Fixing 'make_rotated_aperture' Issues In Hcipy (All Zeros)

Hey there, hcipy enthusiasts and optics wizards! If you've ever delved into the fantastic world of optical simulations with the hcipy library, you know how powerful it can be for everything from wavefront propagation to designing complex apertures. But what happens when a seemingly straightforward function, like hcipy.aperture.make_rotated_aperture, throws a curveball and leaves you with a blank, all-zero image instead of your beautifully rotated pupil? You're definitely not alone, and it's a frustrating head-scratcher that many of us have encountered. Let's unpack this particular bug that's been giving some folks grief, even after it was supposedly fixed. We'll dive deep into why you might still be seeing this problem, how to resolve it, and what to do if the fix isn't as straightforward as you'd hope. Our goal here is to get your rotated apertures rendering perfectly, so you can get back to the exciting stuff without this pesky issue holding you back. This article is your go-to guide for understanding, troubleshooting, and ultimately conquering the make_rotated_aperture bug, ensuring your hcipy simulations run smoothly and accurately every single time. We'll explore the specific code examples that demonstrate this peculiar behavior, discuss the underlying reasons for its persistence, and provide clear, actionable steps to get your optical simulations back on track. So, buckle up, grab your favorite beverage, and let's get those apertures spinning just right!

Understanding the hcipy.aperture.make_rotated_aperture Challenge

Alright, guys, let's kick things off by really understanding what hcipy.aperture.make_rotated_aperture is all about and why it's such a crucial tool in your hcipy arsenal. hcipy is an incredibly versatile and powerful Python library designed specifically for high-contrast imaging and general optical simulations. It allows researchers and engineers to model complex optical systems, propagate light fields, and analyze instrument performance with remarkable detail. Within this library, the aperture module is absolutely vital for defining the physical shape of your optical elements, like telescope pupils, masks, or even complex diffractive elements. When you're working with optics, being able to rotate these apertures is often a fundamental requirement. Imagine you're simulating a telescope that needs to observe different parts of the sky, or perhaps you're designing an instrument where a specific optical component needs to be precisely oriented. That's where make_rotated_aperture comes into play. It's supposed to take an existing aperture definition and generate a new one that's rotated by a specified angle, making it super convenient for a wide range of simulations without having to manually redefine every single point. For instance, simulating the rotation of a segmented mirror, or even just checking the effect of misalignment in a system, often requires this functionality. The ability to dynamically rotate apertures greatly enhances the flexibility and realism of your optical models.

Now, here's where the plot thickens. Some folks, including our current user, have reported a peculiar issue where make_rotated_aperture simply doesn't work as expected. Instead of a beautiful, rotated image of their pupil, they end up with a blank, all-black field – essentially, an array full of zeros. This is definitely not the desired outcome! The frustrating part is that this particular issue has actually been identified and a fix was supposedly implemented in a GitHub pull request, specifically PR #265, with a comment from the core developer @ehpor stating, "This is indeed a bug. Fixed in PR #265. Thanks for reporting." This comment, dating back to 2023, suggests that the problem should be resolved. So, why are users like you still encountering it? That's the million-dollar question we're going to tackle. The user explicitly stated they are running hcipy version 0.7.0 and provided code snippets demonstrating the persistent problem. This immediately points us towards a potential versioning issue, which is a common pitfall in software development. If the fix was merged after version 0.7.0 was released, then anyone running that specific version (or earlier ones) wouldn't have the benefit of that bug correction. It's like having a patch for a video game that you haven't downloaded yet – the problem still exists on your console! Understanding this crucial detail is the first step toward getting to the bottom of this make_rotated_aperture conundrum and getting your hcipy environment running like a well-oiled machine. Without a properly functioning rotation capability, many complex simulations become either impossible or incredibly tedious to set up manually, severely limiting the utility of hcipy for dynamic or orientation-sensitive optical designs. The core issue of a function returning all zeros indicates a failure in its internal logic to correctly map the rotated aperture onto the computational grid, a fundamental flaw that needs addressing for accurate simulation results. Therefore, unraveling this mystery is paramount for anyone relying on hcipy for professional or academic optical work.

Diving Deep into the make_rotated_aperture Bug: What's Going On?

Alright, let's really dig into the specifics of this make_rotated_aperture bug, because understanding the exact symptoms is half the battle when it comes to troubleshooting. The user clearly outlined the problem: while the unrotated pupil renders perfectly fine, the rotated one inexplicably returns all zeros. This behavior is consistent across their own code and a previous user's example, strongly suggesting a core issue rather than a simple user error. Let's break down the provided code snippets to see exactly what's happening under the hood.

The Original Problem Statement and its Context

Our user is working with hcipy version 0.7.0, which, as we'll discuss, is a crucial piece of information. They're trying to simulate a Keck-like aperture and then rotate it. Here’s a closer look at their approach:

import matplotlib.pyplot as plt 
import hcipy
import numpy as np

if __name__ == "__main__":
    angle = 30
    angle_rad = angle*np.pi/180

    pupil_grid = hcipy.make_pupil_grid(256, 12) 
    aperture = hcipy.aperture.make_keck_aperture(normalized=False)
    rot_aperture = hcipy.aperture.make_rotated_aperture(aperture, angle_rad)

    #unrotated
    telescope_pupil = hcipy.evaluate_supersampled(aperture, pupil_grid, 8)
    #rotated
    rot_telescope_pupil = hcipy.evaluate_supersampled(rot_aperture, pupil_grid, 8)

    #first iteration works, second fails
    for pup in [telescope_pupil, rot_telescope_pupil]:
        im = hcipy.imshow_field(pup, cmap='gray')
        plt.colorbar()
        plt.xlabel('x / D')
        plt.ylabel('y / D')
        plt.show()

Let's dissect this, folks. First, they define a pupil_grid using hcipy.make_pupil_grid(256, 12), which sets up a 256x256 grid spanning 12 units. This is a standard way to define the computational domain for optical fields. Then, they create an aperture using hcipy.aperture.make_keck_aperture(normalized=False). The normalized=False part is important here, indicating that the aperture will retain its physical dimensions rather than being scaled to a unit diameter. So far, so good. The critical line for our discussion is rot_aperture = hcipy.aperture.make_rotated_aperture(aperture, angle_rad). This is where the magic (or lack thereof, in this case!) is supposed to happen. It takes the original aperture and attempts to create a new rot_aperture rotated by 30 degrees. Finally, both the original and the rotated apertures are evaluated onto the pupil_grid using hcipy.evaluate_supersampled, which is a smart way to get a high-quality representation of the aperture on the grid, reducing aliasing effects by supersampling and then averaging. The user then iterates through both telescope_pupil (the unrotated one) and rot_telescope_pupil (the rotated one) to display them using hcipy.imshow_field. The key observation here is that the first iteration (displaying telescope_pupil) works perfectly, showing a clear image of the Keck aperture. However, the second iteration (displaying rot_telescope_pupil) results in a completely blank image, a field of nothing but zeros. This behavior is consistent and reproducible with the provided code, which is a classic sign of a bug rather than an environmental fluke. The fact that the unrotated version works confirms that the pupil_grid and the initial aperture definition are sound. The problem specifically lies within the make_rotated_aperture function's ability to correctly generate the transformed field.

Examining the Previous User's Code and its Similarities

To really drive home that this isn't an isolated incident, let's look at the code provided by the previous user in the GitHub issue referenced in the problem description. This code also demonstrates the same frustrating behavior:

import matplotlib.pyplot as plt 
import hcipy
import numpy as np

aperture = hcipy.aperture.make_luvoir_a_aperture(normalized=True)
grid = hcipy.make_pupil_grid(1000,1)
angle = 45

plt.figure()
hcipy.imshow_field(aperture(grid), cmap = "gray") ## no error
plt.show()

#still doesn't work
rot_aperture = hcipy.aperture.make_rotated_aperture(aperture, angle*np.pi/180)

plt.figure()
hcipy.imshow_field(rot_aperture(grid), cmap = "gray") ## causes error
plt.show()

This snippet, while using a different aperture (make_luvoir_a_aperture) and a different grid size (make_pupil_grid(1000,1)), exhibits the exact same pattern. The original, unrotated aperture (aperture(grid)) displays without any issues, as confirmed by the ## no error comment. But when make_rotated_aperture is used to create rot_aperture, and that rotated aperture is then evaluated and displayed (rot_aperture(grid)), the result is again a blank field, indicated by ## causes error. The key difference here is that the previous user directly called aperture(grid) to evaluate the aperture, whereas our current user employed hcipy.evaluate_supersampled. However, the outcome remains identical: rotation breaks the aperture evaluation. This widespread confirmation, across different hcipy versions (implied for the previous user, explicitly 0.7.0 for the current user) and different aperture types, points to a fundamental flaw in the make_rotated_aperture implementation within specific hcipy releases. The normalized=True argument in the previous example also shows that the issue isn't tied to the normalization state of the aperture. The consistency of this bug across various setups makes it clear that the problem is deeply rooted in the library's code for handling aperture rotations, specifically affecting how the transformed aperture is evaluated onto the computational grid. It's not a subtle visual glitch; it's a complete failure to produce any data, which can seriously derail any optical simulation relying on rotated elements.

Why You Might Still See the make_rotated_aperture Bug (Even After a Fix!)

Okay, so we've established that the make_rotated_aperture bug is real and it's frustrating, especially when you know a fix was committed! The biggest head-scratcher here is why users are still encountering this issue even after @ehpor's clear statement about a fix in PR #265. The most probable and common reason for this kind of persistence in software development is a version mismatch. Let's dive into why this happens and how to make sure you're running the patched version.

hcipy Version Mismatch: The Likely Culprit

Think about it like this, guys: software development is a continuous process. Bugs are found, reported, and then fixed. These fixes are typically implemented in the source code (often on platforms like GitHub), and then eventually, they make their way into new releases or versions of the software. When a developer says a bug is