programming assignment sleuth assessment

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Programming Assignment: Writing a Unit Test Solution

In this article i am gone to share Programming with JavaScript by meta Week 4 | Programming Assignment: Writing a Unit Test Solution with you..

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Visit this link:  Programming Assignment: Array and object iteration Solution

Lab Instructions: Unit Testing

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Task 1: Add Jest as a devDependency

Open terminal. Make sure that it’s pointing to  jest-testing  directory. Install the jest npm package using the npm install command and the –save-dev flag. Verify that the installation was completed successfully by opening the package.json file and confirming that the “devDependencies” entry lists jest similar to the following:

Task 2: Update the test entry

In the package.json file, locate the “scripts” entry, and inside of it, update the test entry to  jest .

Task 3: Code the timesTwo function

Open the timesTwo.js file and add a function named  timesTwo . The function should take number as input and return the value 2 multiplied by the number. Export the timesTwo function as a module.

Task 4: Write the first test

Code a test call with the following arguments:

• The description that reads: “returns the number times 2”.
• The second argument should expect the call to the timesTwo function, when passed the number 10, to be 20.

Task 5: Run the first test

With the terminal pointed at the  jest-testing  directory, run the test script using npm.

• Copy & paste this code on Files..
• And save your file and then submit.

First Change in this file timesTwo.js

Second Change in this file timesTwo.test.js

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Introduction to Computer Programming by University of London & Goldsmiths, University of London. SLEUTH ASSIGNMENT.

After downloading the sleuth case I tried running it but it doesn't display the img.jpg , Instead it displays a message (Loading...). Screenshot

*I use VSCode. Because I cant even open a file in brackets editor(ERROR).*

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Getting started with sleuth

Harold pimentel, nicolas bray, páll melsted, lior pachter, introduction.

sleuth is a tool for the analysis and comparison of multiple related RNA-Seq experiments. Key features include:

• The ability to perform both transcript-level and gene-level analysis.
• Compatibility with kallisto enabling a fast and accurate workflow from reads to results.
• The use of boostraps to ascertain and correct for technical variation in experiments.
• An interactive app for exploratory data analysis.

To use sleuth , RNA-Seq data must first be quantified with kallisto , which is a program for very fast RNA-Seq quantification based on pseudo-alignment. An important feature of kallisto is that it outputs bootstraps along with the estimates of transcript abundances. These can serve as proxies for technical replicates, allowing for an ascertainment of the variability in estimates due to the random processes underlying RNA-Seq as well as the statistical procedure of read assignment. kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. sleuth has been designed to work seamlessly and efficiently with kallisto, and therefore RNA-Seq analysis with kallisto and sleuth is tractable on a laptop computer in a matter of minutes. More details about kallisto and sleuth are provided the papers describing the methods:

Nicolas L Bray, Harold Pimentel, Páll Melsted and Lior Pachter, Near-optimal probabilistic RNA-seq quantification , Nature Biotechnology 34 , 525–527 (2016), doi:10.1038/nbt.3519

Harold Pimentel, Nicolas L Bray, Suzette Puente, Páll Melsted and Lior Pachter, Differential analysis of RNA-seq incorporating quantification uncertainty , in press.

sleuth has been designed to facilitate the exploration of RNA-Seq data by utilizing the Shiny web application framework by RStudio. The worked example below illustrates how to load data into sleuth and how to open Shiny plots for exploratory data analysis. The code underlying all plots is available via the Shiny interface so that analyses can be fully “open source”.

Preliminaries

This walkthrough is based on data from the “Cuffdiff2 paper”:

• Differential analysis of gene regulation at transcript resolution with RNA-seq by Cole Trapnell, David G Henderickson, Martin Savageau, Loyal Goff, John L Rinn and Lior Pachter, Nature Biotechnology 31 , 46–53 (2013).

The human fibroblast RNA-Seq data for the paper is available on GEO at accession GSE37704 . The samples to be analyzed are the six samples LFB_scramble_hiseq_repA, LFB_scramble_hiseq_repB, LFB_scramble_hiseq_repC, LFB_HOXA1KD_hiseq_repA, LFB_HOXA1KD_hiseq_repA, and LFB_HOXA1KD_hiseq_repC. These are three biological replicates in each of two conditions (scramble and HoxA1 knockdown) that will be compared with sleuth .

To analyze the data, the raw reads must first be downloaded. This is done by installing kallisto and then quantifying the data with boostraps as described on the kallisto site . This step can be skipped for the purposes of the walkthrough, by downloading the kallisto processed data directly with

Once the kallisto quantifications have been obtained, the analysis shifts to R and begins with loading sleuth :

The first step in a sleuth analysis is to specify where the kallisto results are stored. A variable is created for this purpose with

The result can be displayed by typing

In the box above, lines beginning with ## show the output of the command (in what follows we include the output that should appear with each command).

A list of paths to the kallisto results indexed by the sample IDs is collated with

The next step is to load an auxillary table that describes the experimental design and the relationship between the kallisto directories and the samples:

Now the directories must be appended in a new column to the table describing the experiment. This column must be labeled path , otherwise sleuth will report an error. This is to ensure that samples can be associated with kallisto quantifications.

It is important to check that the pairings are correct:

Next, the “sleuth object” can be constructed. This object will store not only the information about the experiment, but also details of the model to be used for differential testing, and the results. It is prepared and used with four commands that (1) load the kallisto processed data into the object (2) estimate parameters for the sleuth response error measurement (full) model (3) estimate parameters for the sleuth reduced model, and (4) perform differential analysis (testing) using the likelihood ratio test. On a laptop the four steps should take about a few minutes altogether.

The sleuth object must first be initialized with

Then the full model is fit with

What this has accomplished is to “smooth” the raw kallisto abundance estimates for each sample using a linear model with a parameter that represents the experimental condition (in this case scramble vs. HOXA1KD). To test for transcripts that are differential expressed between the conditions, sleuth performs a second fit to a “reduced” model that presumes abundances are equal in the two conditions. To identify differential expressed transcripts sleuth will then identify transcripts with a significantly better fit with the “full” model.

The “reduced” model is fit with

and the test is performed with

In general, sleuth can utilize the likelihood ratio test with any pair of models that are nested, and other walkthroughs illustrate the power of such a framework for accounting for batch effects and more complex experimental designs.

The models that have been fit can always be examined with the models() function.

The results of the test can be examined with

The table shown above displays the top 20 significant genes with a (Benjamini-Hochberg multiple testing corrected) q-value <= 0.05.

Including gene names into transcript-level analysis

At this point the sleuth object constructed from the kallisto runs has information about the data, the experimental design, the kallisto estimates, the model fit, and the testing. In other words it contains the entire analysis of the data. There is, however, one piece of information that can be useful to add in, but that is optional. In reading the kallisto output sleuth has no information about the genes transcripts are associated with, but this can be added allowing for searching and analysis of significantly differential transcripts by their associated gene names.

Since the example was constructed with the ENSEMBL human transcriptome, we will add gene names from ENSEMBL using biomaRt (there are other ways to do this as well):

First, install biomaRt with

Then collect gene names with

and add them into the sleuth table with

This addition of metadata to transcript IDs is very general, and can be used to add in other information.

The easiest way to view and interact with the results is to generate the sleuth live site that allows for exploratory data analysis:

Among the tables and visualizations that can be explored with sleuth live are a number of plots that provide an overview of the experiment. For example, a PCA plot provides a visualization of the samples:

Various quality control metrics can also be examined. The count distributions for each sample (grouped by condition) can be displayed using the plot_group_density command:

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Table of contents

Spotlight effect on firefox, syntax error due to console.log(), function parentheses, variable assignment, 101, stage 3, 201, stage 4, 601, all stages, 601, stage 4, 701, all stages, 701, stage 4, 702, all stages, 702, stage 1, 702, stage 2, 702, stage 4, 801, all stages, 801, stage 3-4, 801, stage 4, 802, stage 1, random function, 802, stage 3, 802, stage 4, audiocontext not allowed to start, audio resources not loading, video: 2d coordinate system, practice quiz: using the console and debugging syntax errors, lesson 4.1 video: conditional statements using ==, lesson 4.2 practice quiz: introducing types: string, number, boolean, practice quiz: conditionals with types, itp1 - reported problems, tips and additional instructions.

This page is about the Introduction to programming I module .

General Sleuth Issues

Be aware that Sleuth cases involving a spotlight effect (302 and 801) will not work on Firefox out of the box, like they work in any webkit based browser (like Google Chrome and Safari).

Easiest workaround is commenting out the line at the bottom that says blendMode(DARKEST) and uncommenting it again before submitting the case. Changing it to blendMode(LIGHTEST) should work at least to be able to see where the spotlight is.

If you get this message when submitting a case:

Remove all of your debugging statements that are using console.log() .

You need to ensure that any function being declared does not have a space between the function name and the argument. For example:

Some cases ask to set the value of a variable to mouseX for instance and then make sure it doesn’t go above or below a certain value with min() and max() functions. Answers can wrongly be accepted if you first set

and then reassign it by applying a function that is missing a parameter:

where X is an integer. The variable should be assign in one statement as follow instead:

Use only fill() and rect() commands. You can adjust opacity with fill() by adding a fourth value as follows:

where R , G and B stand for red , green , blue and can have values from 0 to 255 and A is optional alpha . In this case, a value of about 100 is fine so you can see through the shape being drawn.

• Some students were given cases where body parts of the judge are missing (i.e., legs appear outside the canvas, for instance). In those cases, you may be better off just failing all your attempts and wait for a new randomized case to be given to you as you probably won’t be able to get 100%.
• If your answer isn’t accepted, try increasing the number of times you have vertex() in your code. Answers including at least 40 to 50 vertices have been reported to work better.
• You should only use beginShape() , vertex(x1, y1) and endShape() in your code.
• Note that endShape() stops drawing at the last vertex, but with parameter CLOSE , it closes the shape by drawing to the first vertex.

When required to draw at the various locations of crimes and sightings, take note of the following:

When asked to draw vertices, at least one vertex must be drawn on the exact co-ordinate. Any number of vertices > 1 can be drawn to get the grader to accept the submission.

Other shapes like rectangles and triangles can be drawn around the exact co-ordinate (i.e. no edges passing through it or ending on it) provided that they are smaller than approx 10-15 px in diameter.

The names of array that need plotting may not always match up with the type of crime that is specified, for example, the instructions may refer to thefts, but the array might be called MurderSceneRecord.

When asked to use stroke(r,g,b) , also use noFill() and when asked to use fill(r,g,b) also use noStroke() . Even though these functions are not allowed according to the instructions, the grader appears to need them to correctly assess the stroke and fill properties.

When asked to draw rects around a point, do not use rectMode(CENTER) as it may confuse the grader. Simply use rect(x-5, y-5, 10, 10) or similar.

Where possible matches need to be pushed into a separate array after comparing dates and distances, take note that some conditions could be too strict resulting in zero matches, which could at first seem like an error in your code. In such cases, if you submit, the grader will accept the empty array as long as the logic was implemented correctly.

Witnesses sometimes give details relating to features or characteristics for which no properties are defined in the object arrays. It is usually not required to check for these. If problematic, get suspended to get a new case.

Some versions of this stage have misspelled words which prevent the student from solving the case. If you encounter the words plasic or nerveous , you need to make sure that your solution searches for plastic or nervous instead. Some other variations along those lines with other misspelled words may exist but haven’t been reported yet.

Probably the trickiest of all the Sleuth cases. Instructions are not always explicitly clear and require insight into objects and functions.

There is a bug in the instructions, stating that you need to: Get your car on the road by completing the </DRIVE_NAME/> function below.

The function that requires editing is called Move_Car() (or similar).

Hardest part is to implement the function to check/search a vehicle ahead by comparing the passed variable’s (detective car object) distance/km/miles property against the ones in the array. There are several ways to do this, but the grader may not always like what you’re doing. Some guidance here:

You need to check each object in the array to confirm using if-statement(s) that:

• They are in the same lane (easy, as per the instructions)
• That the difference between the distance/km/miles-properties of the car ahead and the detective vehicle less than 200
• That the car in the array is in front of (and not behind) the detective car

Note that the distance / km / miles_travelled property is increasing towards the top of the screen, opposite to the regular y-coordinate. Since debugging the array might be tricky, consider adding a text readout to each car using a variation of:

Once implemented correctly, remember the logic, as you will likely need to create similar functions things in the stages ahead.

“My suspect’s car didn’t have enough space to pull out in front of me before speeding off, so the chase wouldn’t work as expected. I deliberately got myself suspended so I could grab another case, and it worked fine.” (reported by @dannycallaghan )

More spotlight stages, which may cause Firefox users to not see the spotlights. To get it to work, refer to Spotlight effect on Firefox .

• The 1st seat in the 1st row will be seats[0][0] .
• Rows and seats relate to seats[row][seat] and not vice versa.
• You don’t need to factor in reverse counting of rows such that row numbers increase from front to back, like in a real theatre. For this case the first row is at the back of the theatre (i.e. the top of the screen.)

Many students waste time here trying to spot patterns in the audience members based on their appearance. The information about the seat numbers of gang/perpetrators is already defined in an array. It appears that any information given about appearance (hats, retro glasses, etc.) is merely to confirm that you have used the array to traverse the seats in the correct manner and not to actually identify gang members.

Here the challenge is to traverse a two-dimensional array using a normal (one-dimensional) array. There are different ways to approach this, but these work:

• Create additional variables and use a nested-for with conditionals, or
• convert the 1D array to a 2D array and compare against the 2D array.

It appears that the grader is looking for two simple nested for-loops in the solution, so more elegant ways involving math to convert your 1D iterator into two 2D co-ordinates does not work, even when all gang members are correctly identified. This, for example, was not accepted by the grader:

Tip: You can comment out the line if (frameCount % 7 == 0) in order to speed up the deck spread sequence. It might save some time during testing.

802, Stage 2

“They ask you to create an array of random integers between two values. The random() function in p5.js includes the lower number, but excludes the upper number. So if you do random(5,9) , it might well generate a 5, but never a 9.

I incremented the upper value by one so it’d actually generate values between the two numbers requested, but the puzzle actually expects you to just naively slot the two values into random and not fix the bug.” (reported by Peter Houlihan )

Tip: When comparing cards, you can’t simply compare objects against each other as the objects may be structured differently. Rather consider the properties of the different objects in the arrays and compare similar properties against one another.

Take a good look at some form of documentation to understand how the JavaScript splice() function works. MDN Array.splice() documentation

From the instructions and the variable names, it is not always clear which part of the deck the grader wants in the spliced array. Other versions may exist, but it appears that the objective is to splice the part of the deck that would remain on the table (after it was cut) into a new array. In some cases that new array is called topOfDeck which is incredibly confusing, because it is actually the bottom part of the deck we are looking for. The top card lying on the remaining part of the deck must be the target card.

When testing the reverse operation, take note that the console in Firefox Developer Edition and some other browsers may display object data live at the time of viewing it and not at the time of logging. This could create the impression that your array operations are not working. To see the array values at the time of logging them, do not use console.log(obj) , but use console.log(JSON.parse(JSON.stringify(obj))) instead.

Game Project

When implementing audio on your project, you could get an error similar to this from the browser:

The AudioContext was not allowed to start. It must be resumed (or created) after a user gesture on the page.

This is just a browser feature to prevent websites from playing sounds without user input. Ensure that your user presses a button or clicks the mouse before you attempt to play audio.

Refer to: https://developers.google.com/web/updates/2017/09/autoplay-policy-changes#webaudio

Some users have reported CORS-related problems when trying to launch the audio template provided. This could occur on the file:/// protocol due to Cross-Origin policy restrictions . Ensure that you launch the index.html file from a local web server and not through a file explorer.

Alternatively you can use the Live Server extension in VSCode.

These functions will automatically create a local server for testing and you can confirm this by checking that the address in your browser address starts with localhost or http:// and not file:///

Coursera Material

• At 3:56, the top left corner should have coordinates (4, 3) instead of (5, 3).
• At 3:56, the width of the rectangle should be 12, and not 11.
• Question 3: “triangle” is misspelled → trinagle , adding an additional error which is not an argument error. However, the spelling mistake shouldn’t be taken into account.
• The bomb exercise template is missing.
• Question 5: The question asks for two ways to reuse the variable numWays but expects three selected answers.
• Question 3: The question says the answer “No, because answer is neither a number, nor is it equal to the number 42” is correct. However the correct answer is “Yes, because answer is equal to 42” .
• Question 5: The question says the answer parseInt(a+b)*c is correct and the others are all wrong: however (a+b)*c is also correct. They both produce the same result.