I keep getting this error when I try to compile. I am not quite sure what the issue is. I am not the best at coding, and thus, debugging is not my strong suit. Any ideas whats causing the error?
PROGRAM Atmospheric_Reflection
IMPLICIT NONE
REAL*8:: Wavelength = 0.200D-6, WaveNumber = 0.0, pi = 3.14159265, Length(1:71) = 0, Number(1:71) = 0, IndexOfRe(1:71) = 0
INTEGER:: i = 0
!Calculate the wave number for wavelengths varying from 0.2 micrometers to 1.6 micrometers in increments of 0.02 micrometers
i = 1
DO WHILE (Wavelength <= 1.600D-6)
WaveNumber = 1/Wavelength
Length(i) = Wavelength
Number(i) = WaveNumber
IndexOfRe(i) = 1 + (((5791817.0/(238.0185 - WaveNumber**2))+(167909.0/(57.362-WaveNumber**2))))D-8
Wavelength = Wavelength + 0.02D-6
i = i+1
END DO
END PROGRAM
Possibly the D-8 at the end of this line
IndexOfRe(i) = 1 + (((5791817.0/(238.0185 - WaveNumber**2))+(167909.0/(57.362-WaveNumber**2))))D-8
Related
Quick explanation, I have recently started using codewars to further improve my programming skills and my first challenge was to make a roman numeral decoder, I went through many versions because I wasnt satisfied with what I had, So I am asking if there is an easier way of handling all the patterns that roman numerals have, for example I is 1 but if I is next to another number it takes it away for example V = 5 but IV = 4.
here is my CODE:
function Roman_Numerals_Decoder (roman)
local Dict = {I = 1, V = 5, X = 10, L = 50, C = 100, D = 500, M = 1000}
local number = 0
local i = 1
while i < #roman + 1 do
local letter = roman:sub(i,i) -- Gets the current character in the string roman
if roman:sub(i,i) == "I" and roman:sub(i + 1,i + 1) ~= "I" and roman:sub(i + 1,i + 1) ~= "" then -- Checks for the I pattern when I exists and next isnt I
number = number + (Dict[roman:sub(i +1,i + 1)] - Dict[roman:sub(i,i)]) -- Taking one away from the next number
i = i + 2 -- Increase the counter
else
number = number + Dict[letter] -- Adds the numbers together if no pattern is found, currently checking only I
i = i + 1
end
end
return number
end
print(Roman_Numerals_Decoder("MXLIX")) -- 1049 = MXLIX , 2008 = MMVIII
at the moment I am trying to get 1049 (MXLIX) to work but I am getting 1069, obviously I am not following a rule and I feel like its more wrong then it should be because usually if its not correct its 1 or 2 numbers wrong.
The algorithm is slightly different: you need to consider subtraction when the previous character has less weight than the next one.
function Roman_Numerals_Decoder (roman)
local Dict = {I = 1, V = 5, X = 10, L = 50, C = 100, D = 500, M = 1000}
local num = 0
local i = 1
for i=1, #roman-1 do
local letter = roman:sub(i,i) -- Gets the current character in the string roman
local letter_p = roman:sub(i+1,i+1)
if (Dict[letter] < Dict[letter_p]) then
num = num - Dict[letter] -- Taking one away from the next number
print("-",Dict[letter],num)
else
num = num + Dict[letter] -- Adds the numbers together if no pattern is found, currently checking only I
print("+",Dict[letter],num)
end
end
num = num + Dict[roman:sub(-1)];
print("+",Dict[roman:sub(-1)], num)
return num
end
print(Roman_Numerals_Decoder("MXLIX")) -- 1049 = MXLIX , 2008 = MMVIII
I'm trying to run an optimization with SNOPT.
Right now as I run it I consistently get exit condition 41.
I've added the following parameters to the solver:
prog.SetSolverOption(solver.solver_id(),"Function Precision","1e-6")
prog.SetSolverOption(solver.solver_id(),"Major Optimality Tolerance","1e-3")
prog.SetSolverOption(solver.solver_id(),"Superbasics limit","600")
#print("Trying to Solve")
result = solver.Solve(prog)
print(result.is_success())
But I still contently get the same exit condition.
The error seems to be from the interpolation function I'm using. (When I remove it I no longer get the error).
t, c, k = interpolate.splrep(sref, kapparef, s=0, k=3)
kappafnc = interpolate.BSpline(t, c, k, extrapolate=False)
Here is the function I think I determined was causing the issue:
def car_continous_dynamics(self, state, force, steering):
beta = steering
s = state[0]
#print(s)
n = state[1]
alpha = state[2]
v = state[3]
#State = s, n, alpha , v
#s= distance along the track, n = perpendicular distance along the track
#alpha = velocity angle relative to the track
#v= magnitude of the velocity of the car
s_val = 0
if s.value() >0:
s_val = s.value()
Cm1 = 0.28
Cm2 = 0.05
Cr0 = 0.011
Cr2 = 0.006
m = 0.043
phi_dot = v*beta*15.5
Fxd = (Cm1 - Cm2 * v) * force - Cr2 * v * v - Cr0 *tanh(5 * v)
s_dot = v*cos(alpha+.5*beta)/(1)##-n*self.kappafunc(s_val))
n_dot= v*sin(alpha+.5*beta)
alpha_dot = phi_dot #-s_dot*self.kappafunc(s_val)
v_dot=Fxd/m*cos(beta*.5)
# concatenate velocity and acceleration
#print(s_dot)
#print(n_dot)
#print(alpha_dot)
#print(v_dot)
state_dot = np.array((s_dot,n_dot,alpha_dot,v_dot))
#print("State dot")
#print(state_dot.dtype.name)
#print(state_dot)
#print(state_dot)
return state_dot
``
Debugging INFO 41 in SNOPT is generally challenging, it is often caused by some bad gradient (but could also due to the problem being really hard to optimize).
You should check if your gradient is well-behaved. I see you have
s_val = 0
if s.value() >0:
s_val = s.value()
There are two potential problems
Your s carries the gradient (you could check s.derivatives(), it has non-zero gradient), but when you compute s_val, this is a float object with no gradient. Hence you lose the gradient information.
s_val is non-differentiable at 0.
I would use s instead of s_val in your function (without the branch if s.value() > 0). And also add a constraint s>=0 by
prog.AddBoundingBoxConstraint(0, np.inf, s)
With this bounding box constraint, SNOPT guarantees that in each iteration, the value of is is always non-negative.
While experimenting with word embedding using text2vec package in R, the following error is thrown
embd_dim <- 5
glove_event <- GlobalVectors$new(rank = embd_dim, x_max = 10,learning_rate = 0.01, alpha = 0.95, lambda = 0.005)
wrd_embd_event <- glove_event$fit_transform(tcm_event, n_iter = 200, convergence_tol = 0.001)
Error in glove_event$fit_transform(tcm_event, n_iter = 200, convergence_tol = 0.001) :
Cost is too big, probably something goes wrong... try smaller learning rate
Smaller learning rate has not helped. Similar outcome from experiment with different skip_grams_window values in ctreate_tcm() and different rank values in glove_event().
I am clueless about the source of this error.
I have a .log file that looks like this :
--hh:mm:ss
10:15:46
10:09:33
10:27:26
10:09:49
09:54:21
10:10:25
And what I need to do is to calculate the average on those timestamps, I wrote a function to calculate the average :
function calculate_average_working_hours(working_day_diff)
local current_hour, current_minutes, current_secondes = 0, 0, 0
local total_hour, total_minutes, total_secondes = 0, 0, 0
local working_days_counter = #working_day_diff
for key, value in pairs(working_day_diff) do
current_hour, current_minutes, current_secondes = extract_timestamp_value(value) --covert the values to numbers
total_hour = total_hour + current_hour
total_minutes = total_minutes + current_minutes
total_secondes = total_secondes + current_secondes
end
total_hour = math.ceil(total_hour / working_days_counter)
total_minutes = math.ceil(total_minutes / working_days_counter)
total_secondes = math.ceil(total_secondes / working_days_counter)
return ("%02d:%02d"):format(total_hour, total_minutes)
end
So basically what I'm doing is to sum the seconds, minutes, and hours and divide the results by the number of logs,
for example if i have 10:15:46 and 10:09:33 i will add the seconds, minutes and hours and divide it by 2
is this the correct way to calculate the average of timestamps values?
I would be something like this solved the problem:
--- example 1
local log = [[--hh:mm:ss
10:15:46
10:09:33
10:27:26
10:09:49
09:54:21
10:10:25
]]
local function seconds(v)
local h,m,s = v:match("(%d%d):(%d%d):(%d%d)")
if h and m and s then return h*3600+m*60+s else return nil end
end
local i,sum = 0, 0
for line in log:gmatch('(.-)[\r\n]') do
local r = seconds(line)
if r then i=i+1; sum = sum+r end
end
print(sum,i, os.date("!%X",sum/i) )
I am trying to perform arithmetic on table values and keep getting an error. Here is my total code. I am basically trying to generate simplex noise. I have created a multidimensional array (table) and am trying to perform operations on the values but i keep getting an error that says I cannot perform arithmetic on a table value. I don't know If I have to convert it to something or what. Please Help.
totalNoiseMap = {}
function simplex_noise(width, height)
simplexnoise = {}
for i = 1,512 do
simplexnoise[i] = {}
for j = 1, 512 do
simplexnoise[i][j] = 0
end
end
frequency = 5.0 / width
for x = 1, width do
for y = 1, height do
simplexnoise[x][y] = noise(x * frequency,y * frequency)
simplexnoise[x][y] = (simplexnoise[x][y] + 1) / 2
end
end
return simplexnoise
end
function noise(x, y, frequency)
return simplex_noise(x / frequency, y / frequency)
end
function generateOctavedSimplexNoise(width,height,octaves,roughness,scale)
totalnoise = {}
for i = 1,512 do
totalnoise[i] = {}
for j = 1, 512 do
totalnoise[i][j] = 0
end
end
layerFrequency = scale
layerWeight = 1
weightSum = 0
for octave = 1, octaves do
for x = 1, width do
for y = 1, height do
totalnoise[x][y] = (totalnoise[x][y] + noise(x * layerFrequency,y * layerFrequency, 2) * layerWeight)
end
end
--Increase variables with each incrementing octave
layerFrequency = layerFrequency * 2
weightSum = weightSum + layerWeight
layerWeight = layerWeight * roughness
end
return totalnoise
end
totalNoiseMap = generateOctavedSimplexNoise(512, 512, 3, 0.4, 0.005)
totalnoise[x][y] + noise(x * layerFrequency,y * layerFrequency, 2) * layerWeight
Here you get table noise(x * layerFrequency,y * layerFrequency, 2), mult it by scalar layerWeight and than add it to scalar totalnoise[x][y].
I can think of how to multiply table by scalar - it should be something like
for i = 1,512 do
for j = 1,512 do
a[i][j] = t[i][j] * scalar
end
end
But I'm unable to get what you're trying to do by adding. Suppose it should be addition of two tables
for i = 1,512 do
for j = 1,512 do
a[i][j] = b[i][j] + c[i][j]
end
end
But it works only with same-sized tables