My code is designed to count the the letters that appears in 2 separate names, including the overlapping characters. it should take two names (name = 1st name + last name) and count the number of times the letters "T R U E L O V E" show up.
My code is:
''' # 🚨 Don't change the code below 👇
print("Welcome to the Love Calculator!")
name1 = (input("What is your name? \n"))
name2 = input("What is their name? \n")
# 🚨 Don't change the code above 👆
#Write your code below this line 👇
names = name1 + name2
lowernames = names.lower()
t = lowernames.count("t")
r = lowernames.count("r")
u = lowernames.count("u")
e = lowernames.count("e")
l = lowernames.count("l")
o = lowernames.count("o")
v = lowernames.count("v")
e = lowernames.count("e")
true = t + r + u + e
love = l + o + v + e
love_score = int(str(true) + str(love))
print(love_score)
if (love_score < 10) or (love_score > 90):
print(f"your love score is {score} you fit together like montos and coke")
elif (love_score >= 45) and (love_score <= 50):
print(f"your love score is {love_score} you are alright together")
else:
print(f"your love score is {love_score}")
'''
The names I've entered in are:
Yonatan Allon (should give 2 O's and 2 L's)
Guy Hazan (one U)
I don't get why the score that comes up is 24 and not 41
Can someone please help me fix this?
Thanks in advance, Yonatan :)
Related
I'm wondering if anyone knows any tools which allow me to count the frequency of amino acids at any specific position in a multiple-sequence alignment.
For example if I had three sequences:
Species 1 - MMRSA
Species 2 - MMLSA
Species 3 - MMRTA
I'd like for a way to search by position for the following output:
Position 1 - M = 3;
Position 2 - M = 3;
Position 3 - R = 2, L = 1;
Position 4 - S = 2, T = 1;
Position 5 - A = 3.
Thanks! I'm familiar with R and Linux, but if there's any other software that can do this I'm sure I can learn.
Using R:
x <- read.table(text = "Species 1 - MMRSA
Species 2 - MMLSA
Species 3 - MMRTA")
ixCol = 1
table(sapply(strsplit(x$V4, ""), "[", ixCol))
# M
# 3
ixCol = 4
table(sapply(strsplit(x$V4, ""), "[", ixCol))
# S T
# 2 1
Depending input file format, there are likely a purpose built bioconductor packages/functions.
That is really easy to parse, you can use any language of choice.
Here is an example in Python using a dict and Counter to assemble the data in a simple object.
from collections import defaultdict, Counter
msa = '''
Species 1 - MMRSA
Species 2 - MMLSA
Species 3 - MMRTA
'''
r = defaultdict(list) #dictionary having the sequences index as key and the list of aa found at that index as value
for line in msa.split('\n'):
line = line.strip()
if line:
sequence = line.split(' ')[-1]
for i, aa in enumerate(list(sequence)):
r[i].append(aa)
count = {k:Counter(v) for k,v in r.items()}
print(count)
#{0: Counter({'M': 3}), 1: Counter({'M': 3}), 2: Counter({'R': 2, 'L': 1}), 3: Counter({'S': 2, 'T': 1}), 4: Counter({'A': 3})}
To print the output as you specified:
for k, v in count.items():
print(f'Position {k+1} :', end=' ') #add 1 to start counting from 1 instead of 0
for aa, c in v.items():
print(f'{aa} = {c};', end=' ')
print()
It prints:
Position 1 : M = 3;
Position 2 : M = 3;
Position 3 : R = 2; L = 1;
Position 4 : S = 2; T = 1;
Position 5 : A = 3;
I hope everyone is doing fine. I try to do some combinations of sets, but I have no clue how. If anyone can point me in any direction, it will be great. Here is the problem:
M = FiniteEnumeratedSet({1, 2})
P1 = cartesian_product([M]*2)
P1 = P.list()
P2 = cartesian_product([M]*4)
P2 = [p for p in P2 if p[0] <= p[1]]
C = P1 + P2 #len(C) total columns
R = P1*3 #len(R) total rows
What I would like to do is to construct a matrix where the number of columns represents the set C (16 columns) and the number of rows represents R (12 lines). The rule for each entrance it will be (some function entries):
if (i,j) in R and [(i,j) in C:
return -1
elif if (i,j) in R and [(i,u,j,v) in C or (u,i,v,j) in C]:
return 1
else:
return 0
Unfortunately, I have no idea how to define the function entries that works.
Thank you.
I'm trying to solve a linear system in Julia with ldlfact. Why am I getting different results in the following cases?
Setup:
srand(10)
n = 7
pre = sprand(n,n,0.5)
H = pre + pre' + speye(n,n)
p_true = rand(n)
g = H*-p_true
fac = ldltfact(H; shift=0.0)
perm = fac[:p]
p1 = zeros(n)
p2 = zeros(n)
Case 1:
LDs = sparse(fac[:LD])
q1 = LDs\-g[perm]
p1[perm] = fac[:U]\q1
H*p - H*p_true
Case 2:
q2 = fac[:LD]\-g[perm]
p2[perm] = fac[:U]\q2
H*p2 - H*p_true
The solution p1 is wrong in the first case.
Couldn't post this nicely as a comment, so wanted to add for posterity. Solving Case 1 in the following way worked for this example (thanks to #DanGetz's post)
L = copy(LDs)
for i=1:size(L,1)
L[i,i] = 1.0
end
D = sparse(1:size(L,1),1:size(L,1),diag(LDs))
q1 = (L*D)\-g[perm]
p1[perm] = L'\q1
H*p1 - H*p_true
I'm trying to implement the spiking neuron of the Izhikevich model. The formula for this type of neuron is really simple:
v[n+1] = 0.04*v[n]^2 + 5*v[n] + 140 - u[n] + I
u[n+1] = a*(b*v[n] - u[n])
where v is the membrane potential and u is a recovery variable.
If v gets above 30, it is reset to c and u is reset to u + d.
Given such a simple equation I wouldn't expect any problems. But while the graph should look like , all I'm getting is this:
I'm completely at loss what I'm doing wrong exactly because there's so little to do wrong. I've looked for other implementations but the code I'm looking for is always hidden in a dll somewhere. However I'm pretty sure I'm doing exactly what the Matlab code of the author (2) is doing. Here is my full R code:
v = -70
u = 0
a = 0.02
b = 0.2
c = -65
d = 6
history <- c()
for (i in 1:100) {
if (v >= 30) {
v = c
u = u + d
}
v = 0.04*v^2 + 5*v + 140 - u + 0
u=a*(b*v-u);
history <- c(history, v)
}
plot(history, type = "l")
To anyone who's ever implemented an Izhikevich model, what am I missing?
usefull links:
(1) http://www.opensourcebrain.org/projects/izhikevichmodel/wiki
(2) http://www.izhikevich.org/publications/spikes.pdf
Answer
So it turns out I read the formula wrong. Apparently v' means new v = v + 0.04*v^2 + 5*v + 140 - u + I. My teachers would have written this as v' = 0.04*v^2 + 6*v + 140 - u + I. I'm very grateful for your help in pointing this out to me.
Take a look at the code that implements the Izhikevich model in R below. It results in the following R plots:
Regular Spiking Cell:
Chattering Cell:
And the R code:
# Simulation parameters
dt = 0.01 # ms
simtime = 500 # ms
t = 0
# Injection current
I = 15
delay = 100 # ms
# Model parameters (RS)
a = 0.02
b = 0.2
c = -65
d = 8
# Params for chattering cell (CH)
# c = -50
# d = 2
# Initial conditions
v = -80 # mv
u = 0
# Input current equation
current = function()
{
if(t >= delay)
{
return(I)
}
return (0)
}
# Model state equations
deltaV = function()
{
return (0.04*v*v+5*v+140-u+current())
}
deltaU = function()
{
return (a*(b*v-u))
}
updateState = function()
{
v <<- v + deltaV()*dt
u <<- u + deltaU()*dt
if(v >= 30)
{
v <<- c
u <<- u + d
}
}
# Simulation code
runsim = function()
{
steps = simtime / dt
resultT = rep(NA, steps)
resultV = rep(NA, steps)
for (i in seq(steps))
{
updateState()
t <<- dt*(i-1)
resultT[i] = t
resultV[i] = v
}
plot(resultT, resultV,
type="l", xlab = "Time (ms)", ylab = "Membrane Potential (mV)")
}
runsim()
Some notes:
I've picked the parameters for the "Regular Spiking (RS)" cell from Izhikevich's site. You can pick other parameters from the two upper-right plots on that page. Uncomment the CH parameters to get a plot for the "Chattering" type cell.
As commenters have suggested, the first two equations in the question are incorrectly implemented differential equations. The correct way to implement the first one would be something like: "v[n+1] = v[n] + (0.04*v[n]^2 + 5*v[n] + 140 - u[n] + I) * dt". See the code above for example. dt refers to the user specified time step integration variable and usually dt << 1 ms.
In the for loop in the question, the state variables u and v should be updated first, then the condition checked after.
As noted by others, a current source is needed for both of these cell types. I've used 15 (I believe these are pico amps) from this page on the author's site (bottom value for I in the screenshot). I've also implemented a delay for the current onset (100 ms parameter).
The simulation code should implement some kind of time tracking so it's easier to know when the spikes are occurring in resulting plot. The above code implements this, and runs the simulation for 500 ms.
So here is my situation. Ive been trying to make a advanced calculator in python 3.4, one where you can just type something like this. '1 + 1', and it would then give you the answer of '2'. Now i will explain how my calculator is supposed to work. So you start by entering a maths equation, then it counts the words you entered based on the spaces. It does this so it knows how long some future loops need to be. Then it splits up everything that you entered. It splits it up into str's and int's but its all still in the same variable and it's all still in order. The thing i'm having trouble with is when it is meant to actually do the calculations.
here is all of my code-
# This is the part were they enter the maths equation
print("-------------------------")
print("Enter the maths equation")
user_input = input("Equation: ")
# This is were it counts all of the words
data_count = user_input.split(" ")
count = data_count.__len__()
# Here is were is splits it into str's and int's
n1 = 0
data = []
if n1 <= count:
for x in user_input.split():
try:
data.append(int(x))
except ValueError:
data.append(x)
n1 += 1
# And this is were it actually calculates everything
number1 = 0
number2 = 0
n1 = 0
x = 0
answer = 0
while n1 <= count:
#The code below checks if it is a number
if data[n1] < 0 or data[n1] > 0:
if x == 0:
number1 = data[n1]
elif x == 1:
number2 = data[n1]
elif data[n1] is "+":
if x == 0:
answer += number1
elif x == 1:
answer += number2
n1 += 1
x += 1
if x > 1:
x = 0
print("Answer =", answer)
but during the calculation it messes up and gives me and error
error-
if data[n1] < 0 or data[n1] > 0:
TypeError: unorderable types: str() < int()
can anyone see what i am doing wrong here?
Thanks
When you are comparing a string and an integer, this problem comes.
Python doesn't guess, it throws an error.
To fix this, simply call int() to convert your string to an integer:
int(input(...))
So, corrected statement should be:
if int(data[n1]) < 0 or int(data[n1]) > 0: