I’ve experimented with method design at various times and place notation is a very useful tool, but it’s lacking in some situations. Here’s a few ideas for some bolt-ons.

In which your hopeful protagonist describes Million Point Sculptures, and a highly interactive exploration tool written in Metal.

In the 1980s there was a wave of fascination with fractals and chaos in popular culture, and several books really caught the imagination of young me.

One was Chaos by James Gleick (un classique)¹. Also there were some lovely books by Clifford Pickover, like Computers and the Imagination, containing curious things like Million Point Sculptures: intriguing generated art showing wispy smoke-clouds. They’re generated by some quite simple equations.

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

In which your hopeful protagonist describes Million Point Sculptures, and a highly interactive exploration tool written in Metal.

In the 1980s there was a wave of fascination with fractals and chaos in popular culture, and several books really caught the imagination of young me.

One was Chaos by James Gleick (un classique)¹. Also there were some lovely books by Clifford Pickover, like Computers and the Imagination, containing curious things like Million Point Sculptures: intriguing generated art showing wispy smoke-clouds. They’re generated by some quite simple equations.

The orth concept in 2D geometry and graphics is where, given some vector, we find a vector (line) that is at right angles to the original. We have a tiny bit of choice about how to do it – we can pick a vector to the left, or to the right – but it’s very simple (more here).

The equivalent function in 3D is one of those odd little problems where you are given some freedom with the answer, and you don’t really care about that freedom – just pick something please! – but you’re made to care about it anyway and do what feels like too much thinking. Bah!¹

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

Sometimes I do some GLSL or similar: much graphics and geometry. I usually scribble down some back-of-envelope variant of the usual geometry equations, but I’ve never consistently decided what to call things or how to write them down.

Here I’m setting down the notation I’m going to use, and capturing the definitions. Reference pseudo-implementations are given too (Swift).

The equations and source given here have been unit tested; full source to come after tidying.

In which your hopeful protagonist describes Million Point Sculptures, and a highly interactive exploration tool written in Metal.

In the 1980s there was a wave of fascination with fractals and chaos in popular culture, and several books really caught the imagination of young me.

One was Chaos by James Gleick (un classique)¹. Also there were some lovely books by Clifford Pickover, like Computers and the Imagination, containing curious things like Million Point Sculptures: intriguing generated art showing wispy smoke-clouds. They’re generated by some quite simple equations.

The orth concept in 2D geometry and graphics is where, given some vector, we find a vector (line) that is at right angles to the original. We have a tiny bit of choice about how to do it – we can pick a vector to the left, or to the right – but it’s very simple (more here).

The equivalent function in 3D is one of those odd little problems where you are given some freedom with the answer, and you don’t really care about that freedom – just pick something please! – but you’re made to care about it anyway and do what feels like too much thinking. Bah!¹

A recent news story was about doctors not knowing the basics of Bayes’ theorem: they were asked a basic question about false results on a disease test. A lot of them flubbed it.

Let’s be fair: I wouldn’t expect most doctors to be able to regurgitate Bayes law or do an applied example.

I would expect them to say “That question is more complex than it sounds”, rather than fall into the usual trap.

It’s the old knowing what you don’t know (and that’s for another post).

Anyway, that was the prod for me do a dive into basics of Bayesian Analysis in several parts.

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

Sometimes I do some GLSL or similar: much graphics and geometry. I usually scribble down some back-of-envelope variant of the usual geometry equations, but I’ve never consistently decided what to call things or how to write them down.

Here I’m setting down the notation I’m going to use, and capturing the definitions. Reference pseudo-implementations are given too (Swift).

The equations and source given here have been unit tested; full source to come after tidying.

After seeing my post on ChatGPT dazzle, a friend asked what the code for that exact problem would look like if I rewrote it in a better way.

I did criticise the original code, so it’s fair that I should show my own version.

I’ve long known about the power of computer visualisation to dazzle and distract, to give cover to bad or poorly supported ideas. The case study I saw at university was about a famous computer animation of the single-bullet theory in the JFK assassination.

This general idea of dazzle pops up in different contexts over the years. Most recently we can see ChatGPT and other AI tools being used in some very low-effort dazzle attempts.

Here’s a recent example in a post from Twitter:

Introducing the simplex generator for higher dimension pascal/combinatorics and looking at the bigger picture: exhaustive function composition.

This is the first of a few notes about combinatorics and probability. Simpler concepts first, and eventually might get to stuff like analytic combinatorics.

I’m interested in the point where more simple combinatorics and multinomials become blunt tools and we have to move to higher concepts like generators and species.

In which your hopeful protagonist describes Million Point Sculptures, and a highly interactive exploration tool written in Metal.

In the 1980s there was a wave of fascination with fractals and chaos in popular culture, and several books really caught the imagination of young me.

One was Chaos by James Gleick (un classique)¹. Also there were some lovely books by Clifford Pickover, like Computers and the Imagination, containing curious things like Million Point Sculptures: intriguing generated art showing wispy smoke-clouds. They’re generated by some quite simple equations.

This helper is installable with SPM, see GitHub repo

I’ve been using the Swift Testing framework more. Despite my previous grumble I do like the arguments: feature of the @Test macro and how much it can clean up tests:

@Test(arguments: [
	(true, "bob", 38),
	(false, "sue", 45)
])
func testUserPermissions(isBasketEmpty: Bool, username: String, age: Int) {
    #expect( ... )
}

The ability to supply a list of parameter variants to test is very useful. I think it tends to result in more exhaustive tests because of ease of use.

But being able to easily whack in a list of argument variants soon reveals a slight annoyance. It’s not unusual to end up with a test like this:

I took the new Swift Testing framework out for a spin and used it seriously on a small project.

Conclusion: to me, Swift Testing isn’t ready for serious production use, because either it’s buggy in some important ways, or Apple’s documentation is not specific enough about Testing’s design philosophy and how you should (or should not) use certain features.

My time ratio for “writing tests” to “work out why Testing is crashing” is 1:2 (or worse) at this point.

Testing tools should be well understood and well presented; we trust them with a lot. I think if issues are found with a new framework like Testing, this should be mentioned in the framework documentation.¹

This helper is installable with SPM, see GitHub repo

I’ve been using the Swift Testing framework more. Despite my previous grumble I do like the arguments: feature of the @Test macro and how much it can clean up tests:

@Test(arguments: [
	(true, "bob", 38),
	(false, "sue", 45)
])
func testUserPermissions(isBasketEmpty: Bool, username: String, age: Int) {
    #expect( ... )
}

The ability to supply a list of parameter variants to test is very useful. I think it tends to result in more exhaustive tests because of ease of use.

But being able to easily whack in a list of argument variants soon reveals a slight annoyance. It’s not unusual to end up with a test like this:

The orth concept in 2D geometry and graphics is where, given some vector, we find a vector (line) that is at right angles to the original. We have a tiny bit of choice about how to do it – we can pick a vector to the left, or to the right – but it’s very simple (more here).

The equivalent function in 3D is one of those odd little problems where you are given some freedom with the answer, and you don’t really care about that freedom – just pick something please! – but you’re made to care about it anyway and do what feels like too much thinking. Bah!¹

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

Sometimes I do some GLSL or similar: much graphics and geometry. I usually scribble down some back-of-envelope variant of the usual geometry equations, but I’ve never consistently decided what to call things or how to write them down.

Here I’m setting down the notation I’m going to use, and capturing the definitions. Reference pseudo-implementations are given too (Swift).

The equations and source given here have been unit tested; full source to come after tidying.

I took the new Swift Testing framework out for a spin and used it seriously on a small project.

Conclusion: to me, Swift Testing isn’t ready for serious production use, because either it’s buggy in some important ways, or Apple’s documentation is not specific enough about Testing’s design philosophy and how you should (or should not) use certain features.

My time ratio for “writing tests” to “work out why Testing is crashing” is 1:2 (or worse) at this point.

Testing tools should be well understood and well presented; we trust them with a lot. I think if issues are found with a new framework like Testing, this should be mentioned in the framework documentation.¹

In recent years there seems to have been a shift in interviews: less pairing exercises and more home coding tasks / projects.

After recent experience of home coding projects pre-interview, I’ve set a policy for my engagement in these tasks. I’m detailing it below, partly to avoid repeating myself to recruiters. Further down I give some reasons and discussion.

Currying. It’s one of the stalwarts of functional programming.

Is Currying something you need to know about to be a developer?

Nope.

Is it handy to know about?

Yes. Think of it as a pattern for your toolbox. It can allow some elegant solutions and less code.

Is it weird and esoteric?

No; there’s a certain ‘shape’ to currying code but once you recognise it, there’s no mystery.

Here’s something a lot of devs would like to hear:

I’d say that anyone at senior level (and definitely above¹) should have some justified² thoughts on the greenfield question:

This helper is installable with SPM, see GitHub repo

I’ve been using the Swift Testing framework more. Despite my previous grumble I do like the arguments: feature of the @Test macro and how much it can clean up tests:

@Test(arguments: [
	(true, "bob", 38),
	(false, "sue", 45)
])
func testUserPermissions(isBasketEmpty: Bool, username: String, age: Int) {
    #expect( ... )
}

The ability to supply a list of parameter variants to test is very useful. I think it tends to result in more exhaustive tests because of ease of use.

But being able to easily whack in a list of argument variants soon reveals a slight annoyance. It’s not unusual to end up with a test like this:

This helper is installable with SPM, see GitHub repo

I’ve been using the Swift Testing framework more. Despite my previous grumble I do like the arguments: feature of the @Test macro and how much it can clean up tests:

@Test(arguments: [
	(true, "bob", 38),
	(false, "sue", 45)
])
func testUserPermissions(isBasketEmpty: Bool, username: String, age: Int) {
    #expect( ... )
}

The ability to supply a list of parameter variants to test is very useful. I think it tends to result in more exhaustive tests because of ease of use.

But being able to easily whack in a list of argument variants soon reveals a slight annoyance. It’s not unusual to end up with a test like this:

I took the new Swift Testing framework out for a spin and used it seriously on a small project.

Conclusion: to me, Swift Testing isn’t ready for serious production use, because either it’s buggy in some important ways, or Apple’s documentation is not specific enough about Testing’s design philosophy and how you should (or should not) use certain features.

My time ratio for “writing tests” to “work out why Testing is crashing” is 1:2 (or worse) at this point.

Testing tools should be well understood and well presented; we trust them with a lot. I think if issues are found with a new framework like Testing, this should be mentioned in the framework documentation.¹

Currying. It’s one of the stalwarts of functional programming.

Is Currying something you need to know about to be a developer?

Nope.

Is it handy to know about?

Yes. Think of it as a pattern for your toolbox. It can allow some elegant solutions and less code.

Is it weird and esoteric?

No; there’s a certain ‘shape’ to currying code but once you recognise it, there’s no mystery.

This helper is installable with SPM, see GitHub repo

I’ve been using the Swift Testing framework more. Despite my previous grumble I do like the arguments: feature of the @Test macro and how much it can clean up tests:

@Test(arguments: [
	(true, "bob", 38),
	(false, "sue", 45)
])
func testUserPermissions(isBasketEmpty: Bool, username: String, age: Int) {
    #expect( ... )
}

The ability to supply a list of parameter variants to test is very useful. I think it tends to result in more exhaustive tests because of ease of use.

But being able to easily whack in a list of argument variants soon reveals a slight annoyance. It’s not unusual to end up with a test like this:

I took the new Swift Testing framework out for a spin and used it seriously on a small project.

Conclusion: to me, Swift Testing isn’t ready for serious production use, because either it’s buggy in some important ways, or Apple’s documentation is not specific enough about Testing’s design philosophy and how you should (or should not) use certain features.

My time ratio for “writing tests” to “work out why Testing is crashing” is 1:2 (or worse) at this point.

Testing tools should be well understood and well presented; we trust them with a lot. I think if issues are found with a new framework like Testing, this should be mentioned in the framework documentation.¹

The orth concept in 2D geometry and graphics is where, given some vector, we find a vector (line) that is at right angles to the original. We have a tiny bit of choice about how to do it – we can pick a vector to the left, or to the right – but it’s very simple (more here).

The equivalent function in 3D is one of those odd little problems where you are given some freedom with the answer, and you don’t really care about that freedom – just pick something please! – but you’re made to care about it anyway and do what feels like too much thinking. Bah!¹

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

Sometimes I do some GLSL or similar: much graphics and geometry. I usually scribble down some back-of-envelope variant of the usual geometry equations, but I’ve never consistently decided what to call things or how to write them down.

Here I’m setting down the notation I’m going to use, and capturing the definitions. Reference pseudo-implementations are given too (Swift).

The equations and source given here have been unit tested; full source to come after tidying.

After seeing my post on ChatGPT dazzle, a friend asked what the code for that exact problem would look like if I rewrote it in a better way.

I did criticise the original code, so it’s fair that I should show my own version.

I’ve long known about the power of computer visualisation to dazzle and distract, to give cover to bad or poorly supported ideas. The case study I saw at university was about a famous computer animation of the single-bullet theory in the JFK assassination.

This general idea of dazzle pops up in different contexts over the years. Most recently we can see ChatGPT and other AI tools being used in some very low-effort dazzle attempts.

Here’s a recent example in a post from Twitter:

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I introduced ohmaps in parts 1 and 2 and looked at some simpler examples.

We looked at parallel and series resistor networks (and combinations of those):

And I wrote this:

And not every resistor network can be shown as an ohmap – things outwith simple series/parallel nestings, like delta or Y networks.

It turns out I was a little hasty here. So how might ohmaps cope with more interesting networks?

More on Ohmaps: component failure battles, limitations, ambiguity…

Disclaimer: I am not an electrician. Nothing here is electrical advice/expertise. Insure your garments.

Occasionally there’s a lovely moment when I’m working on a problem and I realise I’m also looking at some other thing that seems completely unrelated. It’s like a metaphor made flesh.

These ‘ isomorphism moments’ can be powerful because the two seemingly unrelated things can give you insights into each other. Their commonality encourages you think about the essential thread running through them both.

This post details one of these moments I had recently.

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I introduced ohmaps in parts 1 and 2 and looked at some simpler examples.

We looked at parallel and series resistor networks (and combinations of those):

And I wrote this:

And not every resistor network can be shown as an ohmap – things outwith simple series/parallel nestings, like delta or Y networks.

It turns out I was a little hasty here. So how might ohmaps cope with more interesting networks?

Here’s a few details about the weird clocks in the previous post The Lost Clock Emporium.

The clocks are all regular analogue clocks (rotation aside), with the exception of Hades’ Timepiece, which has numbers and hands going counter-clockwise (so a mirror image of a normal clock).

The entire clocks are rotating clockwise at these rates (per day):

I can’t remember exactly how I ended up at the Lost Clock Emporium. I do remember brushing by disturbed looking people making their way out.

“Clock a load of you!”, the proprietor muttered, before looking up. “Sorry, no time for introductions, I have things to show you.”

More on Ohmaps: component failure battles, limitations, ambiguity…

Disclaimer: I am not an electrician. Nothing here is electrical advice/expertise. Insure your garments.

Occasionally there’s a lovely moment when I’m working on a problem and I realise I’m also looking at some other thing that seems completely unrelated. It’s like a metaphor made flesh.

These ‘ isomorphism moments’ can be powerful because the two seemingly unrelated things can give you insights into each other. Their commonality encourages you think about the essential thread running through them both.

This post details one of these moments I had recently.

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I introduced ohmaps in parts 1 and 2 and looked at some simpler examples.

We looked at parallel and series resistor networks (and combinations of those):

And I wrote this:

And not every resistor network can be shown as an ohmap – things outwith simple series/parallel nestings, like delta or Y networks.

It turns out I was a little hasty here. So how might ohmaps cope with more interesting networks?

I used JLCPCB to fabricate my cap-fun circuit (see part 1). It was under $20 including delivery, for 75 copies of this small PCB (4 x 4 cm).

I’ve been meaning to look into PCB fabrication forever, and it’s time, baby.

What would I make for my first small PCB? I settled on designing an educational demo board for capacitors. I call it cap-fun.

Capacitor demo boards are nothing new, but I’ve remixed things a little because the usual designs hide some nuances of capacitors that I think can be easily demonstrated.

More on Ohmaps: component failure battles, limitations, ambiguity…

Disclaimer: I am not an electrician. Nothing here is electrical advice/expertise. Insure your garments.

Occasionally there’s a lovely moment when I’m working on a problem and I realise I’m also looking at some other thing that seems completely unrelated. It’s like a metaphor made flesh.

These ‘ isomorphism moments’ can be powerful because the two seemingly unrelated things can give you insights into each other. Their commonality encourages you think about the essential thread running through them both.

This post details one of these moments I had recently.

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I want to mention the concept of walkabout and then go for a meander with the ohmaps idea. The idea is to eventually look at if the ohmap extends from resistance (DC behaviour circuits) to impedence (AC circuits) in any useful way.

Let’s go walkabout

For quite a lot of years I would go walkabout and not really thinking about what that meant.

Walkabout is my expression for when I’m thinking about one thing and then I go off in some other interesting direction or I try to generalise something. The original ohmap idea is a good example: I was just sketching some trivial code for building image montages, and I later spotted the simple mapping to resistor networks.

I introduced ohmaps in parts 1 and 2 and looked at some simpler examples.

We looked at parallel and series resistor networks (and combinations of those):

And I wrote this:

And not every resistor network can be shown as an ohmap – things outwith simple series/parallel nestings, like delta or Y networks.

It turns out I was a little hasty here. So how might ohmaps cope with more interesting networks?

More on Ohmaps: component failure battles, limitations, ambiguity…

Disclaimer: I am not an electrician. Nothing here is electrical advice/expertise. Insure your garments.

Occasionally there’s a lovely moment when I’m working on a problem and I realise I’m also looking at some other thing that seems completely unrelated. It’s like a metaphor made flesh.

These ‘ isomorphism moments’ can be powerful because the two seemingly unrelated things can give you insights into each other. Their commonality encourages you think about the essential thread running through them both.

This post details one of these moments I had recently.

I used JLCPCB to fabricate my cap-fun circuit (see part 1). It was under $20 including delivery, for 75 copies of this small PCB (4 x 4 cm).

I’ve been meaning to look into PCB fabrication forever, and it’s time, baby.

What would I make for my first small PCB? I settled on designing an educational demo board for capacitors. I call it cap-fun.

Capacitor demo boards are nothing new, but I’ve remixed things a little because the usual designs hide some nuances of capacitors that I think can be easily demonstrated.

I used JLCPCB to fabricate my cap-fun circuit (see part 1). It was under $20 including delivery, for 75 copies of this small PCB (4 x 4 cm).

I’ve been meaning to look into PCB fabrication forever, and it’s time, baby.

What would I make for my first small PCB? I settled on designing an educational demo board for capacitors. I call it cap-fun.

Capacitor demo boards are nothing new, but I’ve remixed things a little because the usual designs hide some nuances of capacitors that I think can be easily demonstrated.

I used JLCPCB to fabricate my cap-fun circuit (see part 1). It was under $20 including delivery, for 75 copies of this small PCB (4 x 4 cm).

I’ve been meaning to look into PCB fabrication forever, and it’s time, baby.

What would I make for my first small PCB? I settled on designing an educational demo board for capacitors. I call it cap-fun.

Capacitor demo boards are nothing new, but I’ve remixed things a little because the usual designs hide some nuances of capacitors that I think can be easily demonstrated.

Below I list my amateur radio hardware, it doesn’t represent a single rig!

A recent news story was about doctors not knowing the basics of Bayes’ theorem: they were asked a basic question about false results on a disease test. A lot of them flubbed it.

Let’s be fair: I wouldn’t expect most doctors to be able to regurgitate Bayes law or do an applied example.

I would expect them to say “That question is more complex than it sounds”, rather than fall into the usual trap.

It’s the old knowing what you don’t know (and that’s for another post).

Anyway, that was the prod for me do a dive into basics of Bayesian Analysis in several parts.

A recent news story was about doctors not knowing the basics of Bayes’ theorem: they were asked a basic question about false results on a disease test. A lot of them flubbed it.

Let’s be fair: I wouldn’t expect most doctors to be able to regurgitate Bayes law or do an applied example.

I would expect them to say “That question is more complex than it sounds”, rather than fall into the usual trap.

It’s the old knowing what you don’t know (and that’s for another post).

Anyway, that was the prod for me do a dive into basics of Bayesian Analysis in several parts.

A recent news story was about doctors not knowing the basics of Bayes’ theorem: they were asked a basic question about false results on a disease test. A lot of them flubbed it.

Let’s be fair: I wouldn’t expect most doctors to be able to regurgitate Bayes law or do an applied example.

I would expect them to say “That question is more complex than it sounds”, rather than fall into the usual trap.

It’s the old knowing what you don’t know (and that’s for another post).

Anyway, that was the prod for me do a dive into basics of Bayesian Analysis in several parts.

Introducing the simplex generator for higher dimension pascal/combinatorics and looking at the bigger picture: exhaustive function composition.

This is the first of a few notes about combinatorics and probability. Simpler concepts first, and eventually might get to stuff like analytic combinatorics.

I’m interested in the point where more simple combinatorics and multinomials become blunt tools and we have to move to higher concepts like generators and species.

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

I’ve exhibited at Colony of Artists several times, a vibrant art festival at Abbeyhill Colonies in Edinburgh.

One of the things I was showing and selling was my tesselation pieces: designs inspired by MC Escher’s work, particularly matamorphosing tesselations.

Some of these pieces play with negative space and the transition from 3D to 2D:

These are notes from a workshop I gave on Snare technique for Beltane 2021 (Acropolyptic).

The target audience is someone learning basic technique from the ground up, particularly in the context of processional drumming (playing a single drum). But the skills can equally apply to kit drumming etc.

Developing snare technique is hard. It can take ten hours or more practice time to start solidifying things, due to the fine motor control and muscle memory training involved.

These are notes from a workshop I gave on Snare technique for Beltane 2021 (Acropolyptic).

The target audience is someone learning basic technique from the ground up, particularly in the context of processional drumming (playing a single drum). But the skills can equally apply to kit drumming etc.

Developing snare technique is hard. It can take ten hours or more practice time to start solidifying things, due to the fine motor control and muscle memory training involved.

These are notes from a workshop I gave on Snare technique for Beltane 2021 (Acropolyptic).

The target audience is someone learning basic technique from the ground up, particularly in the context of processional drumming (playing a single drum). But the skills can equally apply to kit drumming etc.

Developing snare technique is hard. It can take ten hours or more practice time to start solidifying things, due to the fine motor control and muscle memory training involved.

I’ve been doing 3D printing for over five years. Designing and printing things for practical use gives you an appreciation for everyday objects and what makes them useful (or not)¹.

Thinking of getting into 3D printing? Here’s some considerations:

I’ve been doing 3D printing for over five years. Designing and printing things for practical use gives you an appreciation for everyday objects and what makes them useful (or not)¹.

Thinking of getting into 3D printing? Here’s some considerations:

If you have various nests of cables around the place you’re not unusual (USB anyone?). Organising your cable types, and keeping them organised, feels like a classic Sisyphean task.

One way to make things easier is to make your most important cables easier to recognise. Here’s a handy system I use.

If you have various nests of cables around the place you’re not unusual (USB anyone?). Organising your cable types, and keeping them organised, feels like a classic Sisyphean task.

One way to make things easier is to make your most important cables easier to recognise. Here’s a handy system I use.

If you have various nests of cables around the place you’re not unusual (USB anyone?). Organising your cable types, and keeping them organised, feels like a classic Sisyphean task.

One way to make things easier is to make your most important cables easier to recognise. Here’s a handy system I use.

In recent years there seems to have been a shift in interviews: less pairing exercises and more home coding tasks / projects.

After recent experience of home coding projects pre-interview, I’ve set a policy for my engagement in these tasks. I’m detailing it below, partly to avoid repeating myself to recruiters. Further down I give some reasons and discussion.

Currying. It’s one of the stalwarts of functional programming.

Is Currying something you need to know about to be a developer?

Nope.

Is it handy to know about?

Yes. Think of it as a pattern for your toolbox. It can allow some elegant solutions and less code.

Is it weird and esoteric?

No; there’s a certain ‘shape’ to currying code but once you recognise it, there’s no mystery.

This simple guide to jdupes is split into traffic light sections 🚦 based on the danger of the commands.

If you want some file de-duplication test data, there’s a simple repo at https://github.com/alexhunsley/file-duplication-test-data.

This simple guide to jdupes is split into traffic light sections 🚦 based on the danger of the commands.

If you want some file de-duplication test data, there’s a simple repo at https://github.com/alexhunsley/file-duplication-test-data.

This simple guide to jdupes is split into traffic light sections 🚦 based on the danger of the commands.

If you want some file de-duplication test data, there’s a simple repo at https://github.com/alexhunsley/file-duplication-test-data.

I’ve long known about the power of computer visualisation to dazzle and distract, to give cover to bad or poorly supported ideas. The case study I saw at university was about a famous computer animation of the single-bullet theory in the JFK assassination.

This general idea of dazzle pops up in different contexts over the years. Most recently we can see ChatGPT and other AI tools being used in some very low-effort dazzle attempts.

Here’s a recent example in a post from Twitter:

I’ve long known about the power of computer visualisation to dazzle and distract, to give cover to bad or poorly supported ideas. The case study I saw at university was about a famous computer animation of the single-bullet theory in the JFK assassination.

This general idea of dazzle pops up in different contexts over the years. Most recently we can see ChatGPT and other AI tools being used in some very low-effort dazzle attempts.

Here’s a recent example in a post from Twitter:

Meta-content time!

As the site develops, this post will be updated.

I’m a big fan of Flour Water Salt Yeast, Ken Forkish’s epic book on fancy bread¹.

Hence I’m writing a recipe app for fancy artisanal bread and pizza. For these loaves the ingredient calculations go a bit beyond bog standard bread².

I’m a big fan of Flour Water Salt Yeast, Ken Forkish’s epic book on fancy bread¹.

Hence I’m writing a recipe app for fancy artisanal bread and pizza. For these loaves the ingredient calculations go a bit beyond bog standard bread².

I’m a big fan of Flour Water Salt Yeast, Ken Forkish’s epic book on fancy bread¹.

Hence I’m writing a recipe app for fancy artisanal bread and pizza. For these loaves the ingredient calculations go a bit beyond bog standard bread².

I’m a big fan of Flour Water Salt Yeast, Ken Forkish’s epic book on fancy bread¹.

Hence I’m writing a recipe app for fancy artisanal bread and pizza. For these loaves the ingredient calculations go a bit beyond bog standard bread².

I’m a big fan of Flour Water Salt Yeast, Ken Forkish’s epic book on fancy bread¹.

Hence I’m writing a recipe app for fancy artisanal bread and pizza. For these loaves the ingredient calculations go a bit beyond bog standard bread².

Here’s a few details about the weird clocks in the previous post The Lost Clock Emporium.

The clocks are all regular analogue clocks (rotation aside), with the exception of Hades’ Timepiece, which has numbers and hands going counter-clockwise (so a mirror image of a normal clock).

The entire clocks are rotating clockwise at these rates (per day):

I can’t remember exactly how I ended up at the Lost Clock Emporium. I do remember brushing by disturbed looking people making their way out.

“Clock a load of you!”, the proprietor muttered, before looking up. “Sorry, no time for introductions, I have things to show you.”

If you’re working with image processing and discrete Fourier transforms (frequency analysis/filtering)¹ you need test images, and possibly even videos.

Xor Xor Gabor² is my name for an easy to make test image (and video) that is a nutritious source of frequencies:

If you’re working with image processing and discrete Fourier transforms (frequency analysis/filtering)¹ you need test images, and possibly even videos.

Xor Xor Gabor² is my name for an easy to make test image (and video) that is a nutritious source of frequencies:

If you’re working with image processing and discrete Fourier transforms (frequency analysis/filtering)¹ you need test images, and possibly even videos.

Xor Xor Gabor² is my name for an easy to make test image (and video) that is a nutritious source of frequencies:

Introducing the simplex generator for higher dimension pascal/combinatorics and looking at the bigger picture: exhaustive function composition.

This is the first of a few notes about combinatorics and probability. Simpler concepts first, and eventually might get to stuff like analytic combinatorics.

I’m interested in the point where more simple combinatorics and multinomials become blunt tools and we have to move to higher concepts like generators and species.