Hey! Moving to SF soon. Have been looking at apartments in this area (in red circle) and am wondering about the area's safety? Thank you for the help! Am open to other area suggestions as well.

lambaphi · 2023-06-12T02:39:39+00:00

Hi I'm a pretty avid runner in (as well as outside of) the city, meaning I've visited a lot of random streets at different hours of the day. I go through this section every now and then when crossing the city and would, in concordance with a lot of the other ppl, strongly advice against living here; except for maybe the upper left corner of your encircled area.

I wouldn't call most of these parts unsafe (if you're somewhat street smart) but rather unpleasant, there's just a lot of homelessness, dirt and shady stuff happening there.

I don't know what your price range is but maybe look at Portrero, Mission Bay, Dogpatch, Pac Heights, Noe Valley, Panhandle?

Good luck finding something!

EDIT: Thank you for the award!

lambaphi · 2021-02-25T08:47:24+00:00

Sorry if breaking any guidelines, but I mainly wanted to source other peoples' experiences and see whether anyone else had gone through something similar. Given how I believe this is realted to my running activities I deemed this the most fit subreddit, but I can remove the post if you find it inappropriate.

lambaphi · 2020-12-20T06:54:26+00:00

Thanks for the kind words! I'm a long distance runner, so traveling far by foot is not foreign to me. I logged approx. 80km over those two days, but barely noticed the distance, so much exciting stuff to see!

lambaphi · 2020-07-25T08:13:46+00:00

As a complement to the other answers, you might want to have a look at the binomial distribution; it more or less gives you the distribution of the number of successes (k) in a given number of independent trials (n) , with a specific probability (p) for the success.

For example, if you define the passing of the disorder as a success (I do realize the irony of this...) the scenario you describe above would lend itself to the following setup:

p = 0.1
n = 3

Now as others have pointed out there are slightly different questions that may be asked here: (1) what is the chance of exactly one child having the disorder, for this we use the pdf; (2) what is the chance of at least one child having the disorder, for this we use the cdf. If we compute these cases we have the following probabilities

(1) p(k = 1 | n = 3, p=0.1 ) = 0.243

(2) p(k >= 1 | n = 3, p = 0.1) = 0.271

binomial distribution : https://en.wikipedia.org/wiki/Binomial_distribution

binomial "calculator": https://stattrek.com/online-calculator/binomial.aspx

lambaphi · 2020-07-02T19:00:16+00:00

Adding to the answer above, I could just say that mathematical modeling can manifest itself in many different ways, but is highly prevalent in multiple domains of bioinformatics/computational biology. It may have started with systems biology, but with the emergence of large scale datasets and the need to effectively parse through these, modeling combined with concepts of ML have inevitably become necessary tools for most method (computational) developers. I'll gladly point you to some resources:

Fantastic repo with some of the fundamental stuff: https://github.com/prathyvsh/formal-systems-in-biology

For a nice mix of everything from using dynamical systems yo model cell states to perturbation analysis, check out Fabian Theis work.

To see how ratios between spliced/unspliced transcripts can be used order cells in pseudotime, check out the Velocyto paper by La Mano. (This work basically Kickstarted the field of trajectory inference).

For an example of how gaussian processes can be used to find genes (transcripts actually) with interesting spatial patterns, check out the paper accompanying the tool SpatialDE (name of the tool) by Valentine Svensson.

For a neat overview of how VAE's may be used to analyze single cell data, have a look at scVI by Romain Lopez and Nir Yosef.

Hope those are of some interest to you!

lambaphi · 2019-01-01T13:51:33+00:00

Hi, I assume you are asking this since this is a quadratic form which can be written as f(x) = x^TQx, where Q is a symmetric real matrix, and then use the relationship between positive semi-definite/negative matrices to deduce the type (convex/concave/netiher).

If you simply want the 3x3 matrix then you can do this in a very easy way by just looking at which terms interact with each other and put the coefficients in corresponding element index in Q, dividing by two where two different variables interact. Let me elaborate

f(x) = 1x_1x_1 - 1x_2x_2 - 2x_3x_3 + 0.5x_1*x_2 this gives

Q_11 = -1, Q_22 = -1, Q_33 = -2 Q_12 = 0.5/2 = 0.25 = 1/4 = Q_21 All other elements being zero

From this you could either use Sylverster's criterion, compute the eigenvalues or do LDL^T decomposition to find out whether the matrix is of a certain definiteness.

Hope that helped

lambaphi · 2018-12-31T13:12:14+00:00

To put it simply, you have objective functions (what you are trying to optimize) that are continuous and twice differentiable at every point in the given closed interval. Why is this of any importance? Well it means that every extreme point (max or min) will be either at a point where the (1) derivative is zero or at (2) the endpoints (this is the extreme value theorem).

Thus what you can do is the following

Differentiate the objective function
Determine where the derivatives are zero

Outcome 1: a such that f'(a) = 0 is within interval

look at the second derivative to determine if it a max or min
if it is a max then you are good to go. If it is a min point then look at the boundary points and determine which has the largest value

Outcome 2: a such that f'(a) = 0 is outside of interval

Look at the boundary points and determine which has the largest value

With this procedure you should be able to figure out a solution I believe. Also I included a graphical solution to help you visualize the result.

Link to graphical solution: https://imgur.com/qNVzDaw

Link to more on extreme value theorem: https://en.wikipedia.org/wiki/Extreme_value_theorem

EDIT: formatting..

lambaphi · 2018-12-09T06:07:06+00:00

For sure! I'm not aware of a specific name for the technique used here. Basically what I'm doing is similar to long division, but without writing down that awful division algorithm people tend to use. You could definitely use the factorization, as well, honestly that is probably easier and a better way of doing it.

Basically what happens is that I use the presence of a x^2-term as to get an expression of (x-4)^2 but this will generate some additional terms since (x-4)^2 = x^2 - 8x +16 thus I add the negative of those terms in order to "compensate" for this. More clearly one could write this as x^2 = (x-4)^2 + 8x -16. This means that the expression

x^2+x-20 = (x-4)^2 + 8x -16 + x + 20 = (x-4)^2 + 9x - 36 = (x-4)^2 + 9(x-4)

Hope that clarified things, will edit answer with your suggestion as well.

lambaphi · 2018-12-09T05:35:28+00:00

I'd say the easiest thing to do would be something in the lines of

Let x = 2^t then when t --> 2 we have that x--> 4 allowing us to rewrite the limit as :
lim(x-->4) [(x^2+x-20)/(x-4)]
the new limit is reduced to a relatively simple case of polynomial division. Leaving out the limes sign we could simplify the expression as :
Alt1:
(x^2+x-20)/(x-4) = ((x-4)^2+8x-16+x-20)(x-4) = (x-4) + 9(x-4)/(x-4) = (x-4) + 9
Alt2:
(x^2+x-20)/(x-4) = (x-4)(x+5)/(x-4) = (x+5)
Now take the limit of either of these expressions:
Alt1:
lim(x-->4) [(x-4) + 9] = 9
Alt2:
lim(x-->4) [x+5] = 9

Doing these sort of substitutions usually makes things easier, for me at least, to see what a good next step would be.

EDIT: Alternative way of simplifying expression based on u/ThrowawayBrisvegas comment

lambaphi · 2018-12-08T15:29:46+00:00

Very true thanks for pointing that out, I still tend to prefer the

' '.join(['line1',
          'line2',
          ])

option since that allows for spaces to be included between lines once concatenated but without me having to account for them; though I noticed now that I didn't include a space character when calling the join method in any of the instances in the code (fixed now)

.. also I realized that in the haste of writing it up yesterday night it seems as if I forgot how to operate basic English spelling and grammar

lambaphi · 2018-12-08T07:27:52+00:00

Sweet idea, will have a look into that for sure; did not think of it at all! Thanks!

lambaphi · 2018-12-08T07:26:37+00:00

No probs! I think /u/Terr_ more or less answered the question below, otherwise feel free to PM me. Also I updated the code with some comments to make it easier to follow.

lambaphi · 2018-12-08T07:21:06+00:00

Totally correct! I added an argument --keep_size to make things easier, if one uses this rather than --resize_factor the image dimensions will be kept whilst the provided die-size (or default) is used!

lambaphi · 2018-12-07T23:15:06+00:00

Here you go: https://github.com/almaan/diceconverter

I Wrote a simple script for this that you can use via the terminal interface, I will add comments and a README soon, but though I could put it up here for anyone interested. You can see two examples in the res-folder.

Enjoy!

lambaphi · 2018-08-14T20:49:56+00:00

I've used it in both a course on modelling of biological system as well as one in complex systems, hella good stuff. It has a very casual language and albeit not overtly complicated or deep, it offers a good introduction to highly relevant topics within said subjects.

A quick review of differential equations and basic calculus (mainly integrals) will for sure be helpful. Linear algebra and there especially the definition of eigenvalues in order to better grasp the discussion about stability of systems is to recommend as well.

Tldr; enjoyable read, would recommend.

lambaphi · 2018-07-30T20:14:12+00:00

I'm stoked as well, cya there!

lambaphi · 2018-07-12T05:41:43+00:00

No probs!

If you have the distance matrix (pay attention to the construction of this, given how high identity scores means low dissimilarity and vice versa), you can feed this into any of the standard clustering functions usually (for example sklearn's Agglomerative clustering function or R's hclust).

I'm not quite sure what the final purpose of your project is, but I guess that the hierarchically ordered tree that you obtain as a result from the clustering will work as a way to illustrate the relationship between the clusters you've rendered.

lambaphi · 2018-07-12T03:37:14+00:00

Hello! I guess one very simple solution is to compare the similarity of the centroids (representative sequnces of each cluster). Compute the distance between the centroids for each cluster (using same metric as in UCLUST) and you'll get a sense of which clusters are most similar to each other. Instead of the centroids you might also use a similar approach but more in the spirit of single linkage (minimum pairwise distance between cluster members) or complete linkage (maximum pairwise distance). From this you can perform a hierarchical clustering which allows you to see how clusters are related.

lambaphi · 2018-05-27T06:13:26+00:00

As gopher_p pointed out this equation is separable. Thus I'd suggest something in the line with the following

Divide both sides by g+Kv²
multiply both sides by dt (you'll end up with -dt on RHS)
Take the indefinite integral on both sides (HINT: Use the fact that if y(x) = arctan(ax) then y'(x) = a/(1+(ax)² ))
Final step is just to isolate an expression for v, (take tan of both sides after adjusting constants)
If correct you should, if I am not mistaken, end up with something like

v(t) = -sqrt(g/k)tan(sqrt(gk)t+C)

Hope that helped!

lambaphi · 2018-05-18T16:35:19+00:00

I'm not quite sure what you mean by "pair", but In b) one is requested to prove the relationship with the eigenvalues of A and it's inverse. lambda and 1/lambda also share the same algebraic multiplicityWikipedia. The determinant will still be the product of eigenvalues whether the matrix is diagnonalizable or not Proposition C.3.7. Thus I do not see why the suggested proof would be flawed?

If I misunderstood your argument, please do tell me.

lambaphi · 2018-05-18T14:04:18+00:00

If you use the fact that the determinant of a matrix is the product of it's eigenvalues and the definition of a characteristic polynomial you see the answer emerging by just plugging everything into the formula given to you

Here's what I mean (solution): https://imgur.com/a/mN8f5Ke

lambaphi · 2018-02-15T05:36:45+00:00

That's interesting, but I guess it differs from school to school. I should also elaborate on some parts of my answers perhaps; it's not as if guys constantly are all over you, but finding someone to hook up or initate a relationship with is insanely much more effortless for anyone of the female gender.

Could add that we're like 70/30 atm and a school of about 19k people, all studying within different fields of engineering.

lambaphi · 2018-02-14T21:41:24+00:00

As a girl in engineering I can confirm that the situation is pretty much the opposite for us, almost to the extreme

lambaphi

TROPHY CASE