hysteresis | a tape saturation vst

In the dts file of my kernel, I have:

I'm building a visitor counter in my room using Arduino, IR transmitter, and two SHARP IR sensors. The sensors count the number of people in my room - one person turns up the light, more do nothing, and zero turns the light off. The IR transmitter works great (it turns the light on/off) so as the detection, but I have a problem and a question.

My question is, is there an option to make a function and call it twice instead of repeating myself inside the loop? if so, how? they are mostly symmetric, but still have some differences like the flags and num_people manipulating.

My main problem right now is counting num_people and I found out that this line is the problem: num_people = (num_people > 0) ? num_people-1 : 0; When I put this line in a comment I can count more than one person, but when I'm not it runs over the code and counts 1,0,1,0,1,0 (only when getting inside the room). Need to say that when I go out it decreases num_people as it should and when on zero keeps that number.

The code is here:

I am plotting data in a scatterplot an I would like to see the direction of the hysteresis. Does anyone have a good idea how to implement arrows on each line that point into the direction of the next point?

Alternatively, the markers could be replaced by arrows pointing in the direction of the next point.

What I am looking for:

Code to obtain the plot (without arrows):

What I want to achieve can be described as follows:

• I have a stream of samples, wich are timestamped measurement values. This is the raw stream.
• I am applying a filter on the raw stream, whereby I get a derived stream (it will be the hysteresis filter from this question, but for the sake of simplicity I am using a Where operator here)
• To eliminate the big gaps resulting from slowly changing values, I am applying a Sample operator to the raw stream
• I am merging both streams into a resulting stream

The concept looks like this:

I need the functionality of a hysteresis filter in RX. It should emit a value from the source stream only when the previously emitted value and the current input value differ by a certain amount. As a generic extension method, it could have the following signature:

Using some code I calculate some numbers. I store those numbers in a pandas dataframe namely data_nn. I have many such data_nn generated in a for loop.

While looping want to concatenate the data_nn with a dataframe namely data_all. Finally I would export the data_all to a csv file. But the concatenation fails.

Below my code. It gives an error: 'cannot concatenate object of type ""; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid'

How to resolve this?

I have the following problem:

I'm writing a collection library for a bunch of sensors to be used with a microcontroller. Meaning I take a lot of libraries for sensors and abstract and simplify them a bit in a unified library for a student project.

I use #define structures to figure out which sensors the students want to use and connected.

Example:

Let A be a 1D numpy array, a threshold t, and a window length K.

How to find the minimal index j, such that A[j:j+K] < t? (i.e. the first time A stays below the threshold on a full window of width K).

I've tried (unfinished) things with a loop, but it seemed far from optimal, and I thought maybe there's a clever "numpy way" to do it.

Sidenote: the fact we want to test if we're below the threshold during a certain window length instead of ponctual value, is useful to avoid on/off/on/off/on/off artefacts near the threshold (see also Hysteresis: "hysteresis is intentionally added to an electronic circuit to prevent unwanted rapid switching [...] compensate for contact bounce in switches, or noise in an electrical signal.").

This is a follow up question to How can I fit a smooth hysteresis in R?. A straightforward application of smooth.spline fits my actual poorly, although it proved a useful generic idea for this type of problem and had worked well on my simulated toy dataset.

I uploaded an example of my dataset here.

Following image is created by the code at the end.

Thysteresis is not fully closed - but that's not an issue. Applying smooth.spline produces a way too messy output (red). Using argument spar in smooth.spline I was able to get a sufficiently smooth approximation (blue) - though it is only poorly following the curve of my data points on the upper right.

However what really disturbs me is the "knot" around the points in the lower left - even for the smooth curve (blue) it is there. It also has an artificial "loop" when it moves from the lower left to the upper right, although there are not data points near there.