Bonus: Coloring markers

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來自 University of California San Diego 的課程

面向对象 Java 程序设计

3408 個評分

University of California San Diego

面向对象 Java 程序设计

3408 個評分

課程 3（共 4 門，Specialization Object Oriented Programming in Java）

你是否曾想过大型软件项目诸如Google搜索引擎是如何开发的？本课程将帮助你超越平凡编程，去学习设计和开发更加复杂的Java软件项目（尽管还没到Google搜索引擎那种级别！）我们会探索如何将一个大的项目分解为层次结构的类，以及如何通过现有的库来增强项目的功能。我们也会探究一些搜索和排序的核心算法。在学习过程中，你将要开发一个令人兴奋的有着图形用户界面（GUI）的交互式应用程序。我们期待本课能启发你去创造。你即将进入课程项目，每节课所涉及的原理概念都设计成可直接应用于项目功能拓展。视频课程同时包括核心课程内容和现实中的软件工程师的来信和故事，与正在学习本课的真实学生之间的对话，以及一些你遇到困惑时可去观看的补充视频。（本课程若发现字幕错误请发送邮件到caesarguangli@hotmail.com，谢谢！）

從本節課中

Graphical output: Creating GUIs and Displaying Data

Now that you have the tools to write and trace object oriented code, let’s get back to developing the project! In this first (real) part of the project, you will create an interactive graphical map that will display geospatial data. This is a highly interactive week, so make sure you’ve got Eclipse loaded up! We encourage you to play around as you watch the videos. Some of the code that we use in the videos is in the demos package in the starter code you set up for this course. Open it up and experiment with it while you're watching the videos. We also encourage you to dive right into the programming project, even before watching the videos, if you want. The programming assignment instructions are in the last lesson of this week - you can watch a video walkthrough of the instructions and also read the step-by-step directions in the accompanying reading. There’s lots of room for creativity, too, so have fun!

Core: Why Processing?1:08

Support: Using Documentation7:08

In the Real World: Documentation3:24

Core: Setting up map visualization9:49

Core: Adding markers5:27

Core: Using live data11:18

Bonus: Visualizing life expectancy0:29

Bonus: Setting up the map4:48

Bonus: Representing data8:53

Bonus: Coloring markers11:42

Support: ArrayLists and Generics8:54

與講師見面

Mia Minnes
Assistant Teaching Professor
Computer Science and Engineering
Leo Porter
Assistant Teaching Professor
Computer Science and Engineering
Christine Alvarado
Associate Teaching Professor
Computer Science and Engineering

[MUSIC]

All right, we're in step three of three of this

project to visualized average life expectancy around the world.

And in this video, we're going to build on what we've done in the previous two so,

we've all set up the map and we've ready read in the data from this CSB file.

Which tells us the average life expectancy for each country, and

now we want to translate that data into the colors of this map.

And so, hopefully you've implemented everything that we've done so

far in Eclipse, and you're ready to get going and do this last piece with us.

And so the data we need in order to annotate the map with this information is

not only the life expectancy for each country.

But also how the countries look on the global map, itself,

what their coordinates are and how they occupy space in the map.

So that information is located in a file in the data directory

of the unfolding maps library.

And it's called countries.geo.json

Json is an extension that indicates that we've got formatted text.

Now, in order to pull all of this information together,

the geographical information about the countries.

As well as their life expectancies, we want to design some objects or

use some predefined objects.

That help us organize both geographic locations and

features or properties of these locations.

So what we're going to think about are the underlying groupings of the properties and

locations as distinct from their visual representations on the map.

And in fact unfolding as a library has some classes

that are able to manage that distinction for us.

So when we're just thinking about a particular location in the world and

its associated properties, we want to define or use the type feature

to use objects of type feature for talking about locations with properties.

But then when we want to translate those into some sort of visual representation on

the map, then we could use the marker class.

In the unfolding library, which then lets us style how these

properties might impact what we display on the map.

So let's think about how we are going to store all of this information,

because we have a lot of countries, and so

we want to have a list of features, and also a list of markers.

So this is another example of an abstract data type.

In the previous video, we saw the abstract data type, map,

which let us store pairs of pieces of information, pairs of objects.

And now we got lists and lists are relevant whenever we want

a collection of objects that are ordered in some way.

Okay, so we've already seen lots of examples of lists for example, when you

think about array lists then that's a particular implementation of a list.

And we'll talk more about this data type and it's implementations later but for now

we want to think about a list of features each one associated with a country.

So in our in our applet, we're going to think about all of the countries,

each of the countries has associated its life expectancy and

some other pieces of information.

And so, each of that is going to be a feature.

We're going to have a feature object for each country and we'll store them all,

all of those feature objects, in a list.

Similarly, we'll have a marker object, a different marker object for

each one of our markers, and for each one of our countries.

And so in our class we need to declare a list of features and

a list of markers, and this is how we do it.

Now, Instead of just declaring that's not good enough.

If we want to work with these objects, we've declared them, but

now we need to build them.

And so we need to create one feature and one marker per country.

So here's the code that we might include in our setup method to do so.

We're not going to go into the details of how this goes about.

We're using helper methods that are provided by the UnfoldingMaps library.

And these are standard methods that you will use in your project and

throughout when you want to create features and

markers for a list of countries that you already have.

Once we have these features and

markers, we want to add them to the map, which means that we display the markers.

But not only do we want to add them to the map, we want to manipulate them.

And what we'd like to do is shade them based on the colors,

based on the life expectancy.

Okay, so let's dig deeper into what this shading will look like and

we've defined a new helper method that will let us do that in some detail.

Okay, so this is our helper method.

Remember that our rule of thumb is that if they are private,

unless there is a reason to open it up to the world.

We're going to keep it private and

what we're going to is go through all of the markers that we created.

Remember there's one marker for each country and what we'd like to do is for

each of the markers, for each of the countries and their associated markers.

We're going to decide how to color the marker and

the coloring is going to depend on the life expectancy.

Now that life expectancies a number.

A number is typically between 45 and

90, and that number is stored in the map data structure, right.

We can access it by saying,

hey map I would like the value associated with the key country.

And so we give, if we pass as an argument to the get method of the map,

the countryID, or the string that has that countryID.

And then the map object gives us back the value associated with that key,

and that's a float.

Once we have that number, well we'd like to translate that number to a color.

And this is where I apologize, because not only do we have

two ways of using the map in this sequence of videos, we now are including a third.

So let's think back to all of the maps that we've used.

We've got the global map, the picture, the map of the world, we've got map the data

structure, that associates keys with values, and now we've got map the method.

And this is a built in method in the library that's a really useful one.

So this method, map, let's us take a number in a pre-defined range and

map it into its comparable location in a different range of values.

So in this particular instance, we're taking the number which is life expectancy

of the country that we're currently focusing on.

And we know that the life expectancy ranges from between 40 in countries

with the lowest average life expectancy to 90 at the top end.

And we'd like to translate that to something to do with color.

And if you think back to a couple of videos ago when we first introduced

colors and the RGB codes for colors,

remember that those RGB channels had minimum value zero and maximum value 255.

So we'd like to translate the range 40 to 90 over to the range 0 to 255,

so we're in a range of numbers that's more compatible with color codes.

And this map method lets us do just that.

Okay, so we invoke it.

What we get back from it is a float and we're going to cast it to

an integer because for the RGB colors, we just deal with integers.

So in the RGB coding of colors, we want an integer between 0 and

255 for each of the 3 color channels: red, green, and blue.

All right, so we've translated the life expectancy of the color of the country

that we're focusing on to some integer value between 0 and 255.

And what we'd like to do is countries that have really low life expectancy,

relatively speaking, are going to be colored bright red.

So bright red means that the red channel should be as high as possible,

somewhere around 255.

And if we want the countries that have

very high life expectancy to be colored bright blue, then for

those the blue should be high 255 and all the other channels should be pretty low.

And so, we can define the color of the marker appropriately, so

the red channel is going to be the first argument of the color method.

And it's going to be 255 minus the number that we just calculated,

so if the color level that we calculated is 0.

Then the color that we're setting our marker to is going to be very close

to 255, it's going to be 255.

So it's going to be a very very red marker and

the other two arguments are going to be very low.

And so, we'll see that bright, bright color.

And on the other side, if the color level that we calculated corresponds

to a really high life expectancy, then we're going to get a large number.

Which means that the red channel, that first argument to the color method,

will be very low.

And so, our marker will be a bright blue.

Now think back about this logic that you see in this code and

we have an if else in there.

And if that if else is dependent on the conditional statement

If lifeExpmap.containsKey(countryID) well what on Earth does that mean?

It could be that the marker that we're looking at

currently has a countryID that doesn't show up in the file of life expectancies.

It could be that, when the world bank put together all of their data on life

expectancies, they weren't able to reach the statistics of one particular country.

And we don't want our code to crash just because we don't have information

about a particular country.

So what we're going to do is check.

We're going to ask our map, the map that associates countries with life

expectancy if they actually have a value of life expectancy for

the country that we care about.

And if there is such a life expectancy for the country we care about,

then we go ahead and do our calculation that we just did.

And we color the marker appropriately but if we don't,

then we want to have some sort of default setting, for what that colors going to be.

And remember when Christine was talking in her supplementary video about color codes.

She mentioned that if we said all three colors are GNB to the same value,

then what we get is a shade of gray.

So our default color for the marker is just going to be a shade of gray If we

don't happen to have information about the life expectancy of a particular country.

All right, we've done it, what we've done now if we've colored the whole

world based on the data in the life expectancy file.

And what's really powerful about the techniques that we've gone through in

these three videos, is that really most of what we were talking

about doesn't depend on the fact that we're talking about life expectancies.

Any time we have a data file that tells us some values associated with country IDs.

We could do exactly the same process, and

color the world based on all sorts of other information and data.

So I hope now you're excited about doing these kinds of projects.

What you might want to do,

is look for additional data sets about things that you care about.

Or you could also plunge right back into your project and

think about how to use these techniques when you're customizing your markers and

displaying the data that you're working with in the project.

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