1
00:00:05,150 --> 00:00:07,655
Welcome to Week 2.

2
00:00:07,655 --> 00:00:09,120
In this week we're going to be

3
00:00:09,120 --> 00:00:11,660
focusing on grid structures.

4
00:00:11,660 --> 00:00:13,980
While technically a grid

5
00:00:13,980 --> 00:00:16,715
is not a different
data structure,

6
00:00:16,715 --> 00:00:20,160
we will see that grids

7
00:00:20,160 --> 00:00:23,700
it's basically a way of
organizing the data spatially,

8
00:00:23,700 --> 00:00:25,525
and I think that that's
particularly interesting to

9
00:00:25,525 --> 00:00:28,260
us designers or people that

10
00:00:28,260 --> 00:00:31,380
operate within the design
space to really start thinking

11
00:00:31,380 --> 00:00:32,780
of how data structures

12
00:00:32,780 --> 00:00:34,720
could have a spatial
configuration.

13
00:00:34,720 --> 00:00:37,680
Let's look at the foundation or

14
00:00:37,680 --> 00:00:42,240
the basics of a grid.
So what is a grid?

15
00:00:42,240 --> 00:00:43,780
There's multiple kinds of grids

16
00:00:43,780 --> 00:00:45,240
I'm going to be
showing you here,

17
00:00:45,240 --> 00:00:47,640
orthogonal or square-like grid.

18
00:00:47,640 --> 00:00:49,340
But you could think about

19
00:00:49,340 --> 00:00:51,640
hexagonal grids and
other kinds of grids.

20
00:00:51,640 --> 00:00:54,080
We'll be linking to some of

21
00:00:54,080 --> 00:00:55,340
the documentation that you can

22
00:00:55,340 --> 00:00:57,040
read on different
kinds of grids.

23
00:00:57,040 --> 00:01:00,680
But let's start simple with
something more regular.

24
00:01:00,680 --> 00:01:04,290
This is orthogonal grid,

25
00:01:04,290 --> 00:01:07,990
and we can define
that columns and

26
00:01:07,990 --> 00:01:12,150
rows define the number of cells.

27
00:01:12,150 --> 00:01:14,610
We're going to identify
and use the word cells to

28
00:01:14,610 --> 00:01:17,500
identify each one of
the entries on a list,

29
00:01:17,500 --> 00:01:19,270
and how many cells do we

30
00:01:19,270 --> 00:01:21,130
have in X? That would
be our columns.

31
00:01:21,130 --> 00:01:23,175
How many cells do we have in Y?

32
00:01:23,175 --> 00:01:25,750
That would be our rows.

33
00:01:25,750 --> 00:01:28,270
If you think about it, this grid

34
00:01:28,270 --> 00:01:30,630
is going to contain data,

35
00:01:30,630 --> 00:01:32,530
we're not just drawing a grid or

36
00:01:32,530 --> 00:01:34,710
something that looks
like a grid graphically.

37
00:01:34,710 --> 00:01:37,150
We are thinking of
a data structure,

38
00:01:37,150 --> 00:01:38,970
something that will allow us to

39
00:01:38,970 --> 00:01:41,410
organize data in a
way that we could be

40
00:01:41,410 --> 00:01:47,770
reliably access the spatial
organization of that data.

41
00:01:47,770 --> 00:01:50,310
So we can do that with a list.

42
00:01:50,310 --> 00:01:52,450
I think that list is going
to be our main tool,

43
00:01:52,450 --> 00:01:54,690
but there's different
ways of using lists

44
00:01:54,690 --> 00:01:57,795
to create a grid.

45
00:01:57,795 --> 00:01:59,710
So we're going to
talk about probably

46
00:01:59,710 --> 00:02:02,250
at least two different
methods to use

47
00:02:02,250 --> 00:02:05,280
lists for the
construction of grids.

48
00:02:05,280 --> 00:02:10,050
You can see here on the
bottom right the cell size.

49
00:02:11,030 --> 00:02:14,130
This is often going
to be used for

50
00:02:14,130 --> 00:02:17,195
us when we really want to
start thinking of grids,

51
00:02:17,195 --> 00:02:22,930
also grids correlating to
a special environment.

52
00:02:22,930 --> 00:02:25,950
We really want to have a sense
that this piece of data,

53
00:02:25,950 --> 00:02:27,810
let's say it's a territory,

54
00:02:27,810 --> 00:02:31,850
it's a plane, or it's a section,

55
00:02:31,850 --> 00:02:34,410
it's something special, we

56
00:02:34,410 --> 00:02:36,430
might want to be
able to say, "Hey,

57
00:02:36,430 --> 00:02:38,530
the data contained
within the cell

58
00:02:38,530 --> 00:02:43,830
represents or maps to some
kind of spatial condition."

59
00:02:43,830 --> 00:02:47,850
That is not a requirement
of a data structure.

60
00:02:47,850 --> 00:02:51,210
A data structure could be
thought as a grid as well,

61
00:02:51,210 --> 00:02:54,670
but by no means requires

62
00:02:54,670 --> 00:02:59,385
a cell size to have a
correlation with anything else.

63
00:02:59,385 --> 00:03:01,970
It could be just a
piece of data that we

64
00:03:01,970 --> 00:03:06,410
organize in a grid format.

65
00:03:06,710 --> 00:03:09,270
There's great
operations that we can

66
00:03:09,270 --> 00:03:11,010
actually do by doing so.

67
00:03:11,010 --> 00:03:12,090
If you start thinking

68
00:03:12,090 --> 00:03:15,090
of entity that operates
within a list,

69
00:03:15,090 --> 00:03:15,790
we're going to be talking

70
00:03:15,790 --> 00:03:17,830
about relationships
between neighbors.

71
00:03:17,830 --> 00:03:19,820
What is the data
that is above me,

72
00:03:19,820 --> 00:03:21,680
below me, adjacent to me?

73
00:03:21,680 --> 00:03:23,110
All these operations are going

74
00:03:23,110 --> 00:03:24,430
to be incredible operations

75
00:03:24,430 --> 00:03:27,570
that are going to open up
different kinds of algorithms,

76
00:03:27,570 --> 00:03:29,750
different kind of computation

77
00:03:29,750 --> 00:03:31,770
that we could
ultimately exercise

78
00:03:31,770 --> 00:03:36,550
once we start organizing
our data in this fashion.

79
00:03:36,550 --> 00:03:38,150
So this is a foundation
of what we're

80
00:03:38,150 --> 00:03:40,540
going to be doing throughout
this second week.

81
00:03:40,540 --> 00:03:42,960
So let's get started.

82
00:03:42,960 --> 00:03:44,610
I'll see you in the next video,

83
00:03:44,610 --> 00:03:47,910
where we're going to start
constructing our first grid.