import numpy
def rtpairs(R,T):
for i in range(numpy.size(R)):
o=0.0
for j in range(T[i]):
o +=2*(numpy.pi)/T[i]
yield R[i],o
R=[0.0,0.1,0.2]
T=[1,10,20]
for r,t in genpolar.rtpairs(R,T):
plot(r*cos(t),r*sin(t),'bo')
This program is supposed to be a generator, but I would like to check if i'm doing the right thing by first asking it to return some values for pheta (see below)
import numpy as np
def rtpairs (R=None,T=None):
R = np.array(R)
T = np.array(T)
for i in range(np.size(R)):
pheta = 0.0
for j in range(T[i]):
pheta += (2*np.pi)/T[i]
return pheta
Then
I typed import omg as o in the prompt
x = [o.rtpairs(R=[0.0,0.1,0.2],T=[1,10,20])]
# I tried to collect all values generated by the loops
It turns out to give me only one value which is 2 pi ... I have a habit to check my codes in the half way through, Is there any way for me to get a list of angles by using the code above? I don't understand why I must use a generator structure to check (first one) , but I couldn't use normal loop method to check.
Normal loop e.g.
x=[i for i in range(10)]
x=[0,1,2,3,4,5,6,7,8,9]
Here I can see a list of values I should get.
return pheta
You switched to return instead of yield. It isn't a generator any more; it's stopping at the first return. Change it back.
x = [o.rtpairs(R=[0.0,0.1,0.2],T=[1,10,20])]
This wraps the rtpairs return value in a 1-element list. That's not what you want. If you want to extract all elements from a generator and store them in a list, call list on the generator:
x = list(o.rtpairs(R=[0.0,0.1,0.2],T=[1,10,20]))
Related
Background:I have two catalogues consisting of positions of spatial objects. My aim is to find the similar ones in both catalogues with a maximum difference in angular distance of certain value. One of them is called bss and another one is called super.
Here is the full code I wrote
import numpy as np
def crossmatch(bss_cat, super_cat, max_dist):
matches=[]
no_matches=[]
def find_closest(bss_cat,super_cat):
dist_list=[]
def angular_dist(ra1, dec1, ra2, dec2):
r1 = np.radians(ra1)
d1 = np.radians(dec1)
r2 = np.radians(ra2)
d2 = np.radians(dec2)
a = np.sin(np.abs(d1-d2)/2)**2
b = np.cos(d1)*np.cos(d2)*np.sin(np.abs(r1 - r2)/2)**2
rad = 2*np.arcsin(np.sqrt(a + b))
d = np.degrees(rad)
return d
for i in range(len(bss_cat)): #The problem arises here
for j in range(len(super_cat)):
distance = angular_dist(bss_cat[i][1], bss_cat[i][2], super_cat[j][1], super_cat[j][2]) #While this is supposed to produce single floating point values, it produces numpy.ndarray consisting of three entries
dist_list.append(distance) #This list now contains numpy.ndarrays instead of numpy.float values
for k in range(len(dist_list)):
if dist_list[k] < max_dist:
element = (bss_cat[i], super_cat[j], dist_list[k])
matches.append(element)
else:
element = bss_cat[i]
no_matches.append(element)
return (matches,no_matches)
When put seperately, the function angular_dist(ra1, dec1, ra2, dec2) produces a single numpy.float value as expected. But when used inside the for loop in this crossmatch(bss_cat, super_cat, max_dist) function, it produces numpy.ndarrays instead of numpy.float. I've stated this inside the code also. I don't know where the code goes wrong. Please help
I have an array of time values. I want to know how many values are in each 0.05 seconds window.
For example, some values of my array are: -1.9493, -1.9433, -1.911 , -1.8977, -1.8671,..
In the first interval of 0.050 seconds (from -1.9493 to -1.893) I´m expecting to have 3 elements
I already create another array with the 0.050 seconds steps.
a=max(array)
b=min(array)
ventanalinea1=np.arange(b,a,0.05)
v1=np.array(ventanalinea1)
In other words, I would like to compare my original array with this one.
I would like to know if there is a way to ask python to evaluate my array within a given dynamic range.
One of the variants:
import numpy as np
# original array
a = [-1.9493, -1.9433, -1.911 , -1.8977, -1.8671]
step = 0.05
bounds = np.arange(min(a), max(a) + step, step)
result = [
list(filter(lambda x: b[i] <= x <= b[i+1], a))
for i in range(len(b)-1)
]
I have found a cool python library python-intervals that simplify your problem a lot:
Install it with pip install python-intervals and try the code below.
import intervals as I
# This is a recursive function
def counter(timevalues, w=0.050):
if not timevalues:
return "" # stops recursion when timevalues is empty
# Make an interval object that provides convenient interval operations like 'contains'
window = I.closed(
timevalues[0], timevalues[0] + w)
interval = list(
filter(window.contains, timevalues))
count = len(interval)
timevalues = timevalues[count:]
print(f"[{interval[0]} : {interval[-1]}] : {count}")
return counter(timevalues)
if __name__ == "__main__":
times = [-1.9493, -1.9433, -1.911, -1.8977, -1.8671]
print(counter(times))
Adapt it as you wish, for example you might want to return a dictionary rather that a string.
You could still get around this without using the python-intervals library here but i have introduced it here because it will be very likely that you would need other complex operations along the way on your code.
How do you get the very next list within a nested list in python?
I have a few lists:
charLimit = [101100,114502,124602]
conditionalNextQ = [101101, 101200, 114503, 114504, 124603, 124604]`
response = [[100100,4]
,[100300,99]
,[1100500,6]
,[1100501,04]
,[100700,12]
,[100800,67]
,[100100,64]
,[100300,26]
,[100500,2]
,[100501,035]
,[100700,9]
,[100800,8]
,[101100,"hello"]
,[101101,"twenty"] ... ]
for question in charLimit:
for limitQuestion in response:
limitNumber = limitQuestion[0]
if question == limitNumber:
print(limitQuestion)
The above code is doing what I want, i.e. printing the list instances in response when it contains one of the numbers in charlimit. However, I also want it to print the immediate next value in response also.
For example the second-to-last value in response contains 101100 (a value thats in charlimit) so I want it to not only print
101100,"hello"
(as the code does at the moment)
but the very next list also (and only the next)
101100,"hello"
101101,"twenty"
Thank is advance for any help here. Please note that response is a verrrrry long list and so I'm looking to make things fairly efficient if possible, although its not crucial in the context of this work. I'm probably missing something very simple but cant find examples of anyone doing this without using specific indexes in very small lists.
You can use enumerate
Ex:
charLimit = [101100,114502,124602]
conditionalNextQ = [101101, 101200, 114503, 114504, 124603, 124604]
response = [[100100,4]
,[100300,99]
,[1100500,6]
,[1100501,04]
,[100700,12]
,[100800,67]
,[100100,64]
,[100300,26]
,[100500,2]
,[100501,035]
,[100700,9]
,[100800,8]
,[101100,"hello"]
,[101101,"twenty"]]
l = len(response) - 1
for question in charLimit:
for i, limitQuestion in enumerate(response):
limitNumber = limitQuestion[0]
if question == limitNumber:
print(limitQuestion)
if (i+1) <= l:
print(response[i+1])
Output:
[101100, 'hello']
[101101, 'twenty']
I would eliminate the loop over charLimit and loop over response instead. Using enumerate in this loop allows us to access the next element by index, in the case that we want to print it:
for i, limitQuestion in enumerate(response, 1):
limitNumber = limitQuestion[0]
# use the `in` operator to check if `limitNumber` equals any
# of the numbers in `charLimit`
if limitNumber in charLimit:
print(limitQuestion)
# if this isn't the last element in the list, also
# print the next one
if i < len(response):
print(response[i])
If charLimit is very long, you should consider defining it as a set instead, because sets have faster membership tests than lists:
charLimit = {101100,114502,124602}
I want to make a list of elements where each element starts with 4 numbers and ends with 4 letters with every possible combination. This is my code
import itertools
def char_range(c1, c2):
"""Generates the characters from `c1` to `c2`"""
for c in range(ord(c1), ord(c2)+1):
yield chr(c)
chars =list()
nums =list()
for combination in itertools.product(char_range('a','b'),repeat=4):
chars.append(''.join(map(str, combination)))
for combination in itertools.product(range(10),repeat=4):
nums.append(''.join(map(str, combination)))
c = [str(x)+y for x,y in itertools.product(nums,chars)]
for dd in c:
print(dd)
This runs fine but when I use a bigger range of characters, such as (a-z) the program hogs the CPU and memory, and the PC becomes unresponsive. So how can I do this in a more efficient way?
The documentation of itertools says that "it is roughly equivalent to nested for-loops in a generator expression". So itertools.product is never an enemy of memory, but if you store its results in a list, that list is. Therefore:
for element in itertools.product(...):
print element
is okay, but
myList = [element for itertools.product(...)]
or the equivalent loop of
for element in itertools.product(...):
myList.append(element)
is not! So you want itertools to generate results for you, but you don't want to store them, rather use them as they are generated. Think about this line of your code:
c = [str(x)+y for x,y in itertools.product(nums,chars)]
Given that nums and chars can be huge lists, building another gigantic list of all combinations on top of them is definitely going to choke your system.
Now, as mentioned in the comments, if you replace all the lists that are too fat to fit into the memory with generators (functions that just yield), memory is not going to be a concern anymore.
Here is my full code. I basically changed your lists of chars and nums to generators, and got rid of the final list of c.
import itertools
def char_range(c1, c2):
"""Generates the characters from `c1` to `c2`"""
for c in range(ord(c1), ord(c2)+1):
yield chr(c)
def char(a):
for combination in itertools.product(char_range(str(a[0]),str(a[1])),repeat=4):
yield ''.join(map(str, combination))
def num(n):
for combination in itertools.product(range(n),repeat=4):
yield ''.join(map(str, combination))
def final(one,two):
for foo in char(one):
for bar in num(two):
print str(bar)+str(foo)
Now let's ask what every combination of ['a','b'] and range(2) is:
final(['a','b'],2)
Produces this:
0000aaaa
0001aaaa
0010aaaa
0011aaaa
0100aaaa
0101aaaa
0110aaaa
0111aaaa
1000aaaa
1001aaaa
1010aaaa
1011aaaa
1100aaaa
1101aaaa
1110aaaa
1111aaaa
0000aaab
0001aaab
0010aaab
0011aaab
0100aaab
0101aaab
0110aaab
0111aaab
1000aaab
1001aaab
1010aaab
1011aaab
1100aaab
1101aaab
1110aaab
1111aaab
0000aaba
0001aaba
0010aaba
0011aaba
0100aaba
0101aaba
0110aaba
0111aaba
1000aaba
1001aaba
1010aaba
1011aaba
1100aaba
1101aaba
1110aaba
1111aaba
0000aabb
0001aabb
0010aabb
0011aabb
0100aabb
0101aabb
0110aabb
0111aabb
1000aabb
1001aabb
1010aabb
1011aabb
1100aabb
1101aabb
1110aabb
1111aabb
0000abaa
0001abaa
0010abaa
0011abaa
0100abaa
0101abaa
0110abaa
0111abaa
1000abaa
1001abaa
1010abaa
1011abaa
1100abaa
1101abaa
1110abaa
1111abaa
0000abab
0001abab
0010abab
0011abab
0100abab
0101abab
0110abab
0111abab
1000abab
1001abab
1010abab
1011abab
1100abab
1101abab
1110abab
1111abab
0000abba
0001abba
0010abba
0011abba
0100abba
0101abba
0110abba
0111abba
1000abba
1001abba
1010abba
1011abba
1100abba
1101abba
1110abba
1111abba
0000abbb
0001abbb
0010abbb
0011abbb
0100abbb
0101abbb
0110abbb
0111abbb
1000abbb
1001abbb
1010abbb
1011abbb
1100abbb
1101abbb
1110abbb
1111abbb
0000baaa
0001baaa
0010baaa
0011baaa
0100baaa
0101baaa
0110baaa
0111baaa
1000baaa
1001baaa
1010baaa
1011baaa
1100baaa
1101baaa
1110baaa
1111baaa
0000baab
0001baab
0010baab
0011baab
0100baab
0101baab
0110baab
0111baab
1000baab
1001baab
1010baab
1011baab
1100baab
1101baab
1110baab
1111baab
0000baba
0001baba
0010baba
0011baba
0100baba
0101baba
0110baba
0111baba
1000baba
1001baba
1010baba
1011baba
1100baba
1101baba
1110baba
1111baba
0000babb
0001babb
0010babb
0011babb
0100babb
0101babb
0110babb
0111babb
1000babb
1001babb
1010babb
1011babb
1100babb
1101babb
1110babb
1111babb
0000bbaa
0001bbaa
0010bbaa
0011bbaa
0100bbaa
0101bbaa
0110bbaa
0111bbaa
1000bbaa
1001bbaa
1010bbaa
1011bbaa
1100bbaa
1101bbaa
1110bbaa
1111bbaa
0000bbab
0001bbab
0010bbab
0011bbab
0100bbab
0101bbab
0110bbab
0111bbab
1000bbab
1001bbab
1010bbab
1011bbab
1100bbab
1101bbab
1110bbab
1111bbab
0000bbba
0001bbba
0010bbba
0011bbba
0100bbba
0101bbba
0110bbba
0111bbba
1000bbba
1001bbba
1010bbba
1011bbba
1100bbba
1101bbba
1110bbba
1111bbba
0000bbbb
0001bbbb
0010bbbb
0011bbbb
0100bbbb
0101bbbb
0110bbbb
0111bbbb
1000bbbb
1001bbbb
1010bbbb
1011bbbb
1100bbbb
1101bbbb
1110bbbb
1111bbbb
Which is the exact result you are looking for. Each element of this result is generated on the fly, hence never creates a memory problem. You can now try and see that much bigger operations such as final(['a','z'],10) are CPU-friendly.
I have some project which I decide to do in Python. In brief: I have list of lists. Each of them also have lists, sometimes one-element, sometimes more. It looks like this:
rules=[
[[1],[2],[3,4,5],[4],[5],[7]]
[[1],[8],[3,7,8],[3],[45],[12]]
[[31],[12],[43,24,57],[47],[2],[43]]
]
The point is to compare values from numpy array to values from this rules (elements of rules table). We are comparing some [x][y] point to first element (e.g. 1 in first element), then, if it is true, value [x-1][j] from array with second from list and so on. Five first comparisons must be true to change value of [x][y] point. I've wrote sth like this (main function is SimulateLoop, order are switched because simulate2 function was written after second one):
def simulate2(self, i, j, w, rule):
data = Data(rule)
if w.world[i][j] in data.c:
if w.world[i-1][j] in data.n:
if w.world[i][j+1] in data.e:
if w.world[i+1][j] in data.s:
if w.world[i][j-1] in data.w:
w.world[i][j] = data.cc[0]
else: return
else: return
else: return
else: return
else: return
def SimulateLoop(self,w):
for z in range(w.steps):
for i in range(2,w.x-1):
for j in range(2,w.y-1):
for rule in w.rules:
self.simulate2(i,j,w,rule)
Data class:
class Data:
def __init__(self, rule):
self.c = rule[0]
self.n = rule[1]
self.e = rule[2]
self.s = rule[3]
self.w = rule[4]
self.cc = rule[5]
NumPy array is a object from World class. Rules is list as described above, parsed by function obtained from another program (GPL License).
To be honest it seems to work fine, but it does not. I was trying other possibilities, without luck. It is working, interpreter doesn't return any errors, but somehow values in array changing wrong. Rules are good because it was provided by program from which I've obtained parser for it (GPL license).
Maybe it will be helpful - it is Perrier's Loop, modified Langton's loop (artificial life).
Will be very thankful for any help!
)
I am not familiar with Perrier's Loop, but if you code something like famous "game life" you would have done simple mistake: store the next generation in the same array thus corrupting it.
Normally you store the next generation in temporary array and do copy/swap after the sweep, like in this sketch:
def do_step_in_game_life(world):
next_gen = zeros(world.shape) # <<< Tmp array here
Nx, Ny = world.shape
for i in range(1, Nx-1):
for j in range(1, Ny-1):
neighbours = sum(world[i-1:i+2, j-1:j+2]) - world[i,j]
if neighbours < 3:
next_gen[i,j] = 0
elif ...
world[:,:] = next_gen[:,:] # <<< Saving computed next generation