a null hypothesis stating that the frequency distribution of certain events observed in a sample is consistent with a particular theoretical distribution Pearson s Chi squared Test Wikipedia 23 December 2010 The observed values are the frequencies of the observed spot distances The expected values are calculated with the formula e d N x p d where N is the total number of observed distances and p is the probability for spot distance d The probability p has been pre calculated for each spot distance The probabilities for intra specific spot distances are from the model of Distribution for intra specific spot distances and the probabilities for inter specific distances 20 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 are from the model of Distribution for inter specific spot distances The probabilities have been hard coded into the application
64. n C Python27 Lib site packages gtk 2 0 runtime Manually copy the following folders to the src dist folder lt GTK_runtime_path gt etc e lt GTK_runtime_path gt lib Only the dll files from the subdirectories are needed Remove the other files to save space lt GTK_runtime_path gt share From this folder only the themes and locale subdirectories are needed Remove the other files and folders to save space Even from the locale folder you don t need all files You can just keep the locales that are used in SETLyze mainly locales for English which saves a lot of space Again run set lyze exe SETLyze should now look like a native Windows application no more ugly dialogs But we are not there yet Try to use one of SETLyze Help buttons You ll notice that it doesn t work This is because it s looking for the documentation files in the src dist docs folder This folder doesn t exist yet The 58 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 build win32 exe py script doesn t automatically copy the src setlyze docs folder to the src dist folder This is not yet built into the build win32 exe py script so you ll have to copy paste it manually Copy the folder src setlyze docs into the src dist folder The contents of src set lyze docs were generated from the src doc src folder with the Sphinx documentation generator Again try one of SETLyze s Help buttons The help contents sho
65. n spot distances for analyses where two species are involved first the plate records are collected that contain both of the selected species Then all possible spot distances are calculated between the two species The following figure shows an example with positive spots for two species A and B and all possible spot distnaces In the above figure the distances are calculated the same way as for intra specific spot distances Note however that only inter specific distances are calculated distances between two different species This also makes it possible to have a distance of 0 as visualized in the next figure The distances for this figure are calculated as follows 2 2 User Manual 7 SETLyze Documentation Release 1 0 1 Fig 2 4 Spot distances on SETL plate inter specific Fig 2 5 Spot distances on SETL plate inter specific 8 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 spot_distance a V0 0 0 spot_distance b V3 1 3 16 spot_distance c V0 2 2 Expected spot distances The expected spot distances are calculated by generating a copy of each plate record matching the species selection Each copy has the same number of positive spots as its original except the positive spots are placed randomly at the plates Then the spot distances are calculated the same way as for the observed spot distances This means that the resulting list of expected spot distances has the
66. ne invasive species The website describes the SETL project as follows Over the last ten years marine invaders have had a dramatically increasing impact on temperate water ecosystems around the world Substantial ecological and economical damage has been caused by the introduction of diseases parasites predators invaders outcompeting native species and species that are a nuisance for public health tourism aquaculture or in any other way In the SETL project standardized PVC plates are used to detect these invasive species and other fouling community organisms The material and methods of the SETL project were developed by the ANEMOON foundation in cooperation with the Smithsonian Marine Invasions Laboratory of Smithsonian Environmental Research Centre In this project 14x14 cm PVC plates are hung 1 meter below the water surface and refreshed and checked for species at least every three months ANEMOON foundation Data collected from these SETL plates are stored in the SETL database This database currently contains over 25000 records containing information of over 200 species in different locations throughout the Netherlands SETLyze is an application capable of performing a set of analyses on this SETL data SETLyze can perform the following analyses 4 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Spot Preference Determine a species preference for a specific location on a SETL plate Species can be
67. nly enabled in batch mode and allows you to export the reports of the individual analyses Clicking the Save button in batch mode only saves the Summary Report which is based on the individual reports 2 2 User Manual 15 SETLyze Documentation Release 1 0 1 Analysis Spot preference y w 9 Define SETL plate Areas for Chi squared Test Please define the plate areas for the Chi squared test You can keep the default setting meaning that A B C and D are treated as separate plate areas or you can combine specific areas by changing the setting below Combining areas means that the combined areas are treated as a single plate area One must define at least two plate areas In any case the Wilcoxon test will analyze the plate areas A B C D A B C D A B C and B C D A BCD Plate area Plate area2 9 Platearea3 O amp Platearead O O O Fig 2 12 Define Plate Areas dialog 16 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Fig 2 13 Default plate areas In any case the Wilcoxon test will analyze the C D A B C D A B C and B C D A B C D Plate area 1 6 Plate area 2 Plate areaz O O mim D gt Plate areadz O O O Er Fig 2 14 Combined plate areas selection 2 2 User Manual 17 SETLyze Documentation Release 1 0 1 Fig 2 15 Plate areas A and B combined SVS ell Report Spot P
68. nses 2 5 2 Links to other websites This documentation contains links to other websites and resources The links are provided for convenience only and GiMaRIS is not responsible for the content of any linked websites The inclusion of any link to a website does not imply endorsement by GiMaRIS of the website or their entities products or services 2 5 3 Disclaimer This documentation was created using Sphinx which is property of their authors SETLyze is written in the Python programming language and thus needs the Python interpreter to operate SETLyze might come in packages bundled with Python and other software tools it requires The third party software tools bundled with SETLyze are property of their individual authors and are governed by their individual applicable licence Below is a list of the key third party software tools that SETLyze depends on Python GTK PyGTK PyCairo PyGObject setuptools e R e RPy xlrd Python Win32 Extensions 2 5 4 Credits e This legal information is based on Canonical s legal information The Developer Guide is based on the Developer Guide for Bazaar 2 6 About Us The following people have been involved in the SETLyze project 2 6 About Us 61 SETLyze Documentation Release 1 0 1 2 6 1 Arjan Gittenberger Project leader and contact info O gimaris com at GiMaRIS 2 6 2 Jonathan den Boer Internship bioinformatics Leiden University of Applied Science student at
69. of reports Standard Report When running an analysis in standard mode not in batch mode the report is divided into sections There is a section for each statistical test that was performed Summary Report When running an analysis in batch mode the report will be a summary of all standard reports that were generated This report will show less details than a standard report Both types of reports will be explained below Standard Report A standard report is divided into subsections You have to click on a subsection to reveal its contents Find the explanation for each subsection below Locations and Species Selections Displays the locations and species selections If multiple selections were made each element is suffixed by a number For example Species selection 2 stands for the second species selection Wilcoxon rank sum test with continuity correction Shows the results for the non repeated Wilcoxon rank sum tests In statistics the Mann Whitney U test also called the Mann Whitney Wilcoxon MWW or Wilcoxon rank sum test is a non parametric statistical hypothesis test for assessing whether two independent sam ples of observations have equally large values Mann Whitney U Wikipedia 6 December 2010 Tests showed that spot distances on a SETL plate are not normally distributed see Testing spot distances for normal distribution hence the Wilcoxon rank sum test for unpaired data was chosen to test if observed and e
70. og is displayed telling the user that existing data is being loaded Clicking the About button shows SETLyze s About dialog The About dialog shows general information about SET Lyze its version number license information a link to the GiMaRIS website the application developers and contact information Clicking the Preferences button loads the Preferences dialog Batch Mode dialog Batch Mode Select the SETL analysis that you want to run in batch mode Attraction within species Attraction between species Spot preference Determine if a species has preference for a specific area on SETL plates Close OK Fig 2 7 Batch Mode dialog Selecting Batch mode in the Analysis Selection dialog brings up the Batch Mode dialog This dialog allows you to start an analysis in batch mode In batch mode the selected analysis is repeated for each species in a species selection or each inter species combination for analysis Attraction between Species When multiple species are selected the analysis is repeated for each species separately and the results are displayed in a Summary Report The summary report only displays the species that had significant results Preferences dialog The preferences dialog allows you to change SETLyze s settings Settings set here are saved to a configuration file in the user s home directory setlyze setlyze cfg The following settings can be changed Alpha level o for statistic
71. ok something like this This would result in three plate areas Analysis Spot Preference would then determine if the selected species has a preference for either of the three plate areas The names of the plate areas area 1 area 2 do not have a special meaning It is simply used internally by the application to distinguish between plate areas These area names are also used in the analysis report to distinguish between the plate areas The Back button allows you to go back to the previous dialog This can be useful when you want to correct a choice you made in a previous dialog The Continue button saves the selection closes the dialog and shows the next dialog Analysis Report dialog The analysis report dialog shows the results for an analysis The dialog consists of the results frame and a toolbar on top The toolbar holds a number of buttons Hover your mouse pointer over the buttons to reveal a tooltip which explains the button s action Some buttons are explained below Save The Save button allows you to save the report to a file Clicking this button first shows a File Save dialog which allows you to select a target directory and filename One file type is supported reStructuredText rst Plain text files in an easy to read markup syntax One can use Docutils to convert reStructuredText files into useful formats such as HTML LaTeX man pages open document or XML Save All The Save All button is o
72. ort 1 50 setlyze report Report set location selections 1 51 setlyze report Report set species selections Continued on next p 32 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Table 2 1 continued from previous page Design Part Reference 1 52 setlyze report Report set spot distances observed 1 53 setlyze report Report set spot distances expected 1 54 setlyze report Report set plate areas definition 1 55 setlyze report Report set area totals observed 1 56 setlyze report Report set area totals expected 1 57 setlyze config ConfigManager 1 58 setlyze analysis spot preference Analysis run 1 59 setlyze analysis attraction intra Analysis run 1 60 setlyze analysis attraction inter Analysis run 1 62 setlyze analysis spot preference Analysis set plate area totals observed 1 63 setlyze analysis spot preference Analysis set plate area totals expected 1 64 setlyze analysis spot preference Analysis get defined areas totals observed 1 65 setlyze analysis spot preference Analysis repeat wilcoxon test 1 68 setlyze analysis common PrepareAnalysis on display results 1 69 setlyze analysis attraction inter Analysis calculate distances inter expectec
73. pecies Selection etc The Back button allows you to go back to the previous dialog This can be useful when you want to correct a choice you made in a previous dialog The Continue button saves the selection closes the dialog and shows the next dialog Making a selection Just click on one of the species to select it To select multiple species hold Ctrl or Shift while selecting To select all species at once click on a species and press Ctrl A Load Data dialog Load SETL Data Load SETL Data Use one of the tabs below to load SETL data Fram Local Files Load SETL data from CSV or XLS files These data files can be exported from the Microsoft Access SETL database The user manual describes how to export these files Select locations file E SETL lacalities xls in Select species file SETL species csv Select recards file None Select plates file None a Cancel OK Fig 2 11 Load Data dialog The Load Data dialog allows you to load SETL data into SETLyze Two data sources are supported 14 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Text CSV csv txt files exported from the Microsoft Access SETL database The CSV files need to be ex ported by Microsoft Access one file for each of the four tables SETL_localities SETL_plates SETL_records and SETL_species The section Exporting SETL data from the Access database describes how
74. possible configure your text editor to automatically remove trailing spaces and tabs upon saving Unix style newlines LF are used Each file must have a newline at the end of it Lines should be no more than 79 characters if at all possible Use a text editor that has some kind of long line marker indicating the 79 characters boundary Lines that continue a long statement may be indented in either of two ways within the parenthesis or other character that opens the block e g my long method argl arg2 arg3 or indented by four spaces my long method argl arg2 arg3 The first is considered clearer by some people however it can be a bit harder to maintain e g when the method name changes and it does not work well if the relevant parenthesis is already far to the right Avoid this self legbone kneebone shinbone toebone shake it one two three but rather 48 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 self legbone kneebone shinbone toebone shake_it one two three or self legbone kneebone shinbone toebone shake it one two three For long lists we like to add a trailing comma and put the closing character on the following line This makes it easier to add new items in the future from setlyze std import unigify median distance There should be spaces between function parameters but not
75. press Ctri A Species Latin V Species common Anaitides maculata gestippelde dieseltreinworm Anemone bad photograph Aplidium glabrum Glanzende bolzakpijp Ascidian A Ascidian A Ascidiella aspersa Vuilwitte zakpijp Asterias rubens Gewone zeester Athanas nitescens Kreeftgarnaal Aurelia aurita Kwalpoliepjes Balanus crenatus Gekartelde zeepok Balanus improvisus Brakwaterpok Balanus sp Barnacle bad photograph Barnacle bad photograph Barnacle young black amphipod Back Continue Fig 2 10 Species Selection dialog The species selection dialog shows a list of all SETL species that were found in the selected SETL locations This dialog allows you to select the species to be included in the analysis Only the SETL records that match both the locations and species selection will be used for the analysis It is possible to select more than one species see Making a selection Selecting more than one species in a single species selection dialog means that the selected species are threated as one species for the analysis In batch mode however the analysis is repeated for each of the selected species 2 2 User Manual 13 SETLyze Documentation Release 1 0 1 If the selected analysis requires two or more separate species selections e g two species are compared it will display the selection dialog multiple times In this case the header of the selection dialog will say First Species Selection Second S
76. r disconnect should generall be done when the instance that called setlyze std sender connect is destroyed 2 3 SETLyze Developer Guide 49 SETLyze Documentation Release 1 0 1 License Statement SETLyze is released under the GNU General Public License version 3 Each file that s part of SETLyze must have the copyright notice and copying permission statement included at the top of the file after the encoding declaration So the top of each file should look like this usr bin env python coding utf 8 Copyright 2010 GiMaRIS lt info gimaris com gt This file is part of SETLyze A tool for analyzing the settlement of species on SETL plates SETLyze is free software you can redistribute it and or modify it under the terms of the GNU General Public License as published by the Free Software Foundation either version 3 of the License or at your option any later version SETLyze is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE See the GNU General Public License for more details You should have received a copy of the GNU General Public License along with this program If not see lt http www gnu org licenses gt Sh SR SR ches Hs AG SHS SR CHe HRS cHe che Ho SS SSE SS HS cH A 2 3 3 Testing and Optimization The following document describes the steps taken to test an
77. reated as a single species Additionally any of the above analyses can be performed in batch mode meaning that the analysis is repeated for each species of a species selection Thus an analysis can be easily performed on an entire data set without intervention Batch mode for analyses are parallelized such that the computing power of a computer is optimally used SETLyze Documentation Release 1 0 1 2 Chapter 1 About SETLyze CHAPTER 2 Documentations 2 1 Installation 2 1 1 Requirements SETLyze runs on GNU Linux MacOS and Microsoft Windows The following software is required to run SETLyze e GTK gt 2 24 0 2 24 8 2 24 10 eR Python gt 2 6 amp lt 2 8 appdirs PyGTK PyCairo and PyGObject pandas RPy2 xlrd gt 0 8 Windows users can use the Windows installer for SETLyze which installs all dependencies and creates shortcuts in the Start menu and on the desktop On Debian based systems the dependencies can be installed from the software repository sudo apt get install python appdirs python gtk2 python pandas python rpy2 python xlrd r base cor More recent versions of some Python packages can be obtained via the Python Package Index preferably inside a Python virtualenv pip install r requirements txt Windows users should install the PyGTK all in one Windows installer Then use pip as described above to install the remaining dependencies Note t
78. reference gt gt Locations and Species Selections gt gt Plate Areas Definition for Chi squared Test gt gt Species Totals per Plate Area for Chi squared Test gt Chi squared test for given probabilities Y Wilcoxon rank sum test with continuity correction Plate Area n totals n observed species n expected species P value A 849 1581 1594 0 839102 B 849 4773 4751 0 911878 E 849 3076 3118 0 666472 D 849 415 382 0 108679 A B 849 6354 6345 0 996669 C D 849 3491 3500 0 873874 A B C 849 9430 9463 0 906475 B C D 849 8264 8251 0 996635 Mean Observed 1 862191 5 621908 3 623086 0 488810 7 484099 4 111897 11 107185 9 733805 W Wilcoxon rank sum test with continuity correction repeated Plate Area n totals n observed species n significant A 849 1581 0 B 849 4773 0 E 849 3076 0 n non significant 20 20 20 NN n preference Mean Expected 1 877503 5 595995 3 672556 0 449941 7 473498 4 122497 11 146054 9 718493 n rejection 0 0 0 Fig 2 16 Analysis Report dialog 18 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Repeat The Repeat button can be used to repeat an analysis with different parameters Clicking this button will open a dialog which shows the same parameters available in the Preferences dialog So one can for example quickly repeat the analysis with a different number of repeats The report dialog can display two types
79. revelingen attract individuals of its own kind Performing the analysis Analysis Attraction of Species intra specific can be used to determine if a species attracts or repels individuals of its own kind For this analysis we can define the following hypotheses 28 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 Null hypothesis The species in question settles at random areas of SETL plates unregarded the presence of other individuals of its own kind Alternative hypothesis The species attracts observed mean lt expected mean or repels observed mean gt expected mean individuals of its own kind The analysis uses the P value to decide which hypothesis is true P gt alpha level Assume that the null hypothesis is true P lt alpha level Assume that the alternative hypothesis is true To find an answer to this research question we re going to run the analysis on Balanus crenatus from the location Aquadome Grevelingen Start SETLyze and from the main window select analysis Attraction within Species Then click the OK button to start the selected analysis The Locations Selection dialog will now show up If this is your first time running SETLyze then the list of locations will be empty Clicking the Load Data button opens the Load Data dialog Use this dialog to load your SETL data For this example we ll use the test data provided with SETLyze Note On Windows the test data can
80. rformed on records with up to 24 positive spots This means that the significance test will also be performed on records of all groups together Note that records of group 1 will still be ignored The results of the significance tests are presented in rows Each row contains the result of the test for one group The Positive Spots column tells you to which group each result belongs Record grouping by ratios groups This type of grouping is done in the case of calculated spot distances between two different groups of species analysis Attraction between Species When dealing with two species plate records are matched that contain both species This means we can get a ratio for the positive spots for each matching SETL plate record Consider Spot distances on SETL plate inter specific which visualizes a SETL plate with positive spots of species A and B There are two positive spots of one species and three positive spots of the other That makes the ratio for this plate 2 3 The order of the species doesn t matter here so a ratio A B is considered the same as ratio B A All records are grouped based on this ratio We ve defined five ratios groups Note c comb s A function for generating a list of two item combinations with replacement c from a sequence of num bers s The two item combinations are ratios e g 2 3 ratio 2 3 s seq start end A function for creating a sequence of numbers s from a number range
81. rganised the Bazaar repositories to be easier to copy develop and track Implemented the cancel button in the progress bar of the analyses e Implemented the possibility of reading Microsoft Office Excel 97 2004 workbooks Tried to make a start making the technical design match the actual implementation Looked into how the repetitions of Wilcoxon tests could be parallelised using the multiprocessing module from Python s standard library 62 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 e Looked into how an analysis could be executed serially for all species in the database to find out which species should be investigated more Release of version 0 2 2 6 About Us 63 SETLyze Documentation Release 1 0 1 64 Chapter 2 Documentations CHAPTER 3 Indices and tables genindex modindex search 65 SETLyze Documentation Release 1 0 1 66 Chapter 3 Indices and tables Python Module Index S setlyze locale 46 67 SETLyze Documentation Release 1 0 1 68 Python Module Index Index S setlyze locale module 46 T text in module setlyze locale 46 69
82. ry report is basically a table where each row represents a single analysis and the columns contain the results per data group In the summary report a result is only displayed if one of the statistical tests done for a species combination was considered significant Some statistical tests are repeated and in this case there is a p value for each repeat In this case the p value is calculated with p 1 s t where s is the number of significant p values for the major form of significance For example if attraction was more often significant than rejection then s is the total number of significant p values for attraction And ft is the total number of repeats for the test So with 20 repeats and a 0 05 19 out of 20 repeats must have had a significant p value in one direction for the test result to be considered significant Below are the definitions for the result codes used in summary reports na There is not enough data for the analysis or in case of the Chi Squared test one of the expected frequencies is less than 5 s The result for the statistical test was significant ns The result for the statistical test was not significant pr There was a significant preference for the plate area in question rj There was a significant rejection for the plate area in question at There was a significant attraction for the species in question rp There was a significant repulsion for the species in question The summary report for each analysis
83. s to be set to a higher number Number of concurrent processes for batch mode Batch mode for analyses are parallelized which means that mul tiple analyzes can be executed in parallel The value set here corresponds to the number of concurrent processes that will execute analyses The higher the number the faster a batch analysis will complete The number of processes must be at least 1 and no more than the number of CPUs The default value of this option equals to 90 of the available CPUs Locations Selection dialog The locations selection dialog shows a list of all SETL locations This dialog allows you to select locations from which you want to select species The Species Selection dialog displayed after clicking the Continue button will only display the species that were recorded in the selected locations Subsequently this means that only the SETL records that match both the locations and species selection will be used for the analysis as each SETL record is bound to a species and a SETL plate from a specific location The Change Data Source button opens the Load Data dialog This dialog allows you to load new SETL data After doing so the locations selection dialog is automatically updated with the new data The Back button allows you to go back to the previous dialog This can be useful when you want to correct a choice you made in a previous dialog The Continue button saves the selection closes the dialog and shows the next dialog
84. same length as the observed spot distances 2 2 3 SETLyze dialogs SETLyze comes with a graphical user interface consisting of separate dialogs The dialogs are described in this section Analysis Selection dialog Welcome to SETLyze ia X Select the desired SETL analysis a E Attraction within species gt Attraction between species 5 Batch mode 5pot preference Determine if a species has preference for a specific area on SETL plates About Preferences Quit OK Fig 2 6 Analysis Selection dialog The analysis selection dialog is the first dialog you see when SETLyze is started It allows the user to select an analysis to perform on SETL data The user can select one of the analyses in the list and click on the OK button to start the analysis Clicking the Quit button closes the application 2 2 User Manual 9 SETLyze Documentation Release 1 0 1 After pressing the OK button two things can happen If no SETL data was found on the user s computer SETLyze automatically tries to load SETL locations and species data from the SETL database server This requires a direct connection with the SETL database server A progress dialog is shown while the data is being loaded If connecting to the database server fails SETLyze continues without data Since the database server has not been implemented yet no data will be loaded If SETL data is found on the user s computer an information dial
85. ss database or the PostgreSQL database This table contains the SETL plate records PostgreSQL query CREATE TABLE setl plates pla id SERIAL pla loc id INTEGER NOT NULL pla setl coordinator VARCHAR 100 pla nr VARCHAR 100 pla deployment dat IMESTAMP pla retrieval date IMESTAMP pla water temperatur VARCHAR 100 pla_salinity VARCHAR 100 pla_visibility VARCHAR 100 pla_remarks VARCHAR 300 CONSTRAINT pla id pk PRIMARY KEY pla id CONSTRAINT pla loc id fk FOREIGN KEY pla loc id REFERENCES setl localities loc id ON DELETE NO ACTION ON UPDATE NO ACTION 2 16 Table plates in the local SQLite database This table is only filled if the user selected CSV files to import SETL data from By default this table is empty and the plates data from 2 75 is used SQLite query CREATE TABLE plates pla_id INTEGER PRIMARY KEY pla_loc_id INTEGER pla setl coordinator VARCHAR pla nr VARCHAR pla deployment date TI EXT pla retrieval date TEXT pla water temperature VARCHAR pla salinity VARCHAR pla visibility VARCHAR 40 Chapter 2 Documentations SETLyze Documentation Release 1 0 1 pla_remarks VARCHAR 2 17 Links to an instance of xml dom minidom Document Its a XML DOM Docum
86. starting with start and ending at end For example seq 1 6 1 2 3 4 5 Ratios group 1 comb seq 1 6 1 1 1 2 1 3 1 4 1 5 2 2 2 3 2 4 2 5 G 3 3 4 3 5 4 4 4 5 5 5 Ratios group 2 comb seq 1 11 comb seq 1 6 1 6 1 7 1 8 1 9 1 10 2 6 2 7 2 8 2 9 2 10 3 6 3 7 3 8 3 9 3 10 4 6 4 7 4 8 4 9 4 10 5 6 5 7 5 8 5 9 5 10 6 6 6 7 6 8 6 9 6 10 7 7 7 8 7 9 7 10 8 8 8 9 8 10 9 9 9 10 10 10 Ratios group 3 comb seq 1 16 comb seq 1 11 1 11 1 12 1 13 1 14 1 15 2 11 2 12 2 13 2 14 2 15 3 11 3 12 3 13 3 14 3 15 4 11 4 12 4 13 4 14 4 15 5 1D 6 12 5 13 5 14 5 15 6 11 6 12 6 13 6 14 6 15 7 11 7 12 7 13 7 14 7 15 8 11 8 12 8 13 8 14 8 15 9 11 9 12 9 13 9 14 9 15 10 11 10 12 10 13 10 14 10 15 11 11 11 12 11 13 11 14 11 15 12 12 12 13 12 14 12 15 13 13 13 14 13 15 14 14 14 15 15 15 Ratios group 4 comb seq 1 21 comb seq 1 16 1 16 1 17 1 18 1 19 1 20 2 16 2 17 2 18 2 19 2 20 3 16 3 17 3 18 3 19 3 20 4 16 4 17 4 1
87. the Python modules marked with an asterisk need to be installed after Python itself is installed It is important that you get the right versions as well If no version number is given in the list below than it means you can get the latest version The tools marked with an asterisk are Python modules meaning they are available for different versions of Python Since we re using Python 2 7 it is required that you download the versions for Python 2 7 Look at the suffix of the installer s filenames they should end with py2 7 exe Download only 32bit versions of the tools below The 32bit installers often have win32 or x86 not x86 64 in the filename 1 Python gt 2 7 amp lt 3 R 2 12 1 PyGTK bundle with PyCairo PyGObject GTK 2 24 0 2 24 0 RPy gt 1 0 3 xlrd gt 0 8 0 6 Python Win32 Extensions 22218 RAN AeA U N SETLyze will probably run fine with Python 2 6 too but the latest Python 2 7 is recommended and used in this tutorial We are specifically using GTK version 2 24 0 for Windows At the time of writing this there are also GTK 2 24 8 and 2 24 10 available for Windows but we are not using those versions because of a huge memory leak bug 685959 that was introduced in GTK 2 24 8 fixed in 2 24 14 The memory leak causes SETLyze to use a huge amount of memory which results in a crash when running long batch analyses Also notice that we are specifically using
88. the corresponding source code Design Parts 2 3 SETLyze Developer Guide 31 SETLyze Documentation Release 1 0 1 Design Part Reference 1 0 The executable for SETLyze set lyze pyw 1 1 The main function in the executable 1 2 setlyze database MakeLocalDB 1 3 setlyze analysis spot_preference 1 3 1 setlyze analysis spot_preference Begin 1 3 2 setlyze analysis spot_preference BeginBatch 1 3 3 setlyze analysis spot_preference Analysis 1 4 setlyze analysis attraction_intra 1 4 1 setlyze analysis attraction_intra Begin 1 4 2 setlyze analysis attraction_intra BeginBatch 1 4 3 setlyze analysis attraction_intra Analysis 1 5 setlyze analysis attraction_inter 1 5 1 setlyze analysis attraction_inter Begin 1 5 2 setlyze analysis attraction_inter BeginBatch 1 5 3 setlyze analysis attraction_inter Analysis 1 11 setlyze gui SelectionWindow on load data 1 12 setlyze report Report 1 13 setlyze analysis spot preference Analysis generate report 1 14 setlyze analysis attraction intra Analysis generate report 1 15 setlyze analysis attraction inter Analysis generate report 1 17 setlyze report export 1 19 1 setlyze database AccessLocalDB set species spots
89. the plate areas as the records just tell the presence of a species So it tells how many times the presence of a species was found on each user defined plate area This is what the value can look like area4 52 areal 276 area2 751 area3 457 Namespace setlyze analysis spot_preference Start areas_totals_observed 2 26 An application variable that contains the expected species totals for each plate area Keep in mind that this not the number of individuals found on the plate area as the records just tell the presence of a species This is what the value can look like area4 61 439999999999998 areal 245 75999999999999 area2 737 27999999999997 area3 491 51999999999998 Namespace setlyze analysis spot_preference areas_totals_expected 2 27 The element location_selections in the XML DOM report that contains the user selected locations 2 28 The element species_selections in the XML DOM report that contains the user selected species 2 29 The element spot_distances_observed in the XML DOM report that contains the actual spot distances 2 30 The element spot_distances_expected in the XML DOM report that contains the expected spot dis tances 2 31 The element plate_areas_definition in the XML DOM report that contains the user defined plate areas definition 2 32 The element area_totals_observed in the XML DOM report that contains the actual species totals per plate area
90. to export these files Excel 97 2000 XP 2003 xls files exported from the Microsoft Access SETL database One file for each of the four tables SETL_localities SETL_plates SETL_records and SETL_species Microsoft Access by default includes a header row in the exported XLS files The header row must be removed before importing into SETLyze After selecting all four data files files press the OK button to load the SETL data from these files A progress dialog is shown while the data is being loaded Once the data has been loaded the Locations Selection dialog will be updated with the new data Define Plate Areas dialog This dialog allows you to define the plate areas for analysis Spot Preference By default the SETL plate is divided in four plate areas A B C and D This dialog allows you to combine these areas by changing the area definitions Combining areas means that the combined areas are treated as a single plate area One must define at least two plate areas The user defined plate areas are only used for the Chi squared test In any case the Wilcoxon test will analyze the plate areas A B C D A B C D A B C and B C D Below is a schematic SETL plate with a grid By default the plate is divided in four plate areas A B C and D But sometimes it s useful to combine plate areas So if one decides to combine areas A and B the selection could be changed as follows And the resulting plate areas definition would lo
91. uld now open in your browser At this point the src dist folder contains almost all files required to run SETLyze I say almost because one still needs to have R installed to run setlyze exe But we ll get to that later Check and double check that setlyze exe works the way it should Building the Windows Installer Now that you have prepared the dist folder you can start building the Win dows installer for SETLyze The structure of the repository folder is important because the NSIS script set lyze_setup_modern nsi expects to find a number of files and folders in the repository folder and packs these into a single installer The files and folders it uses are as follows COPYING dist icons setlyze ico README md win32 dependencies R 2 12 1 win ex Notice that you need to put the installer for R in the win32Ndependencies folder Open setlyze setup modern nsi in a text editor e g Notepad or gedit and see if you can find the direc tives that load these files hint search for File You do not need to understand everything what s in the NSIS script right now You just need to be able to edit it All directives need to be correct or else building the installer will fail Once all files are in place it s time to compile the NSIS script Compiling means that we will build the actual installer from the NSIS script You ll first need to download and install Nullsoft Scriptabl
92. und which is why we assume that spot distances on a SETL plate don t follow a standard normal distribution Hence we chose the Wilcoxon rank sum test because this test doesn t assume that data come from a normal distribution Dalgaard Welch s t test is an adaptation of Student s t test Wikipedia And because Student s t test does assume that data come from a normal distribution Dalgaard we chose not to use this test Optimization 2 3 SETLyze Developer Guide 53 SETLyze Documentation Release 1 0 1 Spot distance calculation It was thought that retrieving pre calculating spot distances from a table in the local database would be faster than calculating each spot distance on run time Python s timeit module was used to find out which method is faster For this purpose a small script was written usr bin env python import os import timeit from sqlite3 import dbapi2 as sqlite import setlyze std connection sqlite connect os path expanduser setlyze setl local db cursor connection cursor test record 1 1 12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 def test1 Get pre calculated spot distances from the local database combos setlyze std get_spot_combinations_from_record test_record for spotl spot2 in combos h v setlyze std get spot position difference spotl spot2 cursor execute SELECT distance FROM spot distances WHERE delta x AND de
93. xpected spot distances differ significantly The observed and expected spot distances Depending on the analysis the test is performed on different groups of data The data can be grouped by plate area analysis Spot Preference the number of positive spots analysis Attraction within Species or by positive spot ratios groups analysis Attraction between Species See section record grouping for more information on data grouping Each row for the results of the Wicoxon test contains the results of a single test on a data group Each row can have the following elements Plate Area The plate area of a SETL plate A SETL plate is divided into four plate areas A B C and D see Default plate areas The test is performed on each of the four plate areas plus the combinations A B C D A B C and B C D Combining the results of the test for all plate areas and combinations allows you to make conclusions about the species preference for areas on SETL plates See also Grouping by Plate Area Positive Spots A number representing the number of positive spots For this test only records matching that number of positive spots were used See also Record grouping by number of positive spots Ratios Group A number representing the ratios group For this test only records grouped in that ratios group were used See also Record grouping by ratios groups n totals The number of values n used for the statistical test Ea

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