hello I want to select a subchain and analyze it example:
my chain to analyze
NADSU 78000mc0cl0Css
NADBY 7808810008659
PAT 1 21D 089
I need to read and then analyze line by line of a .txt file after that I would like to verify through an if or case cycle that the paramenters could be fulfilled. I clarify the txt file has about 300 lines
the first three characters must be letters with a specific format the following is usually the 4 character or 5 that has a number depends on that number means something and the last is the purchase order number or the amount or type of wrap ... ... this is a generalized idea I'm only giving the minimum to understand ...
Annex example and my code
I put two real cases of the line to analyze
--- here the letters nad = purchase order BY = supplier the remaining one is the purchase order number
NADBY 7808810008659
--- here Pat means = type of payment. the first number = the type of payment if it is one the type of payment is counted if it is two credits. the average 21d = number of days to issue clearance and the 089 = number of days to pay
PAT 1 21D 089
--- here the letters nad = purchase order BY = buyer css = a boxes but it can be ss = minicams
NADSU 78000mc0cl0Css
fileopen ('nombre_doc.txt',r) do |fichero1|
fileopen ('copianombre_doc.txt',w) do |fichero2|
while linea= fichero1.gets
fichero1=gsub(/\s+/,'')
Related
the problem goes like this
Write a program with total change amount as an integer input, and output the change using the fewest coins, one coin type per line. End each line with a newline. The coin types are dollars, quarters, dimes, nickels, and pennies. Use singular and plural coin names as appropriate, like 1 penny vs. 2 pennies.
Ex: If the input is:
0
or less than 0, the output is:
no change
Ex: If the input is:
45
the output is:
1 quarter
2 dimes
A string '321#322#323#324#325'.
here number of digits in each number is 3 but it's not limited to 3 it could be any number.
here are 5 numbers in a string but this number could be anything.
task is to get 321,322,323,324,325 and store in a table so that any operation could be performed over them.
I have tried several string functions like c = c:gsub('%W','') to eliminate those non-alphanumeric characters, but nothing helped.
function encrypter()--FUNCTION 14
c=' '
print('Please enter your message!')
local message=io.read()
lengthOfString=string.len(message)--Inbuit function to get length of a string.
newLine()
print('Please enter your key. Remember this key, otherwise your message wont be decrypted')
newLine()
key=io.read()
key=tonumber(key)
largeSpace()
print("Encrypted message is")
for s=1,lengthOfString do
--print(encryptionFormula(string.byte(message,s),key))
--inbuilt function for converting character of a string to it's respective ASCII value. First place gets character or variable having string whereas second place gets position of that character in the given string.
b=encryptionFormula(string.byte(message,s),key)
c=c..tostring(b)..'#'
--print(c)
b=0
end
print(c)
largeSpace()
print("Now share this message along with the key to the receiver. Don't share your key with anyone, if you don't want your message to be read.")
end
What you're looking for is string.gmatch().
local input = "123#546514#13#548#2315"
local numbers = {}
for number in string.gmatch(input, '%d+') do
table.insert(numbers, number)
end
-- Output the numbers
for index, number in ipairs(numbers) do
print(index, number)
-- This prints:
-- 1 123
-- 2 546514
-- 3 13
-- 4 548
-- 5 2315
end
If you don't know how Lua patterns work, you can read about them in the reference manual or you can have a look at Programming in Lua (the first edition is available for free on their website)
Within my current research I'm trying to find out, how big the impact of ad-hoc sentiment on daily stock returns is.
Calculations functioned quite well and results also are plausible.
The calculations until now with quantmod package and yahoo financial data look like below:
getSymbols(c("^CDAXX",Symbols) , env = myenviron, src = "yahoo",
from = as.Date("2007-01-02"), to = as.Date("2016-12-30")
Returns <- eapply(myenviron, function(s) ROC(Ad(s), type="discrete"))
ReturnsDF <- as.data.table(do.call(merge.xts, Returns))
# adjust column names
colnames(ReturnsDF) <- gsub(".Adjusted","",colnames(ReturnsDF))
ReturnsDF <- as.data.table(ReturnsDF)
However, to make it more robust towards noisy influence of pennystock data I wonder, how its possible to exclude stocks that once in the time period go below a certain value x, let's say 1€.
I guess, the best thing would be to exclude them before calculating the returns and merge the xts object results or even better, before downloading them with the getSymbols command.
Has anybody an idea how this could work best? Thanks in advance.
Try this:
build a price frame of the Adj. closing prices of your symbols
(I use the PF function of the quantmod add-on package qmao which has lots of other useful functions for this type of analysis. (install.packages("qmao", repos="http://R-Forge.R-project.org”))
check by column if any price is below your minimum trigger price
select only columns which have no closings below the trigger price
To stay more flexible I would suggest to take a sub period - let’s say no price below 5 during the last 21 trading days.The toy example below may illustrate my point.
I use AAPL, FB and MSFT as the symbol universe.
> symbols <- c('AAPL','MSFT','FB')
> getSymbols(symbols, from='2018-02-01')
[1] "AAPL" "MSFT" "FB"
> prices <- PF(symbols, silent = TRUE)
> prices
AAPL MSFT FB
2018-02-01 167.0987 93.81929 193.09
2018-02-02 159.8483 91.35088 190.28
2018-02-05 155.8546 87.58855 181.26
2018-02-06 162.3680 90.90299 185.31
2018-02-07 158.8922 89.19102 180.18
2018-02-08 154.5200 84.61253 171.58
2018-02-09 156.4100 87.76771 176.11
2018-02-12 162.7100 88.71327 176.41
2018-02-13 164.3400 89.41000 173.15
2018-02-14 167.3700 90.81000 179.52
2018-02-15 172.9900 92.66000 179.96
2018-02-16 172.4300 92.00000 177.36
2018-02-20 171.8500 92.72000 176.01
2018-02-21 171.0700 91.49000 177.91
2018-02-22 172.5000 91.73000 178.99
2018-02-23 175.5000 94.06000 183.29
2018-02-26 178.9700 95.42000 184.93
2018-02-27 178.3900 94.20000 181.46
2018-02-28 178.1200 93.77000 178.32
2018-03-01 175.0000 92.85000 175.94
2018-03-02 176.2100 93.05000 176.62
Let’s assume you would like any instrument which traded below 175.40 during the last 6 trading days to be excluded from your analysis :-) .
As you can see that shall exclude AAPL and FB.
apply and the base function any applied(!) to a 6-day subset of prices will give us exactly what we want. Showing the last 3 days of prices excluding the instruments which did not meet our condition:
> tail(prices[,apply(tail(prices),2, function(x) any(x < 175.4)) == FALSE],3)
FB
2018-02-28 178.32
2018-03-01 175.94
2018-03-02 176.62
I am generating a unique and random alphanumeric string segment to represent certain links that will be generated by the users. For doing that I was approaching with "uuid" number to ensure it's uniqueness and randomness, but, as per my requirements the string shouldn't be more than 5 characters long. So I dropped that idea.
Then I decided to generate such a string using random function of ruby and current time stamp.
The code for my random string goes like this:-
temp=DateTime.now
temp=temp + rand(DateTime.now.to_i)
temp= hash.abs.to_s(36)
What I did is that I stored the current DateTime in a temp variable and then I generated a random number passing the current datetime as parameter. Then in the second line actually added current datetime and random number together to make a unique and random string.
Soon I found,while I was testing my application in two different machines and send the request at the same time, it generated the same string(Though it's rare) once after more than 100 trials.
Now I'm thinking that I should add one more parameter like mac address or client ip address before passing to_s(36) on temp variable. But can't figure out how to do it and even then whether it will be unique or nor...
Thanks....
SecureRandom in ruby uses process id (if available) and current time. You can use the urlsafe_base64(n= 16) class method to generate the sequence you need. According to your requirements I think this is your best bet.
Edit: After a bit of testing, I still think that this approach will generate non-unique keys. The way I solved this problem for barcode generation was:
barcode= barcode_sql_id_hash("#{sql_id}#{keyword}")
Here, your keyword can be time + pid.
If you are certain that you will never need more than a given M amount of unique values, and you don't need more than rudimentary protection against guessing the next generated id, you can use a Linear Congruentual Generator to generate your identificators. All you have to do is remember the last id generated, and use that to generate a new one using the following formula:
newid = (A * oldid + B) mod M
If 2³² distinct id values are enough to suit your needs, try:
def generate_id
if #lcg
#lcg = (1664525 * #lcg + 1013904223) % (2**32)
else
#lcg = rand(2**32) # Random seed
end
end
Now just pick a suitable set of characters to represent the id in as little as 6 character. Uppercase and lowercase letters should do the trick, since (26+26)^6 > 2^32:
ENCODE_CHARS = [*?a..?z, *?A..?Z]
def encode(n)
6.times.map { |i|
n, mod = n.divmod(ENCODE_CHARS.size)
ENCODE_CHARS[mod]
}.join
end
Example:
> 10.times { n = generate_id ; puts "%10d = %s" % [n, encode(n)] }
2574974483 = dyhjOg
3636751446 = QxyuDj
368621501 = bBGvYa
1689949688 = yuTgxe
1457610999 = NqzsRd
3936504298 = MPpusk
133820481 = PQLpsa
2956135596 = yvXpOh
3269402651 = VFUhFi
724653758 = knLfVb
Due to the nature of the LCG, the generated id will not repeat until all 2³² values have been used exactly once each.
There is no way you can generate a unique UUID with only five chars, with chars and numbers you have a basic space of around 56 chars, so there is a max of 56^5 combinations , aprox 551 million (Around 2^29).
If with this scheme you were about to generate 10.000 UUIDs (A very low number of UUIDs) you would have a probability of 1/5.000 of generating a collision.
When using crypto, the standard definition of a big enough space to avert collisions is around 2^80.
To put this into perspective, your algorithm would be better off if it generated just a random integer (a 32 bit uint is 2^32, 8 times the size you are proposing) which is clearly a bad idea.
I'm puzzling over how to map a set of sequences to consecutive integers.
All the sequences follow this rule:
A_0 = 1
A_n >= 1
A_n <= max(A_0 .. A_n-1) + 1
I'm looking for a solution that will be able to, given such a sequence, compute a integer for doing a lookup into a table and given an index into the table, generate the sequence.
Example: for length 3, there are 5 the valid sequences. A fast function for doing the following map (preferably in both direction) would be a good solution
1,1,1 0
1,1,2 1
1,2,1 2
1,2,2 3
1,2,3 4
The point of the exercise is to get a packed table with a 1-1 mapping between valid sequences and cells.
The size of the set in bounded only by the number of unique sequences possible.
I don't know now what the length of the sequence will be but it will be a small, <12, constant known in advance.
I'll get to this sooner or later, but though I'd throw it out for the community to have "fun" with in the meantime.
these are different valid sequences
1,1,2,3,2,1,4
1,1,2,3,1,2,4
1,2,3,4,5,6,7
1,1,1,1,2,3,2
these are not
1,2,2,4
2,
1,1,2,3,5
Related to this
There is a natural sequence indexing, but no so easy to calculate.
Let look for A_n for n>0, since A_0 = 1.
Indexing is done in 2 steps.
Part 1:
Group sequences by places where A_n = max(A_0 .. A_n-1) + 1. Call these places steps.
On steps are consecutive numbers (2,3,4,5,...).
On non-step places we can put numbers from 1 to number of steps with index less than k.
Each group can be represent as binary string where 1 is step and 0 non-step. E.g. 001001010 means group with 112aa3b4c, a<=2, b<=3, c<=4. Because, groups are indexed with binary number there is natural indexing of groups. From 0 to 2^length - 1. Lets call value of group binary representation group order.
Part 2:
Index sequences inside a group. Since groups define step positions, only numbers on non-step positions are variable, and they are variable in defined ranges. With that it is easy to index sequence of given group inside that group, with lexicographical order of variable places.
It is easy to calculate number of sequences in one group. It is number of form 1^i_1 * 2^i_2 * 3^i_3 * ....
Combining:
This gives a 2 part key: <Steps, Group> this then needs to be mapped to the integers. To do that we have to find how many sequences are in groups that have order less than some value. For that, lets first find how many sequences are in groups of given length. That can be computed passing through all groups and summing number of sequences or similar with recurrence. Let T(l, n) be number of sequences of length l (A_0 is omitted ) where maximal value of first element can be n+1. Than holds:
T(l,n) = n*T(l-1,n) + T(l-1,n+1)
T(1,n) = n
Because l + n <= sequence length + 1 there are ~sequence_length^2/2 T(l,n) values, which can be easily calculated.
Next is to calculate number of sequences in groups of order less or equal than given value. That can be done with summing of T(l,n) values. E.g. number of sequences in groups with order <= 1001010 binary, is equal to
T(7,1) + # for 1000000
2^2 * T(4,2) + # for 001000
2^2 * 3 * T(2,3) # for 010
Optimizations:
This will give a mapping but the direct implementation for combining the key parts is >O(1) at best. On the other hand, the Steps portion of the key is small and by computing the range of Groups for each Steps value, a lookup table can reduce this to O(1).
I'm not 100% sure about upper formula, but it should be something like it.
With these remarks and recurrence it is possible to make functions sequence -> index and index -> sequence. But not so trivial :-)
I think hash with out sorting should be the thing.
As A0 always start with 0, may be I think we can think of the sequence as an number with base 12 and use its base 10 as the key for look up. ( Still not sure about this).
This is a python function which can do the job for you assuming you got these values stored in a file and you pass the lines to the function
def valid_lines(lines):
for line in lines:
line = line.split(",")
if line[0] == 1 and line[-1] and line[-1] <= max(line)+1:
yield line
lines = (line for line in open('/tmp/numbers.txt'))
for valid_line in valid_lines(lines):
print valid_line
Given the sequence, I would sort it, then use the hash of the sorted sequence as the index of the table.