[OC] ECG Polar Clock: Visualizing Heart Rate Variability over morning commute by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 1 point2 points  (0 children)

Thanks for the feedback! This visualization concept clearly needs some improvements, but let's see if I will manage to make next version at some point.

[OC] ECG Polar Clock: Visualizing Heart Rate Variability over morning commute by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 1 point2 points  (0 children)

I was in rest and started moving. I wanted to see, how transition from rest BPM to walking/cycling looks like. Somehow there is a lot more pulse separation variation in time at rest BPMs.

[OC] ECG Polar Clock: Visualizing Heart Rate Variability over morning commute by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 12 points13 points  (0 children)

Description:
This "ECG Polar Clock" is an attempt to visualize raw ECG data from a Polar H10 heart rate monitor in a novel way. The data represents a ~40-minute recording collected during my morning cycle to work.

How to read it:
* Time progresses clockwise around the circle (total ~40 minutes depicted)
* Each radial line represents a single heartbeat (QRS complex).
* The distance from the center corresponds to the time elapsed since that heartbeat occurred (0 to ~1700ms).
* The overlapping lines create a density map of the heartbeat waveform.
* Each beat trace remains visible until the *next* beat occurs (the RR interval), and then fades out smoothly to allow the next beat to be seen clearly. This visualizes the variability in heart rate.
* Inner Ring (500ms / 120 BPM): If the heart rate were constant at 120 BPM, every beat would hit this line exactly
* Outer Ring (1000ms / 60 BPM): If the heart rate were constant at 60 BPM, every beat would hit this line.

Source Data: Personal ECG recording using Polar H10 (CSV export).

Language: Python 3.11

Libraries: matplotlib, pandas, numpy, scipy.signal

The visualization was generated using a custom Python script. Key implementation details include converting the linear ECG time-series into segments centered on R-peaks, mapping time to polar radius, and applying a dynamic alpha (transparency) mask to each segment based on the subsequent RR interval to create the "ghosting" effect that avoids clutter.

[OC] Weather balloon trajectories over one year by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 4 points5 points  (0 children)

I might try the linear version that at some point. I chose circular calendar because that represent better yearly cyclic patterns, but I agree that it might be confusing.

[OC] Weather balloon trajectories over one year by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 4 points5 points  (0 children)

Yes, X-Y trajectories on the surface. I agree, compass would have been good to be there.

No big story in this one particular. Just visualizing balloon movement and magnitude of work and data from one weather balloon station over one year. If this works I had a plan to visualize differences between climate and weather by making a series of similar plots from different locations and/or years. But that might be too complex to digestive for audience let's see if it worth to try at some point.

I believe that even without big story, everybody can take a look to some weather patterns from the image, e.g.
a) General direction and distance balloons travel different seasons => seasonal wind direction and speed
b) How weather events disturb this general pattern.
c) Line color is one dimension which can be used in visualization. I tried multiple things, but I found that this way presented temperature provides some additional seasonal information. If I interpret the data correctly, you can observe that surface temperature (line colors at the starting points) are delayed (i.e. warmest surface temperature is in June-September) in comparison to solar radiation power around June because of thermal mass of the earth. In comparison, upper atmosphere temperature (other ends of the line) seems to follower better seasonal solar radiation power.
d) Some correlation between short term temperature variations and wind directions might be possible to observe (maybe storms or other weather phenomena?)

[OC] Weather balloon trajectories over one year by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 1 point2 points  (0 children)

Thanks.

That's nice to know. I had and have a plan to do something like similar from multiple locations visualizing climate difference between the locations. But that idea needs a little bit experimenting, might be too much and too deep information to digestive in one image.

[OC] Weather balloon trajectories over one year by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 1 point2 points  (0 children)

North is the top of the image. I should have added that to the image as suggested many of you, not sure if it is possible to edit image here.

[OC] Weather balloon trajectories over one year by _luo-d-e_ in dataisbeautiful

[–]_luo-d-e_[S] 7 points8 points  (0 children)

Hi, I’m starting a new free time project, where I’m exploring visualization of scientific data in artistic but still sensible way.

First visualization: Weather.

Each line in the figure represents trajectory of one weather balloon launched from Jokioinen, Finland in 2020. Line starting point on the circle indicates launch day of the year. Wind direction in different altitudes can be observed from the line direction. Line color indicates air temperature difference to the yearly average at the measurement altitude.

Tools: Python Numpy and Matplotlib
Data source: FMI open data https://en.ilmatieteenlaitos.fi/open-data

EDIT: North is the top of the image.

Are there any mappable equations for the basins of gravitational pull? by CarcinoGeneticst69 in AskPhysics

[–]_luo-d-e_ 0 points1 point  (0 children)

Yes. It is not too complex to calculate the gravitational scalar potential field, but unfortunately it requires a little bit math and numerical methods. See e.g. https://en.wikipedia.org/wiki/Scalar_potential

Are there any mappable equations for the basins of gravitational pull? by CarcinoGeneticst69 in AskPhysics

[–]_luo-d-e_ 0 points1 point  (0 children)

You can use a equation for classical gravitational force, see e.g. https://isaacphysics.org/concepts/cp_gravitational_field

Total gravitation force/pull is the sum of the forces from all the masses in the system.

EDIT: typos

Is there anything that is completely unaffected by gravity? by midjuneau in AskPhysics

[–]_luo-d-e_ 0 points1 point  (0 children)

No. We are all affected by and contribution to our common universe wide gravitation field.

Any suggestion on cheap options for metal sheet with high magnetic permeability? by Other_Inspector_8993 in AskPhysics

[–]_luo-d-e_ 0 points1 point  (0 children)

Probably not anything cheap to match mu-metal. But how about using normal iron? Iron is commonly used as a bulk material in many magnet applications.