like below fixes the issue Here is a reasonably efficient way. It works by (1) first ignoring the minimum wait. (2) computing intereventtimes (3) adding the minimum wait,(4) going back to absolute times discarding events that have been shifted out the right end. It can create 10**7 samples in less than a second. code :
import numpy as np
def train(T, dt, rate, min_wait):
p = dt*rate
# correct for minimum wait
if p:
p = 1 / (1 / p  min_wait)
if p > 0.1:
print("warning: probability too high for approximation to be good")
n = int(np.ceil(T/dt))
raw_times, = np.where(np.random.random(n) < p)
raw_times[1:] += min_wait  raw_times[:1]
good_times = raw_times.cumsum()
cut = good_times.searchsorted(n)
result = np.zeros(n, int)
result[good_times[:cut]] = 1
return result
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Is it possible for Git to enforce spacing conventions on the serverside?
By : freedom_sky
Date : March 29 2020, 07:55 AM
will help you Based on the comments and additional research, it appears Git's collaboration model makes it very difficult to force things on the server side. My final solution was to use the filter I had and distribute a simple script for users to run to add the relevant configs to their system (as per the answer to Can I specify .git/config values in a repo).

how to enforce some spacing between the elements of 'addCategoryAxis'
By : MIKEL
Date : March 29 2020, 07:55 AM
this will help Ok, so on the advice of @thisOneGuy I started playing around with increasing the width, and it worked. At first I tried to increase the width too much and the chart just disappeared (if anyone knows why that happened I would be interested to hear about it in the comments perhaps)

Insert elements into numpy array so that the minimum spacing is arbitrary
By : pfc
Date : March 29 2020, 07:55 AM
will help you Here is a onepass solution that 1) calculates the differences d between consecutive points code :
def fill(data, step, force_power_of_two=True):
d = data.copy()
d[1:] = data[:1]
if force_power_of_two:
m = 1 << (np.frexp(np.nextafter(d / step, 1))[1]).clip(0, None)
else:
m = (d // step).astype(int)
m[0] = 1
d /= m
return np.cumsum(d.repeat(m))
>>> inp
array([10.08 , 14.23 , 19.47 , 21.855, 24.34 , 25.02 ])
>>> fill(inp, 3)
array([10.08 , 12.155, 14.23 , 16.85 , 19.47 , 21.855, 24.34 , 25.02 ])

I wrote A Code In Python To find Max And Minimum Of 4 elements out of array of 5 elements
By : user3284443
Date : March 29 2020, 07:55 AM
seems to work fine The issue your current code has isn't with large numbers, but with index 3. You never exclude that index from your calculations, so if it is the largest of smallest in your list, you'll get the wrong results. The reason you never skip index 3 is that your outer loop runs is on range(0, 4), and the inner loop is too. That means you take four items, starting at indexes 0 through 3. But you never start at index 4, which is the situation where index 3 would be skipped. code :
for i in range(0, 5): # replace 4 with 5 here!
sum1=0
for j in range(0,4):
...
def miniMaxSum(arr):
arr_sum = sum(arr)
min_val = min(arr)
max_val = max(arr)
print("Minimum:", arr_sum  max_val, "Maximum:", arr_sum  min_val)

Find the minimum sum of 'P' elements in an array of N elements such that no more than 'k' consecutive elements are selec
By : user4671689
Date : March 29 2020, 07:55 AM
like below fixes the issue Below is a Java Dynamic Programming algorithm. (the C++ version should look very similar)

