Canon EF Lenses
the chart
Each prime lens on the chart is represented by a point given by the lens' focal length (mm) and maximum aperture. Zoom lenses are shown as curves whose end points correspond to the lens' maximum aperature at its lowest and highest focal lengths. The path of the curve does not reflect the relationship between focal length and maximum aperture - the curve is routed to minimize, where possible, the number of intersection with other curves. Prices are based on listings at adorama.com.
lens information
Don't be surprised if the information in the pages below isn't updated frequently. Lens technology is improved incrementally and new lens launches are infrequent.
- Canon offers a lot of information about their lenses. A lot of it is very readable, regardless of level and knowledge of the Canon line up. An EF Lens 101 covers the basics. Canon offers an individual summary for each of its EF lenses, which includes sample images and MTF. A complete EF lens spec sheet is also available (local copy).
- Canon publishes the modulation transfer function profiles (wtf is mtf?) for all EF lenses. This is a good thing. The MTF profiles are computed, however, not based on real performance. To compare two MTF functions try Andrew's Magnificent MTF Comparometer.
- An excellent EF Lens Beginner's FAQ is provided by NK Guy. This section of the FAQ is part of a larger EOS Beginner's FAQ. Even if you are a seasoned pro, I highly recommend this resource.
- Finally, if you want to know everything about EF lenses from the horse's mouth, pick up a copy of Canon EF Lens Works III. It's a Canon publication, thus shamelessly self-contratulatory and at times extremely poorly written and downright cheesy, but it does provide (a) description of every lens, (b) sample images for each lens, some breathtaking, (c) MTF functions, including with 1.4x and 2x extenders, (d) description of Canon technology and (e) pretty comprehensive optical glossary. At $20 is a very good buy.
lens reviews
- fredmiranda.com publishes user reviews of Canon, as well as other, lenses. Good reading if you want to know what a lot of people who use the lenses actually think.
- Reviews by William L Castleman of a large number of L lenses. The reviews are well written, and of a technical nature, making use of images of mannequins to illustrate lens characteristics and resolution plots.
- Bob Atkins reviews not only Canon but also some Tamron lenses.
- A large number of reviews at The Digital Picture. A lot of the reviews of similar lenses use the same text and are heavy on describing features more than performance.
Convolutional neural networks
Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. – Richard Feynman
Following up on our Neural network primer column, this month we explore a different kind of network architecture: a convolutional network.
The convolutional network replaces the hidden layer of a fully connected network (FCN) with one or more filters (a kind of neuron that looks at the input within a narrow window).
Even through convolutional networks have far fewer neurons that an FCN, they can perform substantially better for certain kinds of problems, such as sequence motif detection.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:.
Background reading
Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Neural network primer
Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon
In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.
Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.
We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.
Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.
Background reading
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.
Cell Genomics cover
Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.
Designed in collaboration with with Carlos Urzua.
Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).
Browse my gallery of cover designs.
Science Advances cover
My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.
More details about the design.
Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.
Browse my gallery of cover designs.
Regression modeling of time-to-event data with censoring
If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber
In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.
We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).
Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19:1513–1515.
Music video for Max Cooper's Ascent
My 5-dimensional animation sets the visual stage for Max Cooper's Ascent from the album Unspoken Words. I have previously collaborated with Max on telling a story about infinity for his Yearning for the Infinite album.
I provide a walkthrough the video, describe the animation system I created to generate the frames, and show you all the keyframes
The video recently premiered on YouTube.
Renders of the full scene are available as NFTs.