I have two lists of coordinates which should have some overlap (within a certain range) and I'm trying to output a new list which contains all of the coords which are contained in one list but not the other. See first image below for plot of these lists.
Points in each list might be slightly different so I'm allowing for a small amount around each point.
So far I have something like what's shown below which outputs the opposite of what I want - all of the points which are the in common between the two lists.
range = 0.33
different_points = [[],[]]
for i in range(len(All_points[0])):
for j in range(len(Initial_points[1][0])):
if Initial_points[0][j] - range <= All_points[0][i] <= Initial_points[0][j] + range and Initial_points[1][j] - range <= All_points[1][i] <= Initial_points[1][j] + range:
different_points[0].append((All_points[1][0][i]))
different_points[1].append((All_points[1][1][i]))
I'm struggling how to find the opposite list or if there's a much simpler way of doing this as a whole which I'm missing.
Thanks in advance for the help.
Use sets. In particular, intersection and difference.
Either it will help you, or I misunderstood your question completely.
Related
I have a rather complex list of dictionaries with nested dictionaries and arrays. I am trying to figure out a way to either,
make the list of data less complicated and then loop through the
raster points or,
find a way to loop through the array of raster points as is.
What I am ultimately trying to do is loop through all raster points within each polygon, perform a simple greater than or less than on the value assigned to that raster point (values are elevation values). If greater than a given value assign 1, if less than given value assign 0. I would then create a separate array of these 1s and 0s of which I can then get an average value.
I have found all these points (allpoints within pts), but they are in arrays within a dictionary within another dictionary within a list (of all polygons) at least I think, I could be wrong in the organization as dictionaries are rather new to me.
The following is my code:
import numpy as np
def mystat(x):
mystat = dict()
mystat['allpoints'] = x
return mystat
stats = zonal_stats('acp.shp','myGeoTIFF.tif')
pts = zonal_stats('acp.shp','myGeoTIFF.tif', add_stats={'mystat':mystat})
Link to my documents. Any help or direction would be greatly appreciated!
I assume you are using rasterstats package. You could try something like this:
threshold_value = 15 # You may change this threshold value to yours
for o_idx in range(0, len(pts)):
data = pts[o_idx]['mystat']['allpoints'].data
for d_idx in range(0, len(data)):
for p_idx in range(0, len(data[d_idx])):
# You may change the conditions below as you want
if data[d_idx][p_idx] > threshold_value:
data[d_idx][p_idx] = 1
elif data[d_idx][p_idx] <= threshold_value:
data[d_idx][p_idx] = 0;
It is going to update the data within the pts list
I have an idea but I'm stuck with implemention for something basic.
I'm trying to make a points division (Limited number of points) to a certain amount of objects. What does that mean-
If we assume I have 100 points divided into 5 objects, let's say we'll list the objects in the list:
[1,2,3,4,5]
The first place in list will have the highest number of points. Then the second highest place followed and so on ..
I want a function that divides the following points in descending order according to a given function (eg linear, exponential, constant, etc.)
I hope I explained well .. I did my best :)
Does anyone know a package in Python or a nice way to implement such a thing?
Let's say you have a list of the objects to which you want to give points. Then you can do:
totpoints=100
score=[] #this list holds the score based on position
totscore=0 #this will be the sum of all the scores
for i in range(len(lst)): #lst is the list
if mode=="linear":
score[i]=i
elif mode=="quadratic":
score[i]=i*i
elif mode=="exponential":
score[i]=exp(i)
else: #constant
score[i]=1
for i in score:
totscore+=i
for i in range(len(lst)):
lst[i].send(round(score[i]*totpoints/totscore)
#assuming you send the values by some method of the objects
This actually gives the most points to the ones with an higher index, so you would first reverse the score list to get higher-first.
Obviously the best way to use this is inside a function that you'll then be able to call with different modes, totpoints and lsts.
GOTCHA: this may give out a larger or smaller number of points than you actually wanted, depending on the rounding of the values. If you need to be precise add a check for the total number of points you send.
I was almost forgetting: if you need the points as a list, you can do
points=[round(s*totpoints/totscore) for s in score]
Good evening, StackOverflow.
Lately, I've been wrestling with a Python program which I'll try to outline as briefly as possible.
In essence, my program plots (and then fits a function to) graphs. Consider this graph.
The graph plots just fine, but I'd like it to do a little more than that: since the data is periodic over an interval OrbitalPeriod (1.76358757), I'd like it to start with our first x value and then iteratively plot all of the points OrbitalPeriod away from it, and then do the same exact thing over the next region of length OrbitalPeriod.
I know that there is a way to slice lists in Python of the form
croppedList = List[a:b]
where a and b are the indices of the first and last elements you'd like to include in the new list, respectively. However, I have no idea what the indices are going to be for each of the values, or how many values fall between each OrbitalPeriod-sized interval.
What I want to do in pseudo-code looks something like this.
croppedList = fullList on the domain [a + (N * OrbitalPeriod), a + (N+1 * OrbitalPeriod)]
where a is the x-value of the first meaningful data point.
If you have a workaround for this or a cropping method that would accept values instead of indices as arguments, please let me know. Thanks!
If you are working with numpy, you can use it inside the brackets
m = x
M = x + OrbitalPeriod
croppedList = List[m <= List]
croppedList = croppedList[croppedList < M]
I want to build an algorithm in python to flip linestrings (arrays of coordinates) in a linestring collection which represent segments along a road, so that I can merge all coordinates into a single array where the coordinates are rising monotonic.
So my Segmentcollection looks something like this:
segmentCollection = [['1,1', '1,3', '2,3'],
['4,3', '2,3'],
['4,3', '7,10', '5,5']]
EDIT: SO the structure is a list of lists of 2D cartesian coordinate tuples ('1,1' for example is a point at x=1 and y=1, '7,10' is a point at x=7 and y=10, and so on). The whole problem is to merge all these lists to one list of coordinate tuples which are ordered in the sense of following a road in one direction...in fact these are segments which I get from a road network routing service,but I only get segments,where each segment is directed the way it is digitized in the database,not into the direction you have to drive. I would like to get a single polyline for the navigation route out of it.
So:
- I can assume, that all segments are in the right order
- I cannot assume that the Coordinates of each segment are in the right order
- Therefore I also cannot assume that the first coordinate of the first segment is the beginning
- And I also cannot assume that the last coordinate of the last segment is the end
- (EDIT) Even thought I Know,where the start and end point of my navigation request is located,these do not have to be identical with one of the coordinate tuples in these lists,because they only have to be somewhere near a routing graph element.
The algorithm should iterate through every segment, flip it if necessary, and append it then to the resulting array. For the first segment,the challenge is to find the starting point (the point which is NOT connected to the next segment). All other segments are then connected with one point to the last segment in the order (a directed graph).
I'd wonder if there isn't some kind of sorting data structure (sorting tree or anything) which does exactly that. Could you please give some ideas? After messing around a while with loops and array comparisons my brain is knocked out, and I just need a kick into the right direction in the true sense of the word.
If I understand correctly, you don't even need to sort things. I just translated your English text into Python:
def joinSegments( s ):
if s[0][0] == s[1][0] or s[0][0] == s[1][-1]:
s[0].reverse()
c = s[0][:]
for x in s[1:]:
if x[-1] == c[-1]:
x.reverse()
c += x
return c
It still contains duplicate points, but removing those should be straightforward.
def merge_seg(s):
index_i = 0
while index_i+1<len(s):
index_j=index_i+1
while index_j<len(s):
if c[index_i][-1] == c[index_j][0]:
c[index_i].extend(c[index_j][1:])
del c[index_j]
elif c[index_i][-1] == c[index_j][-1]:
c[index_i].extend(c[index_j].reverse()[1:])
del c[index_j]
else:
index_j+=1
index_i+=1
result = []
s.reverse()
for seg_index in range(len(s)-1):
result+=s[seg_index][:-1]#use [:-1] to delete the duplicate items
result+=s[-1]
return result
In inner while loop,every successive segment of s[index_i] is appended to s[index_i]
then index_i++ until every segments is processed.
therefore it is easy to proof that after these while loops, s[0][0] == s[1][-1], s[1][0] == s[2][-1], etc. so just reverse the list and put them together finally you will get your result.
Note: It is the most simple and straightford way, but not most time efficient.
for more algo see:http://en.wikipedia.org/wiki/Sorting_algorithm
You say that you can assume that all segments are in the right order, which means that independently of the coordinates order, your problem is basically to merge sorted arrays.
You would have to flip a segment if it's not defined in the right order, but this doesn't have a single impact on the main algorithm.
simply defind this reordering function:
def reorder(seg):
s1 = min(seg)
e1 = max(seg)
return (s1, e1)
and this comparison funciton
def cmp(seg1, seg2):
return cmp(reorder(seg1), reorder(seg2))
and you are all set, just run a typical merge algorithm:
http://en.wikipedia.org/wiki/Merge_algorithm
And in case, I didn't really understand your problem statement, here's another idea:
Use a segment tree which is a structure that is made exactly to store segments :)
Having not worked with cartesian graphs since high school, I have actually found a need for them relevant to real life. It may be a strange need, but I have to allocate data to points on a cartesian graph, that will be accessible by calling cartesian coordinates. There needs to be infinite points on the graphs. For Eg.
^
[-2-2,a ][ -1-2,f ][0-2,k ][1-2,p][2-2,u]
[-2-1,b ][ -1-1,g ][0-1,l ][1-1,q][1-2,v]
<[-2-0,c ][ -1-0,h ][0-0,m ][1-0,r][2-0,w]>
[-2--1,d][-1--1,i ][0--1,n][1-1,s][2-1,x]
[-2--2,e][-1--2,j ][0--2,o][1-2,t][2-2,y]
v
The actual values aren't important. But, say I am on variable m, this would be 0-0 on the cartesian graph. I need to calculate the cartesian coordinates for if I moved up one space, which would leave me on l.
Theoretically, say I have a python variable which == ("0-1"), I believe I need to split it at the -, which would leave x=0, y=1. Then, I would need to perform (int(y)+1), then re-attach x to y with a '-' in between.
What I want to be able to do is call a function with the argument (x+1,y+0), and for the program to perform the above, and then return the cartesian coordinate it has calculated.
I don't actually need to retrieve the value of the space, just the cartesian coordinate. I imagine I could utilise re.sub(), however I am not sure how to format this function correctly to split around the '-', and I'm also not sure how to perform the calculation correctly.
How would I do this?
To represent an infinite lattice, use a dictionary which maps tuples (x,y) to values.
grid[(0,0)] = m
grid[(0,1)] = l
print(grid[(0,0)])
I'm not sure I fully understand the problem but I would suggest using a list of lists to get the 2D structure.
Then to look up a particular value you could do coords[x-minX][y-minY] where x,y are the integer indices you want, and minX and minY are the minimum values (-2 in your example).
You might also want to look at NumPy which provides an n-dim object array type that is much more flexible, allowing you to 'slice' each axis or get subranges. The NumPy documentation might be helpful if you are new to working with arrays like this.
EDIT:
To split a string like 0-1 into the constituent integers you can use:
s = '0-1'
[int(x) for x in s.split('-')]
You want to create a bidirectional mapping between the variable names and the coordinates, then you can look up coordinates by variable name, apply your function to it, then find the next variable using the new set of coordinates produced by your function.
Mapping between numeric tuples you can apply your function to, and strings usable as keys in a dict, and back, is easy.