I have the data (RA and Dec values) for all the knots in a galaxy that is inclined, with the angle of inclination being 41 degrees. How can I estimate the deprojected distance? I found one paper van der Marel and Cioni (2001) (https://iopscience.iop.org/article/10.1086/323099/fulltext/201194.text.html). Are there any other papers I can refer to?
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Can anyone help .
I now know how to convert Home,Draw,Away probabilities to Asian handicap lines usin excel e.g.:
At first let’s take a look at the simpler situations where the handicap is half a goal or zero
goals (=no advatage for either team).
Handicaps marked as 0:0 are identical to moneyline bets (which is a term used in
America for this type of bet). In moneyline you bet on which team will win the game.
And if the game ends with a draw the stakes will (usually) be fully refunded. And
because the result from refunded stake is exactly the same as if the bet was never placed,
the possibility of draw can be excluded from the set.
The true odds (in decimal presentation) for moneyline can be derived from the
probabilities of home win, draw and away win in the following way:
Home Odds = (1 - p0) / p1
Away Odds = (1 - p0) / p2,
where p1 is the probability for home win (a value between 0 and 1), p0 the probability for
draw (0..1) and p2 the probability for away win (0..1).
Numerical example:
If 1X2-probabilities for a game are 45% (= 0.45), 30% (= 0.30) and 25% (=0.25),
moneyline odds would be: 4
Home Odds = (1 - 0.30) / 0.45 = 1.56
Away Odds = (1 - 0.30) / 0.25 = 2.80
Now I'm stuck tryin to do the same for the over and under Asian goal lines.
what I am tryin to achieve is how this website does it
https://www.totalcorner.com/page/fulltime-asian-handicap-calculator
remember I know 1x2 Asian handicap formula and what I'm asking is help with the over/under goal lines.
Thanks in advance
How can I calaulate the 3D Manhattan distance on excel.
I know the 2D formula but I have absolutely no idea about the Manhattan distance formula for 3D
for example, now I have 2 points:
c1 = (6.25, 4.75, 5.25)
p1 = (8, 8, 1)
I have calculate it on the online Manhattan distance calculater, the anwers is 9.25
But I really want to know the formula
Thanks~
An average light bulb manufactured by Acme corporations lasts 300 days with a standard deviation of 50 days . Assuming that bulb life is normally distributed, what is the probability that an Acme light bulb will last at most 365 days?
How can the same be replicated in code in python?
mu = 10*30
std_d = 50
import math
def norm_pdf(x, mean, std):
variance = float(std)**2
denom = (2*math.pi*variance)**.5
num = math.exp(-(float(x)-float(mean))**2/(2*variance))
return num/denom
norm_pdf(12*30, mu, std_d)
Formula Refrence: Wikipedia
We have collected data in which we measured the length along a measuring tape where particular species overlapped it. In some cases multiple species may overlap it in the same spot. I need to figure out how much of the tape was overlapped by plants without counting the same length of tape twice when multiple plants overlap the same spot, and I need to do it grouped by vegetation type (e.g., shrub, tree, etc). So, I'm answering the question, "how much of the tape is covered by shrubs?" for example.
E.g., imagine the dashed line is the measuring tape, and the asterisks are all different shrubs overlapping the tape. This is what my data essentially represents right now. If I counted the length of all the shrubs, I would get a big number, longer than the actual length of the tape...
*** ** *********
**** ** *******
----------------------------
...but this is what I need to figure out, the actual length of tape covered by any shrub:
***** ** **************
----------------------------
I hope that makes sense, but here are some examples to explain further if needed:
Example: Imagine I encountered Doug Fir trees that overlapped the measuring tape stretching from the 4' mark to the 10' mark and the 20' mark to the 25' mark. I also encountered Spruce trees overlapping the tape from the 7' to 14' marks. I need to know the total length of overlap of tree species (these are both trees), so I will need to sum the lengths of these ranges for both Spruce and Doug Fir. However, if I just sum all the ranges normally, I will end up counting the 7' to 10' area (sum = 3') twice rather than once, where both Spruce and Doug Firs were covering the tape. So, I will need to subtract 3' from the final value so that this part of the measuring tape is not counted more than once. So, my ranges are 6', 5', and 7', which totals 18'. After subtracting the overlapping 3', that gives a total of 15' feet where trees overlap the tape.
Example table below. I already have the SPECIES, START, END, TYPE, and SUM data. What I need excel to help me compute are the values shown below the table, which are the sums after accounting for multiple-species overlap. E.g., if Shrub X overlapped from 10' to 20', and shrub Y overlapped from 13' to 25', the total overlap would be from 10' to 25' so fifteen feet of overlap. Not 22 ft overlap, which is what it would be if you counted each of the ranges separately.)
SPECIES START(ft) END(ft) TYPE SUM (ft)
Dogwood 40.3 40.9 Shrub 0.6
Cedar 52.8 79.5 Tree 26.7
Dogwood 50.2 55.6 Shrub 5.4
Rose 53.8 54.4 Shrub 0.6
Alder 88.2 95.5 Tree 7.3
Clover 75.8 76.2 Forb 0.4
Bunch 82.8 90.3 Grass 7.5
Poa 86.1 95.3 Grass 9.2
Sedge 99.4 100.9 Grass 1.5
Bttrcp 74.5 101.3 Forb 26.8
Elder 105.8 120.3 Shrub 14.5
Bttrcp 110.3 120.2 Forb 9.9
Cedar 90.4 99.9 Tree 9.5
SHRUB SUM TREE SUM FORB SUM GRASS SUM
20.5 38.4 35.4 14
Any guidance in figuring this out would be much appreciated!
Here is some pseudo code that might work. Also, this is only estimated for each TYPE. To get the whole area, repeat for each TYPE:
get_max_area(data):
sort(data, START)
for i <- 1 to n:
for j <- i to n:
if data[j][START] < data[i][START]: // Two segments overlap
if data[j][END] < data[i][END]: // j is fully contained within i
ignore(data[j])
else: // They just overlap
merge(data[i], data[i + 1])
// ELSE: independent segments
return sum(data[SUM])
Ignoring means the segment is not tested anymore. Merging means making segment a(i, j) and b(x, y) a new segment c(i, y). This is just a quick approach, and it takes O(n^2). There must be a better approach.
I've got a big number of nodes (lon,lat) in WGS-84 and I need to draw them on a Pixmap, so I have read a lot of Q&A here, but haven't found the algorithm how to convert lon/lat from WGS-84 to a x/y coordinates. By the way, I need to draw a simple scheme of map. Any ideas?
To go from WGS-84 latitude and longitude to an two-dimensional map, you first need to consider what kind of projection you have. This is because one minute of arc, for example, could mean different distance changes over a particular projection. You're mapping an ellipsoid to a plane, so you're going to get some distortion somewhere.
But for a simple case, let's say that your area is small enough, and close enough to the equator, that the change in angle (latitude or longitude) corresponds to a constant change in distance on the map (Y or X).
So, if you have a 600*600 image of a particular area, and it corresponds to a 10-minute by 10-minute area of the earth that has an upper-left corner at 30 degrees north, 40 degrees west.
To locate the pixel where 29 degrees, 55 minutes north, 39 degrees, 57 minutes west, we use a proportion for both latitude and longitude:
5' / 10' = Y / 600 pixels ---> Y = 300 (from the top edge)
3' / 10' = X / 600 pixels ---> X = 180 (from the left edge)
Hope that helps.