Problem when using variable
echo ""| awk '{
x=-0.35
print x^1.35
print -0.35^1.35
}'
Result
+nan
-0.242377
Using GNU awk
The output is correct.
The power operator ^ has higher precedence than the negation operator. Therefore, x^1.35 is (-0.35)^1.35 (a negative number to a non-integer power is a complex number, interpreted as a -nan), but -0.35^1.35 is -(0.35^1.35), a negated positive power of a positive number.
In college, I was required to take a whole semester on complex math, here is the mathematical meat of this issue:
-0.35^1.35 =
-0.35^(135/100) =
-0.35^(27/20) =
((-0.35^27))^1/20) =
(-0.00000000000049)^1/20 =
0.242377253454738i (or "nan" if constrained to real #s)
-0.35^1.35 =
-0.35^(135/100) =
-0.35^(27/20) =
-0.35^(54/40) =
((-0.35^54))^1/40) =
(2.397035107846411e-25)^1/40 =
0.242377253454738
-- so, the answer is there are two answers! Your new word for the day is "complex conjugate".
Related
in the DVBS2 Standard the SRRC filter is defined as
How can i find the filter's time domain coefficients for implementation? The Inverse Fourier transform of this is not clear to me.
For DVBS2 signal you can use RRC match filter before timing recovery. For match filter, you can use this expression:
For example for n_ISI = 32 and Roll of factor = 0.25 with any sample per symbol you can use this Matlab code:
SPS = 4; %for example
n_ISI=32;
rolloff = 0.25;
n = linspace(-n_ISI/2,n_ISI/2,n_ISI*SPS+1) ;
rrcFilt = zeros(size(n)) ;
for iter = 1:length(n)
if n(iter) == 0
rrcFilt(iter) = 1 - rolloff + 4*rolloff/pi ;
elseif abs(n(iter)) == 1/4/rolloff
rrcFilt(iter) = rolloff/sqrt(2)*((1+2/pi)*sin(pi/4/rolloff)+(1-2/pi)*cos(pi/4/rolloff)) ;
else
rrcFilt(iter) = (4*rolloff/pi)/(1-(4*rolloff*n(iter)).^2) * (cos((1+rolloff)*pi*n(iter)) + sin((1-rolloff)*pi*n(iter))/(4*rolloff*n(iter))) ;
end
end
But if you want to use SRRC, there are two ways: 1. You can use its frequency representation form if you use filtering in the frequency domain. And for implementation, you can use the expression that you've noted. 2. For time-domain filtering, you should define the FIR filter with its time representation sequence. The time representation of such SRRC pulses is shown to adopt the following form:
I need to make a language that has variables in it, but it also needs the letter 'd' to be an operand that has a number on the right and maybe a number on the left. I thought that making sure the lexer checks for the letter first would give it precedence, but that doesn't happen and i don't know why.
from ply import lex, yacc
tokens=['INT', 'D', 'PLUS', 'MINUS', 'LPAR', 'RPAR', 'BIGGEST', 'SMALLEST', 'EQ', 'NAME']
t_PLUS = r'\+'
t_MINUS = r'\-'
t_LPAR = r'\('
t_RPAR = r'\)'
t_BIGGEST = r'\!'
t_SMALLEST = r'\#'
t_D = r'[dD]'
t_EQ = r'\='
t_NAME = r'[a-zA-Z_][a-zA-Z0-9_]*'
def t_INT(t):
r'[0-9]\d*'
t.value = int(t.value)
return t
def t_newline(t):
r'\n+'
t.lexer.lineno += 1
t_ignore = ' \t'
def t_error(t):
print("Not recognized by the lexer:", t.value)
t.lexer.skip(1)
lexer = lex.lex()
while True:
try: s = input(">> ")
except EOFError: break
lexer.input(s)
while True:
t = lexer.token()
if not t: break
print(t)
If i write:
3d4
it outputs:
LexToken(INT,3,1,0)
LexToken(NAME,'d4',1,1)
and i don't know how to work around it.
Ply does not prioritize token variables by order of appearance; rather, it orders them in decreasing order by length (longest first). So your t_NAME pattern will come before t_D. This is explained in the Ply manual, along with a concrete example of how to handle reserved words (which may not apply in your case).
If I understand correctly, the letter d cannot be an identifier, and neither can d followed by a number. It is not entirely clear to me whether you expect d2e to be a plausible identifier, but for simplicity I'm assuming that the answer is "No", in which case you can easily restrict the t_NAME regular expression by requiring an initial d to be followed by another letter:
t_NAME = '([a-ce-zA-CE-Z_]|[dD][a-zA-Z_])[a-zA-Z0-9_]*'
If you wanted to allow d2e to be a name, then you could go with:
t_NAME = '([a-ce-zA-CE-Z_]|[dD][0-9]*[a-zA-Z_])[a-zA-Z0-9_]*'
I am wondering if its possible to search in the database with the given scrambled words.
I have a mobs table in database and it holds the name of the monster names
If given monster name is A Golden Dregon or A Golden Dfigon or A Gelden Dragon I want it to find A Golden Dragon or with the matches that close to it from database. Usually one or two letters at max is given like this as scrambled.
Is that possible with just SQL queries? Or should I build the query by parsing the given monster name?
I am using LUA for the code side.
I have come to know this search type as a fuzzy search. I mainly program in JS and use fuse.js all the time for this kind of problem.
Fuzzy Searches are based on the Levenshtein algorithm that rate the distance of two strings. When you have this distance value you can sort or drop elements from a list based on the score.
I found the algorithm in lua here.
function levenshtein(s, t)
local s, t = tostring(s), tostring(t)
if type(s) == 'string' and type(t) == 'string' then
local m, n, d = #s, #t, {}
for i = 0, m do d[i] = { [0] = i } end
for j = 1, n do d[0][j] = j end
for i = 1, m do
for j = 1, n do
local cost = s:sub(i,i) == t:sub(j,j) and 0 or 1
d[i][j] = math.min(d[i-1][j]+1, d[i][j-1]+1, d[i-1][j-1]+cost)
end
end
return d[m][n]
end
end
As explained in the site you compare two strings like so and get a score based on the distance of them, then sort or drop the items being search based on the scores given. As this is CPU expensive I would suggest caching or use a memoize function to store common mistakes.
levenshtein('referrer', 'referrer') -- zero distance
>>> 0
levenshtein('referrer', 'referer') -- distance of one character
>>> 1
levenshtein('random', 'strings') -- random big distance
>>> 6
Got a simple version of it working in lua here I must say lua is an easy language to pick up and start coding with.
local monsters = {'A Golden Dragon', 'Goblins', 'Bunny', 'Dragoon'}
function levenshtein(s, t)
local s, t = tostring(s), tostring(t)
if type(s) == 'string' and type(t) == 'string' then
local m, n, d = #s, #t, {}
for i = 0, m do d[i] = { [0] = i } end
for j = 1, n do d[0][j] = j end
for i = 1, m do
for j = 1, n do
local cost = s:sub(i,i) == t:sub(j,j) and 0 or 1
d[i][j] = math.min(d[i-1][j]+1, d[i][j-1]+1, d[i-1][j-1]+cost)
end
end
return d[m][n]
end
end
--Fuzzy Search Returns the Best Match in a list
function fuzzySearch(list, searchText)
local bestMatch = nil;
local lowestScore = nil;
for i = 1, #list do
local score = levenshtein(list[i], searchText)
if lowestScore == nil or score < lowestScore then
bestMatch = list[i]
lowestScore = score
end
end
return bestMatch
end
print ( fuzzySearch(monsters, 'golen dragggon') )
print ( fuzzySearch(monsters, 'A Golden Dfigon') )
print ( fuzzySearch(monsters, 'A Gelden Dragon') )
print ( fuzzySearch(monsters, 'Dragooon') ) --should be Dragoon
print ( fuzzySearch(monsters, 'Funny') ) --should be Bunny
print ( fuzzySearch(monsters, 'Gob') ) --should be Goblins
Output
A Golden Dragon
A Golden Dragon
A Golden Dragon
Dragoon
Bunny
Goblins
For SQL
You can try to do this same algorithm in T-SQL as talked about here.
In SQLlite there is an extension called editdist3 which also uses this algorithm the docs are here.
I would be hard to compensate for all the different one and two letter scrambled combinations, but you could create a lua table of common misspellings of "A Golden Dragon" check if it is in the table. I have never used lua before but here is my best try at some sample code:
local mob_name = "A Golden Dregon"--you could do something like, input("Enter mob name:")
local scrambled_dragon_names = {"A Golden Dregon", "A Golden Dfigon", "A Gelden Dragon"}
for _,v in pairs(scrambled_dragon_names) do
if v == mob_name then
mob_name = "A Golden Dragon"
break
end
end
I really hope I have helped!
P.S. If you have anymore questions go ahead and comment and I will try to answer ASAP.
You will have to parse the given monster name to some extent, by making assumptions about how badly it is misspelled. For example, if the user supplied the name
b fulden gorgon
There is no way in hell you can get to "A Golden Dragon". However, if you assume that the user will always get the first and last letters of every word correctly, then you could parse the words in the given name to get the first and last letters of each word, which would give you
"A", "G" "n", "D" "n"
Then you could use the LIKE operator in your query, like so:
SELECT * FROM mobs WHERE monster_name LIKE 'A G%n D%n';
The main point here is what assumptions you make about the misspelling. The closer you can narrow it down, the better your query results will be.
How can you get the length of the curve down below between 0 and 4*pi? The commands you should use are inttrap and diff. Here is what I have now:
t=linspace(0,4*%pi)
x=(4+sin(a*t)).*cos(3*t)
y=(4+sin(a*t)).*sin(3*t)
z=cos(3*t)
xx=diff(x)
yy=diff(y)
zz=diff(z)
aid=sqrt(xx^2+yy^2+zz^2)
length=inttrap([t],aid)
Getting error message, the last step is not right.
The reason for error message is that t and aid have different sizes. And that is because diff returns a vector with 1 entry fewer than the input. You can see how it works on an example: diff([3 1 5]) is [-2 4].
To fix this, use t(1:$-1), which omits the last entry of t. That is,
len = inttrap(t(1:$-1), aid)
(Please don't use length, which is a function name in Scilab.)
Another problem you have is that diff is just differences, not a derivative. To get the derivative, you need to divide by the step size, which in your case is t(2)-t(1).
Also, the syntax xx^2 is deprecated for elementwise power; use xx.^2 instead
t = linspace(0,4*%pi)
a = 1
x = (4+sin(a*t)).*cos(3*t)
y = (4+sin(a*t)).*sin(3*t)
z = cos(3*t)
step = t(2)-t(1)
xx = diff(x)/step
xy = diff(y)/step
xz = diff(z)/step
aid = sqrt(xx.^2+yy.^2+zz.^2)
len = inttrap(t(1:$-1), aid)
Is there a name for logical AND with the negation (~) of the second variable, i.e:
A & (~B)
The truth table for such operation is:
0 & (~0) = 0
0 & (~1) = 0
1 & (~0) = 1
1 & (~1) = 0
And in longer sequences of bits,
A = 10110011
B = 10111001
A & B = 10110001
A &(~B) = 00000010
PS - I'm interested with OR with the negation of the second variable, too.
Incredible. A & (~B) is called Material nonimplication, and A | (~B) is called Material implication Seems that every possible binary operation has a name.
The set theoretic term is the "relative complement" of B with respect to A.
I like to call it bit clearer. You find it in code also in the
form by using an assignment:
A = A & ~B
Or more compact as:
A &= ~B
Example: Before: A = 0x0007, B=0x0004
After: A = 0x0003
It has the effect that it clears the bits B from A. But relative
complement, and hence the name difference, you could write
it as follows A \ B, like the set difference, is also a good name.