I'd like to average the data by matlab - matlab

I'd like to average the data
However, length of the data is different each other
The number of data is seven
How can i solve this problem by matlab?
x_1= 6.45805700000000
6.45805700000000
6.53780000000000
6.57767200000000
6.71722200000000
6.87670800000000
7.17574400000000
7.43490900000000
7.81368900000000
8.31208300000000
8.79054100000000
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10.0066220000000
10.7442450000000
11.5018040000000
12.2992340000000
13.1166000000000
13.9140310000000
14.7313970000000
15.5088910000000
16.2465140000000
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17.6220810000000
18.1204750000000
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19.1571350000000
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20.1937940000000
20.3732160000000
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20.7719310000000
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20.7519950000000
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20.7121240000000
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20.4330230000000
20.3333440000000
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18.6388050000000
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17.9011820000000
17.6021460000000
17.2233660000000
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15.6883130000000
15.3892770000000
15.0503690000000
14.7114610000000
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14.0735170000000
13.8542230000000
13.6947370000000
13.4355730000000
13.2960220000000
13.1564720000000
13.0567930000000
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12.7776930000000
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12.7178850000000
12.7178850000000
12.5982710000000
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12.5583990000000
12.5783350000000
12.5384630000000
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12.3789770000000
12.3191700000000
12.2593630000000
12.1796200000000
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11.9802620000000
11.8606480000000
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11.7011620000000
11.6612900000000
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11.4818680000000
11.3622540000000
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11.2625750000000
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10.4053370000000
10.3255940000000
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10.2259160000000
10.1063010000000
10.0664290000000
9.92687900000000
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9.32880600000000
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9.06964200000000
8.96996300000000
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7.89343200000000
7.85356000000000
7.75388100000000
7.71401000000000
7.67413800000000
7.61433100000000
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7.59439500000000
7.47478100000000
7.45484500000000
7.41497400000000
7.35516600000000
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7.13587300000000
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6.99632300000000
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6.87670800000000
6.81690100000000
6.73715800000000
6.69728600000000
6.63747900000000
6.59760700000000
6.53780000000000
6.45805700000000
6.49792900000000
6.39825000000000
6.37831400000000
6.27863500000000
6.25870000000000
x_2 = 6.25870000000000
6.27863500000000
6.29857100000000
6.25870000000000
6.25870000000000
6.31850700000000
6.43812100000000
6.57767200000000
6.81690100000000
7.03619400000000
7.35516600000000
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8.23234000000000
8.71079800000000
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12.0201340000000
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13.4754440000000
14.2130670000000
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19.3564920000000
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19.4761070000000
19.5558500000000
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19.4960430000000
19.4561710000000
19.3963640000000
19.3166210000000
19.1371990000000
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18.6786770000000
18.4793190000000
18.2400900000000
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15.2297910000000
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12.9969860000000
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12.6780140000000
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7.33523100000000
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7.19568000000000
7.11593700000000
7.09600100000000
7.05613000000000
6.97638700000000
6.91658000000000
6.87670800000000
6.79696500000000
6.81690100000000
6.73715800000000
6.65741500000000
6.61754300000000
6.51786400000000
6.51786400000000
6.43812100000000
6.43812100000000
6.37831400000000
x_3=6.37831400000000
6.37831400000000
6.43812100000000
6.37831400000000
6.41818600000000
6.47799300000000
6.63747900000000
6.83683700000000
7.07606600000000
7.41497400000000
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8.17253200000000
8.77060500000000
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10.6046950000000
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8.59118300000000
8.51144000000000
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8.35195400000000
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7.05613000000000
7.03619400000000
6.93651500000000
6.89664400000000
6.93651500000000
6.83683700000000
x_4=6.83683700000000
6.85677200000000
6.85677200000000
6.91658000000000
7.01625800000000
7.15580900000000
7.31529500000000
7.51465200000000
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x_5=6.45805700000000
6.47799300000000
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6.53780000000000
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x_6=6.83683700000000
6.83683700000000
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11.3622540000000
11.3223820000000
11.2227030000000
11.2027680000000
11.1828320000000
11.0632170000000
10.9834740000000
10.9436030000000
10.8638600000000
10.8239880000000
10.7641810000000
10.7043740000000
10.6445660000000
10.6645020000000
10.5448880000000
10.5249520000000
10.4452090000000
10.4252730000000
10.3455300000000
10.2857230000000
10.2259160000000
10.2458510000000
10.1461730000000
10.1262370000000
10.0464940000000
10.0066220000000
9.94681500000000
9.90694300000000
9.86707200000000
9.74745700000000
9.76739300000000
9.70758600000000
9.68765000000000
9.60790700000000
9.56803600000000
9.50822800000000
9.44842100000000
9.36867800000000
9.38861400000000
9.26899900000000
9.24906300000000
9.18925600000000
9.14938500000000
9.04970600000000
9.02977000000000
8.93009100000000
8.89022000000000
8.83041200000000
8.77060500000000
8.75066900000000
8.69086200000000
8.65099100000000
8.63105500000000
8.57124800000000
8.59118300000000
8.57124800000000
8.49150500000000
8.47156900000000
8.45163300000000
8.41176200000000
8.37189000000000
8.35195400000000
8.33201800000000
8.29214700000000
8.29214700000000
8.25227500000000
8.27221100000000
8.21240400000000
8.25227500000000
8.23234000000000
8.19246800000000
8.15259700000000
8.17253200000000
8.07285400000000
8.05291800000000
8.03298200000000
7.97317500000000
7.91336800000000
7.95323900000000
7.85356000000000
7.81368900000000
7.81368900000000
7.73394600000000
7.67413800000000
7.61433100000000
7.59439500000000
7.51465200000000
7.43490900000000
7.35516600000000
7.39503800000000
7.25548800000000
7.21561600000000
7.17574400000000
7.03619400000000
7.01625800000000
6.99632300000000
6.95645100000000
6.89664400000000
6.87670800000000
6.83683700000000
6.81690100000000
6.73715800000000
x_7=6.73715800000000
6.77702900000000
6.75709400000000
6.79696500000000
6.83683700000000
6.93651500000000
7.05613000000000
7.27542300000000
7.53458800000000
7.87349600000000
8.31208300000000
8.83041200000000
9.34874200000000
9.96675100000000
10.6645020000000
11.3821900000000
12.1397480000000
12.9571140000000
13.7744800000000
14.5719110000000
15.3294690000000
16.0670920000000
16.8047150000000
17.4825310000000
18.1204750000000
18.6986120000000
19.2169420000000
19.7153360000000
20.1140510000000
20.3931520000000
20.6523160000000
20.8915450000000
21.0510320000000
21.1706460000000
21.2703250000000
21.3899390000000
21.3500680000000
21.3500680000000
21.3301320000000
21.2503890000000
21.1706460000000
21.1706460000000
21.0310960000000
20.9114810000000
20.7519950000000
20.6523160000000
20.4728950000000
20.2536010000000
20.0941150000000
19.8548860000000
19.5757860000000
19.3365570000000
19.0175840000000
18.6786770000000
18.3597040000000
18.0008610000000
17.6619530000000
17.2632380000000
16.9243300000000
16.6851010000000
16.2465140000000
15.9873490000000
15.6484420000000
15.3892770000000
15.1699830000000
14.9307540000000
14.7712680000000
14.6117820000000
14.4323600000000
14.3725530000000
14.2529390000000
14.1333240000000
14.0735170000000
14.1133880000000
13.9738380000000
13.9539020000000
13.9339660000000
13.8542230000000
13.8940950000000
13.8741590000000
13.8542230000000
13.7944160000000
13.8143520000000
13.7744800000000
13.7146730000000
13.6548660000000
13.5551870000000
13.5153160000000
13.4156370000000
13.3757650000000
13.2960220000000
13.1365360000000
13.0368570000000
12.9571140000000
12.8574360000000
12.7378210000000
12.6979500000000
12.5583990000000
12.4786560000000
12.3989130000000
12.2992340000000
12.1596840000000
12.0998770000000
12.0400700000000
11.9403910000000
11.8407120000000
11.7210970000000
11.6612900000000
11.5416760000000
11.4818680000000
11.3821900000000
11.2825110000000
11.2625750000000
11.1628960000000
11.0632170000000
11.0632170000000
10.9635390000000
10.9037310000000
10.7841170000000
10.6844380000000
10.6645020000000
10.6046950000000
10.5050160000000
10.4850800000000
10.3854020000000
10.3455300000000
10.2657870000000
10.1661080000000
10.0863650000000
10.0863650000000
10.0265580000000
9.98668600000000
9.92687900000000
9.92687900000000
9.86707200000000
9.78732900000000
9.74745700000000
9.74745700000000
9.64777900000000
9.64777900000000
9.60790700000000
9.58797100000000
9.46835700000000
9.44842100000000
9.40854900000000
9.34874200000000
9.30887100000000
9.30887100000000
9.30887100000000
9.24906300000000
9.20919200000000
9.16932000000000
9.14938500000000
9.10951300000000
9.10951300000000
9.02977000000000
9.02977000000000
8.95002700000000
8.91015500000000
8.83041200000000
8.85034800000000
8.79054100000000
8.79054100000000
8.77060500000000
8.75066900000000
8.73073400000000
8.67092600000000
8.61111900000000
8.59118300000000
8.51144000000000
8.45163300000000
8.43169700000000
8.35195400000000
8.19246800000000
8.23234000000000
8.11272500000000
8.09278900000000
8.07285400000000
7.95323900000000
7.89343200000000
7.91336800000000
7.81368900000000
7.75388100000000
7.71401000000000
7.65420300000000
7.61433100000000
7.61433100000000
7.59439500000000
7.63426700000000
7.59439500000000
7.63426700000000
7.57446000000000
Length of the data array is different.
I'd like to average this 7 data.


If you need to find the mean of values which are stored in several vectors, first sum all the values of both vectors. Then use length() to find out how many entries are in each vector. Add the lengths and you will have the total number of entries. Then you can divide your sum total by the number of entries to get the mean.
Exactly how you do this will depend on your data (how many vectors you have, whether you always have the same number).
So if your variables were a, b, c, d, e, f, g:
sumOfVectors = sum(a) + sum(b) + ... etc
numberOfItems = length(a) + length(b) + ... etc
averageAllData = sumOfVectors/numberOfItems
You could also potentially make this work for an arbitrary number of items by using a loop.


Use mean and just concatenate all your vectors:
mean([x1 x2 x3 x4 x5 x6 x7]);
If they're column vectors concatenate vertically:
mean([x1; x2; x3; x4; x5; x6; x7]);

Related

What is l and v1 and what type of values it holds?

the code below generated from intel GPA tool
and i have been studying these HLSL code and i have trouble understanding in what is l register used in the code and what values it holds?
how do we know the values in registers what values they are using?
dcl_constantbuffer CB2[16], immediateIndexed
dcl_constantbuffer CB12[13], immediateIndexed
dcl_sampler s6, mode_default
dcl_resource_texture2d (float,float,float,float) t6
dcl_input_ps linear v1.xy
dcl_output o0.xyzw
dcl_temps 6
mov r0.x, cb2[15].z
mov r0.yw, l(0,0,0,0)
add r0.xy, r0.xyxx, v1.xyxx
mad r1.xy, r0.xyxx, l(2.000000, -2.000000, 0.000000, 0.000000), l(-1.000000, 1.000000, 0.000000, 0.000000)
sample_l r2.xyzw, r0.xyxx, t6.xyzw, s6, l(0.000000)
mul r1.xy, r1.xyxx, cb12[0].xyxx
mov r1.z, l(1.000000)
mul r1.xyz, r2.xxxx, r1.xyzx
mov r0.z, -cb2[15].z
add r0.xy, r0.zwzz, v1.xyxx
mad r0.zw, r0.xxxy, l(0.000000, 0.000000, 2.000000, -2.000000), l(0.000000, 0.000000, -1.000000, 1.000000)
sample_l r2.xyzw, r0.xyxx, t6.xyzw, s6, l(0.000000)
mul r0.xy, r0.zwzz, cb12[0].xyxx
mov r0.z, l(1.000000)
mul r0.xyz, r2.xxxx, r0.xyzx
mad r2.xy, v1.xyxx, l(2.000000, -2.000000, 0.000000, 0.000000), l(-1.000000, 1.000000, 0.000000, 0.000000)
mul r2.xy, r2.xyxx, cb12[0].xyxx
sample_l r3.xyzw, v1.xyxx, t6.xyzw, s6, l(0.000000)
mov r2.z, l(1.000000)
mad r3.yzw, r2.xxyz, r3.xxxx, -r0.xxyz
dp3 r0.w, r3.yzwy, r3.yzwy
sqrt r0.w, r0.w
mad r3.yzw, r2.xxyz, r3.xxxx, -r1.xxyz
dp3 r1.w, r3.yzwy, r3.yzwy
sqrt r1.w, r1.w
lt r0.w, r0.w, r1.w
movc r0.xyz, r0.wwww, r0.xyzx, r1.xyzx
mad r0.xyz, -r2.xyzx, r3.xxxx, r0.xyzx
dp3 r0.x, r0.xyzx, r0.xyzx
sqrt r0.x, r0.x
mov r1.y, cb2[15].w
mov r1.xz, l(0,0,0,0)
add r0.yz, r1.xxyx, v1.xxyx
mad r1.xy, r0.yzyy, l(2.000000, -2.000000, 0.000000, 0.000000), l(-1.000000, 1.000000, 0.000000, 0.000000)
sample_l r4.xyzw, r0.yzyy, t6.xyzw, s6, l(0.000000)
mul r5.xy, r1.xyxx, cb12[0].xyxx
mov r5.z, l(1.000000)
mul r0.yzw, r4.xxxx, r5.xxyz
mad r3.yzw, r2.xxyz, r3.xxxx, -r0.yyzw
dp3 r1.x, r3.yzwy, r3.yzwy
sqrt r1.x, r1.x
mov r1.w, -cb2[15].w
add r1.yz, r1.zzwz, v1.xxyx
mad r3.yz, r1.yyzy, l(0.000000, 2.000000, -2.000000, 0.000000), l(0.000000, -1.000000, 1.000000, 0.000000)
sample_l r4.xyzw, r1.yzyy, t6.xyzw, s6, l(0.000000)
mul r5.xy, r3.yzyy, cb12[0].xyxx
mov r5.z, l(1.000000)
mul r1.yzw, r4.xxxx, r5.xxyz
mad r3.yzw, r2.xxyz, r3.xxxx, -r1.yyzw
dp3 r2.w, r3.yzwy, r3.yzwy
sqrt r2.w, r2.w
lt r1.x, r1.x, r2.w
movc r0.yzw, r1.xxxx, r0.yyzw, r1.yyzw
mad r0.yzw, -r2.xxyz, r3.xxxx, r0.yyzw
dp3 r0.y, r0.yzwy, r0.yzwy
sqrt r0.y, r0.y
lt r0.xy, r0.xyxx, cb12[12].wwww
and r0.x, r0.y, r0.x
and o0.xyzw, r0.xxxx, l(0x3f800000, 0x3f800000, 0x3f800000, 0x3f800000)
ret
we can see l is being used many times in above code with different values in brackets like
mad r1.xy, r0.xyxx, l(2.000000, -2.000000, 0.000000, 0.000000), l(-1.000000, 1.000000, 0.000000, 0.000000)
and
and o0.xyzw, r0.xxxx, l(0x3f800000, 0x3f800000, 0x3f800000, 0x3f800000)
i know about and operation but how l getting these values and what could be the final output
i'm very new to this please pardon if it seams very dumb thanks in advance

Reading shader bytecode is really not an easy task, for such a complex shader it needs a little patience. To get a deeper understanding I'll recommend to read the documentation, so you can easily lookup operators or registers.
To your questions:
v1 stands for a input color register (docs), as there are to components xy and a texture is declared I would assume that it is describing some kind of texture coordinate passed to the shader
l(...) seems to be a short form for a constant, I didn't find any documentation on this, but it is most probably an inline constant so
mad r1.xy, r0.xyxx, l(2.000000, -2.000000, 0.000000, 0.000000), l(-1.000000, 1.000000, 0.000000, 0.000000) =>
r1.xy = r0.xy * float2(2,-2) + float2(-1, 1)
and o0.xyzw, r0.xxxx, l(0x3f800000, 0x3f800000, 0x3f800000, 0x3f800000) is a bit special to understand. It and's the registers componentwise, two lines above there is a lt, which means that now in r0.x is a boolean in the form 0xFFFFFFFF (true) or 0x00000000(false). By an and with 0x3f800000 (which is the floating point representation of 1.0), it essentially transforms the boolean to a float either 1.0 or 0.0. So the output of the shader is 1.0 or 0.0 in each channel regarding the boolean value of r0.

add rows with strings between a matrix in matlab

I have two matrices that i have concatenated vertically. However, i want to insert 2 or more rows in between them with a string in those rows.. how do i go about doing that.?
Basically this is what i have;
A = 0.7363 0.8217 0.7904 0.5144 0.5341
0.3947 0.4299 0.9493 0.8843 0.0900
0.6834 0.8878 0.3276 0.5880 0.1117
0.7040 0.3912 0.6713 0.1548 0.1363
0.4423 0.7691 0.4386 0.1999 0.6787
0.0196 0.3968 0.8335 0.4070 0.4952
0.3309 0.8085 0.7689 0.7487 0.1897
0.4243 0.7551 0.1673 0.8256 0.4950
0.2703 0.3774 0.8620 0.7900 0.1476
0.1971 0.2160 0.9899 0.3185 0.0550
But i want it to be;
A = 0.7363 0.8217 0.7904 0.5144 0.5341
0.3947 0.4299 0.9493 0.8843 0.0900
0.6834 0.8878 0.3276 0.5880 0.1117
0.7040 0.3912 0.6713 0.1548 0.1363
0.4423 0.7691 0.4386 0.1999 0.6787
MESH PART
0.0196 0.3968 0.8335 0.4070 0.4952
0.3309 0.8085 0.7689 0.7487 0.1897
0.4243 0.7551 0.1673 0.8256 0.4950
0.2703 0.3774 0.8620 0.7900 0.1476
0.1971 0.2160 0.9899 0.3185 0.0550

Assuming CATIA can read the output correctly, you could simply set A as a cell variable, which can contain both numbers and strings of characters. This is achieved by using the brackets { }, as opposed to [ ] for numeric matrices. In your particular case, I would write:
A = {0.7363 0.8217 0.7904 0.5144 0.5341; ...
0.3947 0.4299 0.9493 0.8843 0.0900; ...
0.6834 0.8878 0.3276 0.5880 0.1117; ...
0.7040 0.3912 0.6713 0.1548 0.1363; ...
0.4423 0.7691 0.4386 0.1999 0.6787; ...
'MESH' 'PART' '-' '-' '-' ; ...
0.0196 0.3968 0.8335 0.4070 0.4952; ...
0.3309 0.8085 0.7689 0.7487 0.1897; ...
0.4243 0.7551 0.1673 0.8256 0.4950; ...
0.2703 0.3774 0.8620 0.7900 0.1476; ...
0.1971 0.2160 0.9899 0.3185 0.0550};
The '-'s next to MESH and PART are for consistency with the matrix (in this case, cell) size. I hope this works for you.

Can Lsqnonlin iterative output display current point for the algorithm?

My optimization using "Lsqnonlin" is running into an error in the 18th iteration. I was wondering if I could see what is the current input point that the algorithm is using for each iteration. It may help me diagnose what's going wrong. Thanks
EDIT: First Pass at Solution
I created myoutput.m
function stop = myoutput(x,optimValues,state)
stop = false;
indicator = x;
disp(indicator)
Then added OutPut Fcn to me options
options = optimset('disp','iter-detailed','MaxFunEvals',1000,'TolFun',1e-5,'OutputFcn',#myoutput);
HW1Fparams= lsqnonlin(HW1Fobjfun4,x0,lb,ub,options)
But I am getting hideous looking results like these:
I'd appreciate it if someone can help me make it look nicer. Below the break is the rest of the original question.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Full code below. I am using some Financial Toolbox functions. The idea is to calibrate the Hull White One Factor Model to market data. It's a straightforward exercise and I must be specifying things incorrectly because it's totally tripping me up.
ValuationDate = '10-01-2014';
Settle = datenum(ValuationDate);
CurveDates = [735874;
735882;
735906;
735936;
735950;
736040;
736133;
736224;
736314;
736424;
736606;
736788;
736971;
737153;
737336;
737518;
737701;
737884;
738069;
738251;
738433;
738615;
738797;
738979;
739162;
739345;
739528;
739710;
739893;
740075;
740260;
740442;
740624;
740806;
740989;
741171;
741354;
741536;
741719;
741901;
742084;
742269;
742451;
742633;
742815;
742997;
743180;
743362;
743545;
743728;
743911;
744093;
744278;
744460;
744642;
744824;
745006;
745189;
745372;
745554;
745737;
745919;
746102;
746284;
746469;
746651;
746833;
747015;
747198;
747380;
747563;
747745;
747928;
748111;
748296;
748478;
748660;
748842;
749024;
749206;
749389;
749572;
749755;
749937;
750120;
750302;
750487];
ZeroRates = 1.0e-03*[0.0172;
0.0188;
0.0191;
0.0221;
0.0249;
0.0244;
0.0269;
0.0333;
0.0423;
0.0571;
0.0789;
0.1021;
0.1253;
0.1435;
0.1617;
0.1749;
0.1881;
0.1973;
0.2064;
0.2158;
0.2253;
0.2311;
0.2370;
0.2429;
0.2488;
0.2547;
0.2607;
0.2640;
0.2672;
0.2706;
0.2738;
0.2772;
0.2807;
0.2842;
0.2877;
0.2913;
0.2948;
0.2964;
0.2979;
0.2995;
0.3011;
0.3026;
0.3043;
0.3060;
0.3077;
0.3095;
0.3112;
0.3118;
0.3125;
0.3132;
0.3138;
0.3146;
0.3152;
0.3160;
0.3167;
0.3175;
0.3183;
0.3186;
0.3189;
0.3192;
0.3196;
0.3199;
0.3202;
0.3206;
0.3209;
0.3213;
0.3217;
0.3217;
0.3216;
0.3216;
0.3216;
0.3216;
0.3216;
0.3216;
0.3216;
0.3216;
0.3216;
0.3217;
0.3217;
0.3218;
0.3218;
0.3219;
0.3219;
0.3220;
0.3220;
0.3221;
0.3221];
Compounding = 2;
RateSpec = intenvset('Compounding', 2,'ValuationDate', ValuationDate,'StartDates', ValuationDate,'EndDates', CurveDates,'Rates', ZeroRates);
InstrumentMaturity = datenum('12-Sep-2044');
SwaptionBlackVol = [ 0.5940 0.5550 0.4450 0.3710 0.3400 0.3110 0.2910 0.2750 0.2630 0.2520 0.2250 0.2140 0.2080 0.2050;
0.5630 0.5470 0.4420 0.3690 0.3360 0.3090 0.2900 0.2740 0.2630 0.2520 0.2260 0.2150 0.2090 0.2060;
0.5760 0.5330 0.4400 0.3730 0.3410 0.3150 0.2970 0.2820 0.2700 0.2590 0.2330 0.2220 0.2170 0.2140;
0.5840 0.5020 0.4240 0.3730 0.3480 0.3240 0.3060 0.2920 0.2810 0.2710 0.2430 0.2300 0.2230 0.2190;
0.5630 0.4750 0.4100 0.3700 0.3450 0.3230 0.3070 0.2940 0.2830 0.2740 0.2470 0.2330 0.2260 0.2210;
0.5510 0.4520 0.3980 0.3660 0.3410 0.3220 0.3070 0.2950 0.2850 0.2760 0.2500 0.2360 0.2290 0.2240;
0.4630 0.4010 0.3660 0.3440 0.3250 0.3100 0.2990 0.2890 0.2790 0.2720 0.2470 0.2320 0.2260 0.2210;
0.4230 0.3750 0.3480 0.3290 0.3140 0.3030 0.2930 0.2840 0.2760 0.2690 0.2420 0.2300 0.2240 0.2190;
0.3700 0.3470 0.3280 0.3110 0.2960 0.2880 0.2800 0.2730 0.2680 0.2620 0.2360 0.2240 0.2190 0.2150;
0.3420 0.3250 0.3100 0.2970 0.2850 0.2770 0.2700 0.2640 0.2590 0.2540 0.2280 0.2180 0.2140 0.2110;
0.3230 0.3010 0.2900 0.2810 0.2720 0.2650 0.2590 0.2540 0.2500 0.2470 0.2230 0.2130 0.2090 0.2060;
0.3010 0.2860 0.2760 0.2670 0.2580 0.2530 0.2480 0.2450 0.2420 0.2390 0.2160 0.2060 0.2030 0.2000;
0.2850 0.2750 0.2650 0.2560 0.2480 0.2440 0.2400 0.2370 0.2350 0.2320 0.2100 0.2000 0.1970 0.1940;
0.2710 0.2600 0.2510 0.2440 0.2380 0.2340 0.2310 0.2290 0.2260 0.2240 0.2040 0.1940 0.1910 0.1890;
0.2580 0.2470 0.2400 0.2350 0.2300 0.2270 0.2240 0.2210 0.2190 0.2170 0.1980 0.1890 0.1860 0.1840;
0.2460 0.2370 0.2320 0.2270 0.2240 0.2210 0.2180 0.2150 0.2130 0.2110 0.1980 0.1840 0.1820 0.1800;
0.2040 0.1980 0.1950 0.1920 0.1900 0.1890 0.1890 0.1880 0.1880 0.1870 0.1720 0.1660 0.1640 0.1620;
0.1790 0.1750 0.1740 0.1730 0.1730 0.1710 0.1710 0.1700 0.1690 0.1690 0.1530 0.1510 0.1500 0.1480;
0.1650 0.1650 0.1660 0.1670 0.1680 0.1670 0.1670 0.1680 0.1680 0.1680 0.1550 0.1580 0.1560 0.1530;
0.1530 0.1570 0.1590 0.1620 0.1640 0.1650 0.1660 0.1670 0.1680 0.1690 0.1560 0.1650 0.1620 0.1590];
SwaptionExerciseDates = cellstr(['1M ';'2M ';'3M '; '6M ';'9M ';'1Y ';'18M';'2Y ';'3Y ';'4Y ';'5Y ';'6Y ';'7Y ';'8Y ';'9Y ';'10Y';'15Y';'20Y';'25Y';'30Y']);
SwaptionTenors = cellstr(['1Y ';
'2Y ';
'3Y ';
'4Y ';
'5Y ';
'6Y ';
'7Y ';
'8Y ';
'9Y ';
'10Y';
'15Y';
'20Y';
'25Y';
'30Y']);
testmat = zeros(length(SwaptionExerciseDates),1);
for i = 1:length(SwaptionExerciseDates)
if SwaptionExerciseDates{i}(end)=='Y'
testmat(i) = addtodate(Settle,str2double(SwaptionExerciseDates{i}(1:end-1)),'year');
elseif SwaptionExerciseDates{i}(end)=='M'
testmat(i)=addtodate(Settle,str2double(SwaptionExerciseDates{i}(1:end-1)),'month');
end
end
EurExDates= testmat;
EurExDatesFull = repmat(testmat,1,length(SwaptionTenors));
testmat2 = zeros(length(SwaptionExerciseDates),length(SwaptionTenors));
for i = 1:size(EurExDatesFull,1)
for j = 1:size(EurExDatesFull,2)
if SwaptionTenors{j}(end)=='Y'
testmat2(i,j) = addtodate(EurExDatesFull(i,j),str2double(SwaptionTenors{j}(1:end-1)),'year');
elseif SwaptionTenors{j}(end)=='M'
testmat2(i,j)= addtodate(EurExDatesFull(i,j),str2double(SwaptionTenors{j}(1:end-1)),'month');
end
end
end
EurMatFull = testmat2;
relidx = find(EurMatFull <= InstrumentMaturity);
SwaptionBlackPrices = zeros(size(SwaptionBlackVol));
SwaptionStrike = zeros(size(SwaptionBlackVol));
for iSwaption=1:length(SwaptionExerciseDates)
for iTenor=1:length(SwaptionTenors)
[~,SwaptionStrike(iSwaption,iTenor)] = swapbyzero(RateSpec,[NaN 0],Settle, EurMatFull(iSwaption,iTenor),...
'StartDate',EurExDatesFull(iSwaption,iTenor),'LegReset',[1 2],'Basis',2);
SwaptionBlackPrices(iSwaption,iTenor) = swaptionbyblk(RateSpec,'call', SwaptionStrike(iSwaption,iTenor),Settle, ...
EurExDatesFull(iSwaption,iTenor), EurMatFull(iSwaption,iTenor),SwaptionBlackVol(iSwaption,iTenor));
end
end
TimeSpec = hwtimespec(Settle,daysadd(Settle,30*(1:370),6), 12);
% B = (214:224) produces error free solutions.
B = (150:224);
HW1Fobjfun4 = #(x) SwaptionBlackPrices(relidx(B)) - ...
swaptionbyhw(hwtree(hwvolspec(ValuationDate,testmat,x(2),testmat,x(1),'spline'), RateSpec, TimeSpec), 'call',SwaptionStrike(relidx(B)),EurExDatesFull(relidx(B)), 0,EurExDatesFull(relidx(B)), EurMatFull(relidx(B)),'Basis',2, 'SwapReset',12);
options = optimset('disp','iter','MaxFunEvals',1000,'TolFun',1e-5);
x0 = [.1 .01];
lb = [0 0];
ub = [1 1];
HW1Fparams = lsqnonlin(HW1Fobjfun4,x0,lb,ub,options)

Your best bet may be to modify the source lsqnonlin.m file. This can be a somewhat in-depth process, but it gives you the maximum control over what's going on.
Open the file by typing lsqnonlin at the command prompt, highlighting it, then right-clicking and clicking on Open Selection. Before you do anything else, save a copy of the file to your default Matlab working directory (e.g. C:\Users\username\Documents\MATLAB\ for Windows 7. Matlab puts your default working directory at the top of the search path, so if you have a program that's the same name as a Matlab built-in one, then Matlab will find yours first and use it instead. I don't have that particular function myself, so I can't give you the exact code to put in there, but the solution should be simple enough for you to implement.
With your locally-saved version of the code open, note that on the first line of the program, there's a function declaration that looks something like
function [output1,output2,...]=lsqnonlin(input1,input2,...)
From the MATLAB help page, it looks like x is the first output. Presumably, it's called x in the code itself or something similar, but if not, just use the first output parameter. Now that we know the name of the variable that is being output, we can go through the code and find where it is being calculated. MATLAB will probably have this routine be a wrapper around a more fundamental numerical code. For lsqnonneg, it calls lsqncommon, which then calls either snls or levenbergMarquardt, depending on the details of the problem. Any code that is iteratively solving something will eventually end up in a while loop, since it has to perform the same calculation an unknown number of times to converge on a solution. Once you find the while loop, it's simply a matter of adding a little code to output whatever parameter(s) you'd like to look at.
Just remember that as long as you have a file of the same name in your workspace, you'll be calling that one, not the original code, so you may want to delete (or at lease move) your modified code after you've finished debugging.

Wav file clipping when playing audio file in MATLAB

Here's my problem. I'm implementing high and low pass filers in the continuous time and discrete time domain, without using MATLAB built in functions or the Signal Processing Toolbox. I need to filter an uploaded wav file. I have the following code which implements the low pass continuous time filter. The main problem is that when I go to play the file, I get the following error:
Warning: Data clipped during write to file:flute_new
In wavwrite>PCM_Quantize at 286
In wavwrite>write_wavedat at 302
In wavwrite at 139
In test2 at 23
I've been reading that a common solution to this problem is: signal = signal/max(abs(signal)), but that still doesn't fix the problem of clipping. I don't quite understand what produces this error, so any help would be appreciated. Thank you for reading. Code is as follows:
[y,Fs,nbits]=wavread('flute.wav');
m = length(y); %96375
Fc = 500; %% frequency cut
nbits
n = -(m-1)/2 : (m-1)/2; %% kernel length / samples
%Fs = Fs; %22050 %% sample frequency / (nyquist - %2*m)
Tc = 2*pi*(Fc/Fs); %% theta c
Hm = sin(Tc*n) ./ (pi*n);
if (rem(m, 2) == 1)
index = (m+1)/2;
Hm(index) = Tc/pi;
end
[H w] = freqz(Hm, 1, 1024); % 1024 - Amount of Fourier Transform points
%do playback
sound(w,Fs);
%save and playback the file
wavwrite(w,'flute_new')
UPDATE:
From what I understand, because my wav file is 16 bits, I can only have -1<=w<1. I updated my code as suggested in the comments, but when I check the w values, I still have a w=1 at the end. The suggested code did eliminate the clipping warning, but the playback of the audio file through the speakers still has clipping. Maybe I'm understanding the concept wrong. Sorry if that's the case.
Playback Code (updated):
%Write and play file
w = w./max(abs(w(:)))*(1-(2^-(nbits-1)));
w
%do playback
sound(w,Fs);
wavwrite(w,'flute_new');
Output from terminal:
>> test2
nbits =
16
w =
0
0.0010
0.0020
0.0029
0.0039
0.0049
0.0059
0.0068
0.0078
0.0088
0.0098
0.0108
0.0117
0.0127
0.0137
0.0147
0.0156
0.0166
0.0176
0.0186
0.0195
0.0205
0.0215
0.0225
0.0235
0.0244
0.0254
0.0264
0.0274
0.0283
0.0293
0.0303
0.0313
0.0323
0.0332
0.0342
0.0352
0.0362
0.0371
0.0381
0.0391
0.0401
0.0411
0.0420
0.0430
0.0440
0.0450
0.0459
0.0469
0.0479
0.0489
0.0499
0.0508
0.0518
0.0528
0.0538
0.0547
0.0557
0.0567
0.0577
0.0586
0.0596
0.0606
0.0616
0.0626
0.0635
0.0645
0.0655
0.0665
0.0674
0.0684
0.0694
0.0704
0.0714
0.0723
0.0733
0.0743
0.0753
0.0762
0.0772
0.0782
0.0792
0.0802
0.0811
0.0821
0.0831
0.0841
0.0850
0.0860
0.0870
0.0880
0.0890
0.0899
0.0909
0.0919
0.0929
0.0938
0.0948
0.0958
0.0968
0.0977
0.0987
0.0997
0.1007
0.1017
0.1026
0.1036
0.1046
0.1056
0.1065
0.1075
0.1085
0.1095
0.1105
0.1114
0.1124
0.1134
0.1144
0.1153
0.1163
0.1173
0.1183
0.1193
0.1202
0.1212
0.1222
0.1232
0.1241
0.1251
0.1261
0.1271
0.1281
0.1290
0.1300
0.1310
0.1320
0.1329
0.1339
0.1349
0.1359
0.1368
0.1378
0.1388
0.1398
0.1408
0.1417
0.1427
0.1437
0.1447
0.1456
0.1466
0.1476
0.1486
0.1496
0.1505
0.1515
0.1525
0.1535
0.1544
0.1554
0.1564
0.1574
0.1584
0.1593
0.1603
0.1613
0.1623
0.1632
0.1642
0.1652
0.1662
0.1672
0.1681
0.1691
0.1701
0.1711
0.1720
0.1730
0.1740
0.1750
0.1759
0.1769
0.1779
0.1789
0.1799
0.1808
0.1818
0.1828
0.1838
0.1847
0.1857
0.1867
0.1877
0.1887
0.1896
0.1906
0.1916
0.1926
0.1935
0.1945
0.1955
0.1965
0.1975
0.1984
0.1994
0.2004
0.2014
0.2023
0.2033
0.2043
0.2053
0.2062
0.2072
0.2082
0.2092
0.2102
0.2111
0.2121
0.2131
0.2141
0.2150
0.2160
0.2170
0.2180
0.2190
0.2199
0.2209
0.2219
0.2229
0.2238
0.2248
0.2258
0.2268
0.2278
0.2287
0.2297
0.2307
0.2317
0.2326
0.2336
0.2346
0.2356
0.2366
0.2375
0.2385
0.2395
0.2405
0.2414
0.2424
0.2434
0.2444
0.2453
0.2463
0.2473
0.2483
0.2493
0.2502
0.2512
0.2522
0.2532
0.2541
0.2551
0.2561
0.2571
0.2581
0.2590
0.2600
0.2610
0.2620
0.2629
0.2639
0.2649
0.2659
0.2669
0.2678
0.2688
0.2698
0.2708
0.2717
0.2727
0.2737
0.2747
0.2757
0.2766
0.2776
0.2786
0.2796
0.2805
0.2815
0.2825
0.2835
0.2844
0.2854
0.2864
0.2874
0.2884
0.2893
0.2903
0.2913
0.2923
0.2932
0.2942
0.2952
0.2962
0.2972
0.2981
0.2991
0.3001
0.3011
0.3020
0.3030
0.3040
0.3050
0.3060
0.3069
0.3079
0.3089
0.3099
0.3108
0.3118
0.3128
0.3138
0.3148
0.3157
0.3167
0.3177
0.3187
0.3196
0.3206
0.3216
0.3226
0.3235
0.3245
0.3255
0.3265
0.3275
0.3284
0.3294
0.3304
0.3314
0.3323
0.3333
0.3343
0.3353
0.3363
0.3372
0.3382
0.3392
0.3402
0.3411
0.3421
0.3431
0.3441
0.3451
0.3460
0.3470
0.3480
0.3490
0.3499
0.3509
0.3519
0.3529
0.3539
0.3548
0.3558
0.3568
0.3578
0.3587
0.3597
0.3607
0.3617
0.3626
0.3636
0.3646
0.3656
0.3666
0.3675
0.3685
0.3695
0.3705
0.3714
0.3724
0.3734
0.3744
0.3754
0.3763
0.3773
0.3783
0.3793
0.3802
0.3812
0.3822
0.3832
0.3842
0.3851
0.3861
0.3871
0.3881
0.3890
0.3900
0.3910
0.3920
0.3929
0.3939
0.3949
0.3959
0.3969
0.3978
0.3988
0.3998
0.4008
0.4017
0.4027
0.4037
0.4047
0.4057
0.4066
0.4076
0.4086
0.4096
0.4105
0.4115
0.4125
0.4135
0.4145
0.4154
0.4164
0.4174
0.4184
0.4193
0.4203
0.4213
0.4223
0.4233
0.4242
0.4252
0.4262
0.4272
0.4281
0.4291
0.4301
0.4311
0.4320
0.4330
0.4340
0.4350
0.4360
0.4369
0.4379
0.4389
0.4399
0.4408
0.4418
0.4428
0.4438
0.4448
0.4457
0.4467
0.4477
0.4487
0.4496
0.4506
0.4516
0.4526
0.4536
0.4545
0.4555
0.4565
0.4575
0.4584
0.4594
0.4604
0.4614
0.4624
0.4633
0.4643
0.4653
0.4663
0.4672
0.4682
0.4692
0.4702
0.4711
0.4721
0.4731
0.4741
0.4751
0.4760
0.4770
0.4780
0.4790
0.4799
0.4809
0.4819
0.4829
0.4839
0.4848
0.4858
0.4868
0.4878
0.4887
0.4897
0.4907
0.4917
0.4927
0.4936
0.4946
0.4956
0.4966
0.4975
0.4985
0.4995
0.5005
0.5015
0.5024
0.5034
0.5044
0.5054
0.5063
0.5073
0.5083
0.5093
0.5102
0.5112
0.5122
0.5132
0.5142
0.5151
0.5161
0.5171
0.5181
0.5190
0.5200
0.5210
0.5220
0.5230
0.5239
0.5249
0.5259
0.5269
0.5278
0.5288
0.5298
0.5308
0.5318
0.5327
0.5337
0.5347
0.5357
0.5366
0.5376
0.5386
0.5396
0.5406
0.5415
0.5425
0.5435
0.5445
0.5454
0.5464
0.5474
0.5484
0.5493
0.5503
0.5513
0.5523
0.5533
0.5542
0.5552
0.5562
0.5572
0.5581
0.5591
0.5601
0.5611
0.5621
0.5630
0.5640
0.5650
0.5660
0.5669
0.5679
0.5689
0.5699
0.5709
0.5718
0.5728
0.5738
0.5748
0.5757
0.5767
0.5777
0.5787
0.5796
0.5806
0.5816
0.5826
0.5836
0.5845
0.5855
0.5865
0.5875
0.5884
0.5894
0.5904
0.5914
0.5924
0.5933
0.5943
0.5953
0.5963
0.5972
0.5982
0.5992
0.6002
0.6012
0.6021
0.6031
0.6041
0.6051
0.6060
0.6070
0.6080
0.6090
0.6100
0.6109
0.6119
0.6129
0.6139
0.6148
0.6158
0.6168
0.6178
0.6187
0.6197
0.6207
0.6217
0.6227
0.6236
0.6246
0.6256
0.6266
0.6275
0.6285
0.6295
0.6305
0.6315
0.6324
0.6334
0.6344
0.6354
0.6363
0.6373
0.6383
0.6393
0.6403
0.6412
0.6422
0.6432
0.6442
0.6451
0.6461
0.6471
0.6481
0.6491
0.6500
0.6510
0.6520
0.6530
0.6539
0.6549
0.6559
0.6569
0.6578
0.6588
0.6598
0.6608
0.6618
0.6627
0.6637
0.6647
0.6657
0.6666
0.6676
0.6686
0.6696
0.6706
0.6715
0.6725
0.6735
0.6745
0.6754
0.6764
0.6774
0.6784
0.6794
0.6803
0.6813
0.6823
0.6833
0.6842
0.6852
0.6862
0.6872
0.6882
0.6891
0.6901
0.6911
0.6921
0.6930
0.6940
0.6950
0.6960
0.6969
0.6979
0.6989
0.6999
0.7009
0.7018
0.7028
0.7038
0.7048
0.7057
0.7067
0.7077
0.7087
0.7097
0.7106
0.7116
0.7126
0.7136
0.7145
0.7155
0.7165
0.7175
0.7185
0.7194
0.7204
0.7214
0.7224
0.7233
0.7243
0.7253
0.7263
0.7273
0.7282
0.7292
0.7302
0.7312
0.7321
0.7331
0.7341
0.7351
0.7360
0.7370
0.7380
0.7390
0.7400
0.7409
0.7419
0.7429
0.7439
0.7448
0.7458
0.7468
0.7478
0.7488
0.7497
0.7507
0.7517
0.7527
0.7536
0.7546
0.7556
0.7566
0.7576
0.7585
0.7595
0.7605
0.7615
0.7624
0.7634
0.7644
0.7654
0.7664
0.7673
0.7683
0.7693
0.7703
0.7712
0.7722
0.7732
0.7742
0.7751
0.7761
0.7771
0.7781
0.7791
0.7800
0.7810
0.7820
0.7830
0.7839
0.7849
0.7859
0.7869
0.7879
0.7888
0.7898
0.7908
0.7918
0.7927
0.7937
0.7947
0.7957
0.7967
0.7976
0.7986
0.7996
0.8006
0.8015
0.8025
0.8035
0.8045
0.8054
0.8064
0.8074
0.8084
0.8094
0.8103
0.8113
0.8123
0.8133
0.8142
0.8152
0.8162
0.8172
0.8182
0.8191
0.8201
0.8211
0.8221
0.8230
0.8240
0.8250
0.8260
0.8270
0.8279
0.8289
0.8299
0.8309
0.8318
0.8328
0.8338
0.8348
0.8358
0.8367
0.8377
0.8387
0.8397
0.8406
0.8416
0.8426
0.8436
0.8445
0.8455
0.8465
0.8475
0.8485
0.8494
0.8504
0.8514
0.8524
0.8533
0.8543
0.8553
0.8563
0.8573
0.8582
0.8592
0.8602
0.8612
0.8621
0.8631
0.8641
0.8651
0.8661
0.8670
0.8680
0.8690
0.8700
0.8709
0.8719
0.8729
0.8739
0.8749
0.8758
0.8768
0.8778
0.8788
0.8797
0.8807
0.8817
0.8827
0.8836
0.8846
0.8856
0.8866
0.8876
0.8885
0.8895
0.8905
0.8915
0.8924
0.8934
0.8944
0.8954
0.8964
0.8973
0.8983
0.8993
0.9003
0.9012
0.9022
0.9032
0.9042
0.9052
0.9061
0.9071
0.9081
0.9091
0.9100
0.9110
0.9120
0.9130
0.9140
0.9149
0.9159
0.9169
0.9179
0.9188
0.9198
0.9208
0.9218
0.9227
0.9237
0.9247
0.9257
0.9267
0.9276
0.9286
0.9296
0.9306
0.9315
0.9325
0.9335
0.9345
0.9355
0.9364
0.9374
0.9384
0.9394
0.9403
0.9413
0.9423
0.9433
0.9443
0.9452
0.9462
0.9472
0.9482
0.9491
0.9501
0.9511
0.9521
0.9531
0.9540
0.9550
0.9560
0.9570
0.9579
0.9589
0.9599
0.9609
0.9618
0.9628
0.9638
0.9648
0.9658
0.9667
0.9677
0.9687
0.9697
0.9706
0.9716
0.9726
0.9736
0.9746
0.9755
0.9765
0.9775
0.9785
0.9794
0.9804
0.9814
0.9824
0.9834
0.9843
0.9853
0.9863
0.9873
0.9882
0.9892
0.9902
0.9912
0.9921
0.9931
0.9941
0.9951
0.9961
0.9970
0.9980
0.9990
1.0000

It's not an error, just a warning.
If you write a .wav-file with 32 bits resolution, the allowed data range is -1 <= w <= 1. But for 8, 16 or 24 bits, the limits are -1 <= w < 1, such that w==1 creates the clipping warning (1-bit short of '1', i.e., 1 - 1/32768 = 0.99996948242188 in 16-bit mode.), and it can not be written into file. You can ignore that, or :
format long
w = w./max(abs(w(:)))*(1-(2^-(nbits-1)));
wavwrite(w,'flute_new');

Reserved character codes in Unicode

Why Unicode has several reserved character codes?
See the Unicode for two languages- Kannada and Tamil.
Both language are very old and I think there is no chance to get new characters to these languages.
EDIT: Then why are they wasting some character codes by making it reserved character codes?
Why are they not placing the reserved character codes at the end of each language character set?

This has to do with how the Unicode consortium doles out its allocated blocks, scripts, and code points. For example, in Block=Tamil, the start of it runs this way:
$ unichars '\p{Block=Tamil}' | head -20
U+00B82 ‭ ◌ஂ GC=Mn SC=Tamil TAMIL SIGN ANUSVARA
U+00B83 ‭ ஃ GC=Lo SC=Tamil TAMIL SIGN VISARGA
U+00B85 ‭ அ GC=Lo SC=Tamil TAMIL LETTER A
U+00B86 ‭ ஆ GC=Lo SC=Tamil TAMIL LETTER AA
U+00B87 ‭ இ GC=Lo SC=Tamil TAMIL LETTER I
U+00B88 ‭ ஈ GC=Lo SC=Tamil TAMIL LETTER II
U+00B89 ‭ உ GC=Lo SC=Tamil TAMIL LETTER U
U+00B8A ‭ ஊ GC=Lo SC=Tamil TAMIL LETTER UU
U+00B8E ‭ எ GC=Lo SC=Tamil TAMIL LETTER E
U+00B8F ‭ ஏ GC=Lo SC=Tamil TAMIL LETTER EE
U+00B90 ‭ ஐ GC=Lo SC=Tamil TAMIL LETTER AI
U+00B92 ‭ ஒ GC=Lo SC=Tamil TAMIL LETTER O
U+00B93 ‭ ஓ GC=Lo SC=Tamil TAMIL LETTER OO
U+00B94 ‭ ஔ GC=Lo SC=Tamil TAMIL LETTER AU
U+00B95 ‭ க GC=Lo SC=Tamil TAMIL LETTER KA
U+00B99 ‭ ங GC=Lo SC=Tamil TAMIL LETTER NGA
U+00B9A ‭ ச GC=Lo SC=Tamil TAMIL LETTER CA
U+00B9C ‭ ஜ GC=Lo SC=Tamil TAMIL LETTER JA
U+00B9E ‭ ஞ GC=Lo SC=Tamil TAMIL LETTER NYA
U+00B9F ‭ ட GC=Lo SC=Tamil TAMIL LETTER TTA
They tend to reserve contiguous rows of 4, 8, or 16 code points to all the same “kind” of character. Yes, there are gaps there, but it’s like how in the filesystem, once you allocate a sector (or block if you don’t have separate sectors within a block) to one file, even if that file doesn’t use everything in its (final) sector, you don’t go giving away those unused byte to some other process. Things tend to get padded to block boundaries anyway.
It’s not like we’re at any risk of running out of codes.
Here is the beginning of the allocated area starts with “Signs”, as shown by the first assigned code points in that block. The gap may represent a change from one kind of character to another. If you check out the first five code points in the block for their properties, you see that those unassigned code points still have the right block property:
$ uniprops -a U+00B80 U+00B81 U+00B82 U+00B83 U+00B84 U+00B85
U+0B80 ‹U+0B80› \N{U+0B80}
\pC \p{Cn}
All Any InTamil C Other Cn Unassigned Zzzz Unknown
Age=Unassigned Bidi_Class=L Bidi_Class=Left_To_Right BC=L Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered
CCC=NR Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=Other GCB=XX
Grapheme_Cluster_Break=XX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=Non_Joining JT=U Joining_Type=U Line_Break=Unknown LB=XX Line_Break=XX Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=Unassigned IN=Unassigned Script=Unknown SC=Zzzz Script=Zzzz Sentence_Break=Other SB=XX
Sentence_Break=XX Word_Break=Other WB=XX Word_Break=XX
U+0B81 ‹U+0B81› \N{U+0B81}
\pC \p{Cn}
All Any InTamil C Other Cn Unassigned Zzzz Unknown
Age=Unassigned Bidi_Class=L Bidi_Class=Left_To_Right BC=L Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered
CCC=NR Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=Other GCB=XX
Grapheme_Cluster_Break=XX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=Non_Joining JT=U Joining_Type=U Line_Break=Unknown LB=XX Line_Break=XX Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=Unassigned IN=Unassigned Script=Unknown SC=Zzzz Script=Zzzz Sentence_Break=Other SB=XX
Sentence_Break=XX Word_Break=Other WB=XX Word_Break=XX
U+0B82 ‹◌ஂ› \N{TAMIL SIGN ANUSVARA}
\w \pM \p{Mn}
All Any Alnum Alpha Alphabetic Assigned InTamil Tamil Is_Tamil Case_Ignorable CI M Mn Gr_Ext Grapheme_Extend Graph GrExt ID_Continue IDC
Mark Nonspacing_Mark Print Taml Word XID_Continue XIDC X_POSIX_Alnum X_POSIX_Alpha X_POSIX_Graph X_POSIX_Print X_POSIX_Word
Age=1.1 Bidi_Class=Nonspacing_Mark BC=NSM Bidi_Class=NSM Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered
CCC=NR Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=EX
Grapheme_Cluster_Break=Extend GCB=EX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=T Joining_Type=Transparent JT=T Line_Break=CM Line_Break=Combining_Mark LB=CM Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=1.1 IN=1.1 Present_In=2.0 IN=2.0 Present_In=2.1 IN=2.1 Present_In=3.0 IN=3.0 Present_In=3.1 IN=3.1
Present_In=3.2 IN=3.2 Present_In=4.0 IN=4.0 Present_In=4.1 IN=4.1 Present_In=5.0 IN=5.0 Present_In=5.1 IN=5.1 Present_In=5.2 IN=5.2
Present_In=6.0 IN=6.0 Script=Tamil SC=Taml Script=Taml Sentence_Break=EX Sentence_Break=Extend SB=EX Word_Break=Extend WB=Extend
U+0B83 ‹ஃ› \N{TAMIL SIGN VISARGA}
\w \pL \p{L_} \p{Lo}
All Any Alnum Alpha Alphabetic Assigned InTamil Tamil Is_Tamil L Lo Gr_Base Grapheme_Base Graph GrBase ID_Continue IDC ID_Start IDS Letter
L_ Other_Letter Print Taml Word XID_Continue XIDC XID_Start XIDS X_POSIX_Alnum X_POSIX_Alpha X_POSIX_Graph X_POSIX_Print X_POSIX_Word
Age=1.1 Bidi_Class=L Bidi_Class=Left_To_Right BC=L Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered CCC=NR
Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=Other GCB=XX
Grapheme_Cluster_Break=XX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=Non_Joining JT=U Joining_Type=U Line_Break=AL Line_Break=Alphabetic LB=AL Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=1.1 IN=1.1 Present_In=2.0 IN=2.0 Present_In=2.1 IN=2.1 Present_In=3.0 IN=3.0 Present_In=3.1 IN=3.1
Present_In=3.2 IN=3.2 Present_In=4.0 IN=4.0 Present_In=4.1 IN=4.1 Present_In=5.0 IN=5.0 Present_In=5.1 IN=5.1 Present_In=5.2 IN=5.2
Present_In=6.0 IN=6.0 Script=Tamil SC=Taml Script=Taml Sentence_Break=LE Sentence_Break=OLetter SB=LE Word_Break=ALetter WB=LE
Word_Break=LE
U+0B84 ‹U+0B84› \N{U+0B84}
\pC \p{Cn}
All Any InTamil C Other Cn Unassigned Zzzz Unknown
Age=Unassigned Bidi_Class=L Bidi_Class=Left_To_Right BC=L Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered
CCC=NR Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=Other GCB=XX
Grapheme_Cluster_Break=XX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=Non_Joining JT=U Joining_Type=U Line_Break=Unknown LB=XX Line_Break=XX Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=Unassigned IN=Unassigned Script=Unknown SC=Zzzz Script=Zzzz Sentence_Break=Other SB=XX
Sentence_Break=XX Word_Break=Other WB=XX Word_Break=XX
U+0B85 ‹அ› \N{TAMIL LETTER A}
\w \pL \p{L_} \p{Lo}
All Any Alnum Alpha Alphabetic Assigned InTamil Tamil Is_Tamil L Lo Gr_Base Grapheme_Base Graph GrBase ID_Continue IDC ID_Start IDS Letter
L_ Other_Letter Print Taml Word XID_Continue XIDC XID_Start XIDS X_POSIX_Alnum X_POSIX_Alpha X_POSIX_Graph X_POSIX_Print X_POSIX_Word
Age=1.1 Bidi_Class=L Bidi_Class=Left_To_Right BC=L Block=Tamil Canonical_Combining_Class=0 Canonical_Combining_Class=Not_Reordered CCC=NR
Canonical_Combining_Class=NR Decomposition_Type=None DT=None East_Asian_Width=Neutral Grapheme_Cluster_Break=Other GCB=XX
Grapheme_Cluster_Break=XX Hangul_Syllable_Type=NA Hangul_Syllable_Type=Not_Applicable HST=NA Joining_Group=No_Joining_Group
JG=NoJoiningGroup Joining_Type=Non_Joining JT=U Joining_Type=U Line_Break=AL Line_Break=Alphabetic LB=AL Numeric_Type=None NT=None
Numeric_Value=NaN NV=NaN Present_In=1.1 IN=1.1 Present_In=2.0 IN=2.0 Present_In=2.1 IN=2.1 Present_In=3.0 IN=3.0 Present_In=3.1 IN=3.1
Present_In=3.2 IN=3.2 Present_In=4.0 IN=4.0 Present_In=4.1 IN=4.1 Present_In=5.0 IN=5.0 Present_In=5.1 IN=5.1 Present_In=5.2 IN=5.2
Present_In=6.0 IN=6.0 Script=Tamil SC=Taml Script=Taml Sentence_Break=LE Sentence_Break=OLetter SB=LE Word_Break=ALetter WB=LE
Word_Break=LE
If you look at other allocated blocks, you see the same sort of thing. It doesn’t make sense to slice up blocks into unrelated things.
As I said, it’s not as though they’re going to run out of space, so I don’t know what the concern is here.
BTW, you can get Unicode exploration and proceesing tools like unichars, uniprops, uninames from my Unicode Command-Line Toolchest, either individually from there or the entire suite available through the CPAN Unicode::Tussle suite.