Update Linux on laptop and try Influx there. Nope. The laptop is hosed.
Grabbing another computer to configure. I mean, worst case, I can set up the work laptop as an Ubuntu box. I’d love to know if Influx would work FIRST, though. Looks like I have to. My old dev box won’t boot. Backing up.
Installed Debian on the work laptop. It seems to be booting? Nope:
I guess we’ll try Ubuntu again? Nope. Trying one more variant.
Trying lubuntu. It uses different drivers for some things, and so far hasn’t frozen or blocked yet. It works!
And now the Docker version (docker run –name influxdb -p 9999:9999 quay.io/influxdb/influxdb:2.0.0-beta) works too. Maybe because the system got upgraded?
11:00 IRAD Meeting
Send note about NOAA being a customer for simulated anomalies for machine learning
Working from home has a different rhythm. I work in segments with home chores mixed in. Today I’m doing this at 6:00, along with some coding. Then some morning exercise, breakfast, and work till noon. Ride, lunch and more work till about 3:00. By that time my brain is broken, and I take a break and do light chores. Today I may finally get my road bike ready for spring. Then simple work like commenting for a few hours. In the evenings I find I like watching shows about competent people fixing things and making them better. Bitchin’ Rides is extremely soothing.
integrating the estimated deaths from rate and current deaths as area under the curve until zero.
Work on documentation. Also make sure word wrap works
This. Is. Bad.
Once more, this is Italy. What I’ve done is round-tripped the rates to produce an estimate of total deaths. If calculating rates is taking the derivative, calculating a death prediction is integration. So, if the calculations are right, and Italy is at zero new deaths around April 17th, the toll is around 27 thousand total deaths. That’s 0.04% of the population. If those numbers hold for the US at 327 million, that’s a total of 145,550. The White House is estimating numbers of 100,000 to 240,000, which means their average prediction is that we will fare worse than Italy.
Fixed bugs, worked with Zach, made progress. Aaron is starting to appear again!
Tweak John’s slides
More on saving and restoring docker containers. I think I’m close. Then install InfluxDB and test if I can see the dashboard
Still having problems. I can create, run, add, delete, and tag the images, but I can’t run them. I think I’m getting ahead of myself. Back to reading
So it turns out that I was doing everything right but the load. Here’s how it works
docker run container -it –name imagename some-os /bin/sh
Install what needs to be installed. Poke around, save things, etc
docker container commit imagename modified-os
docker save modified-os> modified-os.tar
docker rmi modified-os
docker load < modified-os.tar
docker run container -it –name imagename modified-os /bin/sh
I need to go grocery shopping today. A friend of mine has come down with the virus. He’s in his 30’s, and I’m feeling vulnerable. I went down to the shop and dug up my painting masks. Turns out I have a few, so that’s what I’m going shopping with. Here’s why, from the NY Times:
When researchers conducted systematic review of a variety of interventions used during the SARS outbreak in 2003, they found that washing hands more than 10 times daily was 55 percent effective in stopping virus transmission, while wearing a mask was actually more effective — at about 68 percent. Wearing gloves offered about the same amount of protection as frequent hand-washing, and combining all measures — hand-washing, masks, gloves and a protective gown — increased the intervention effectiveness to 91 percent.
A friend of mine who works in Whitehall has told me that the army are going to be on the streets this week arresting people who don’t listen to this podcast. If that sounds familiar, you’ll be aware that this crisis has already been fertile ground for disinformation. Marianna Spring is a BBC specialist reporter covering disinformation and social media. In this fascinating interview, Marianna reveals how disinformation and misinformation gets so widely shared, why we share it, how to spot it, what the trends are, how it differs around the world and so much more. This is a brilliant insight not just into the sharing of inaccurate information, but into human behaviour.
Changed the calculations from the linear regression to handle cases where the virus is under control, like China – first pass is done
Have the linear regression only go back some number of weeks/months. I’m worried about missing a second wave
Need to add a disclaimer about the quality of the predictions is dependent on the quality of the data, and that we expect that as poorer countries come online, these trends may be erratic and inaccurate.
Add an UNSET state. The ETS will only set the state if it is UNSET. This lets regression predictions to be used until the ETS is working well – done
I think showing the linear and ETS mean prediction is a good way to start including ETS values
Put together a list of potential papers to present. No need, I’ll do infinitely wide networks
Had just a lovely online evening of figuring out how to use some (terrible!) webex tools, and trying to figure out Neural ODEs. It was an island of geeky normalcy for a few hours. This may be a more comprehensible writeup.
Working with Zach and Aaron on the app. I think we’ll have something by this weekend
Added a starting zero on the regression
Added the regression to the json file, and posted to see if Zach can reach
Set up the hooks for export to excel workbook, with one tab per active country. I’ll work on that later today – done! countries
Got clarification from Wayne on some edits. Going to turn those around this morning and try to submit before COB today. Maryland is at 580 confirmed cases as of yesterday. I’d expect to see nearly 800 when they update the site this morning. Sent over all the edits. It’s in!
Waking up to the news these days makes me want to stay in bed with the radio off
Working on automating the process of downloading the spreadsheet, parsing out the countries, and calculating daily rates. The goal is to have a website up this weekend so you can see how your country is doing.
Set up converter class – done
download spreadsheet – done
parse out countries – working on it
Made mockups of the mobile and webpage displays, and refined a few times based on comments
Got notes for Chapter 11 from Wayne. Switching gears and rolling that in. Put in changes for all the items I could read. There are a few still outstanding. I’ll submit tonight if Wayne doesn’t come back for a discussion.
Back to Docker. Need to connect to the WLS. Done!
AIMS – status for all, plus technichal glitches. We’ll try Teams next time. Vadim has made GREAT progress. We might be able to get a real Yaw Flip soon as well
A2P – Infor demo. Meh.
Stampede theory proposal deadline was delayed a couple of days
Well, I’ve got more predictions using death rates as described in this post. Based on the latest dataset from here (Github), I’ve created a spreadsheet that does a linear (least squares) extrapolation for when the number of new deaths per day drops to zero:
China is in this group as a sanity check, and as you can see, it’s very near zero, and so is South Korea. Italy, Germany, Spain, Iran, and Indonesia are currently all in the middle, with 2-3 weeks to go if nothing changes. France, the Netherlands, and Switzerland are far enough out that I think these may be low confinance values. The UK seems to be doing terribly. The worst performers are Belgium and the US, whose death rates are still going up, as indicated by the “-1” in the “days till” column.
Here are plots of the data used to calculate the table. Due to the way that excel labels axis, I don’t have dates for the x-axis for all the charts. They all end on the seme date (3/21, the last day in the dataset with the two days I need to calculate rates), but some of them have fewer tata points so that the time before the outbreak doesn’t influence the calculations:
Working on Hours for misinfo proposal
Had a good chat with Biruh about InfluxDB running in Docker. Since I’m running the Windows version, things are different enough that I’m going to need to download a linux distro image and run my own version of InfluxDB2 inside that. Which means I need to get smarter on Docker and making a custom image, etc. Got this book. We’ll see how that goes today.
Yesterday, I looked at the confirmed cases from this dataset. Today, I thought I’d look at the death rates. These are actually from yesterday. Maybe I’ll update at the end of the day. Everything is in a logarithmic scale because it’s impossible to tell the difference between one crazy exponential rate and another (It may be small-world power law as well, as per here). This is also with China excluded:
I mean, that’s not a good picture. I can see why California went on full non-essential lockdown today – we seem to be on the same trajectory as Iran, assuming the difference in slope is not related to manipulated or poorly-gathered information. South Korea, as per reports, really has appeared to adjust the trajectory. Note though, that the adjusted curve still seems to be exponential, but at a lower value.
My sense right now is that the economic impacts (however those would be charted) are going to look similar, with some kind of time delay that relates to spare capacity, like savings. My sense is that this is going to be bigger than the 2008 financial meltdown, but maybe in some kind of slow motion?
Since I can work from home, and work on government contracts, I’ve been sending money to food banks and similar charities. Hopefully, the best ways to contribute will become clear as the situation settles into the new “normal”. For some more thinking on the economic impact, there’s a short interview with John Ioannidis, who wrote in this article:
One of the bottom lines is that we don’t know how long social distancing measures and lockdowns can be maintained without major consequences to the economy, society, and mental health. Unpredictable evolutions may ensue, including financial crisis, unrest, civil strife, war, and a meltdown of the social fabric.
“A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data” – StatNews, 3/17/2020
I tend to agree that the world at large is focusing on one, large immediate problem when it needs to be focusing on two large immediate problems. And that’s probably too much to expect.
We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully-connected (non-convolutional) deep network, whose input is a single continuous 5D coordinate (spatial location (x,y,z) and viewing direction (θ,ϕ)) and whose output is the volume density and view-dependent emitted radiance at that spatial location. We synthesize views by querying 5D coordinates along camera rays and use classic volume rendering techniques to project the output colors and densities into an image. Because volume rendering is naturally differentiable, the only input required to optimize our representation is a set of images with known camera poses. We describe how to effectively optimize neural radiance fields to render photorealistic novel views of scenes with complicated geometry and appearance, and demonstrate results that outperform prior work on neural rendering and view synthesis. View synthesis results are best viewed as videos, so we urge readers to view our supplementary video for convincing comparisons.
Let’s see if we can get InfluxDB working in Docker and start to generate and store data
I found a wonderful thing! It looks like you can change the default settings for where applications and their data are saved! Here’s a screenshot of where in the settings:
Going to verify that this is set for the admin accounts. It does!
I found the data sources for the dashboard in the previous few posts. Yes, everything still looks grim:
So rather than working on my dissertation, I thought I’d take a look at the data for the last 9(!) days in Excel:
This is for the USA. The data is sorted based on the cumulative total of new cases confirmed. If you look at the chart on the right, everything is in line with a pandemic in exponential growth. However, that’s not the whole story.
I like to color code the cells in my spreadsheets because colors help me visualize patterns in the data that I wouldn’t otherwise see. And one of the things that really stands out here is the red rows with one yellow cell on the left. These are all cases where the rate of confirmed new cases dropped to zero overnight. And they’re not near each other. They are in WA, NY, and CA. Is this a measuring problem or is something going right in these places?
Maybe we’ll find out more in the next few days. Now that I know how to get the data, I can do some of my own visualizations that look for outliers. I can also train up some sequence-to-sequence ML models to extrapolate trends.
One more thing. I had heard earlier (Twitter, I think?) that Vietnam was handling the crisis well. And it looks like it was, but things are back to being bad:
Ok, back to work
8:00 – 4:30 ASRC PhD, GOES
Working on the process section – done!
Working on the TACJ bookend – done! Made a new figure:
Submitted to Wayne. Here’s hoping it doesn’t fall through the cracks
Inattentional blindness is the psychological phenomenon that causes one to miss things in plain sight. It is a consequence of the selective attention in perception that lets us remain focused on important parts of our world without distraction from irrelevant details. Motivated by selective attention, we study the properties of artificial agents that perceive the world through the lens of a self-attention bottleneck. By constraining access to only a small fraction of the visual input, we show that their policies are directly interpretable in pixel space. We find neuroevolution ideal for training self-attention architectures for vision-based reinforcement learning tasks, allowing us to incorporate modules that can include discrete, non-differentiable operations which are useful for our agent. We argue that self-attention has similar properties as indirect encoding, in the sense that large implicit weight matrices are generated from a small number of key-query parameters, thus enabling our agent to solve challenging vision based tasks with at least 1000x fewer parameters than existing methods. Since our agent attends to only task-critical visual hints, they are able to generalize to environments where task irrelevant elements are modified while conventional methods fail.
AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open-source, cross platform, and supports hardware-in-loop with popular flight controllers such as PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. Similarly, we have an experimental release for a Unity plugin.
Added notes for the dissertation revisions
Working on the GVSETS paper – meeting at 3:00. Got everything into SVN and coordinated across machines.