Hi,
I still fail to see the interactive story behind Leo usage, particularly
in the math learning context, and interactivity in its most general
sense is important for learning. See for example the seam carving
algorithm by Grant Sanderson, from the excellent 3Blue1Brown at [1],
that is explained interactively with Pluto.jl/Julia and reimplemented in
marimo/Python. The educative advantages from the explaining and learning
sides are pretty difficult to imagine by seeing just the source code or
executing it in batch mode, without interactivity.
[1] https://huggingface.co/spaces/marimo-team/seam-carving
As said, LeoVue and maybe the variant of Leo for VS Code/Codium can
convey this sense of interactivity, thanks to the integration with web
technologies. Maybe with Hypermedia and things like FastHTML, much of
that can be done within Leo. But I think that this more
interactive/visual storytelling is needed to make Leo a good math
platform for wider audiences.
Cheers,
Offray
On 17/12/24 10:14, Edward K. Ream wrote:
On Saturday, December 14, 2024 at 4:46:59 AM UTC-6 Edward K. Ream wrote:
On second thought, the title of this thread is misguided.
I have spent the last week coming up to speed on all the fabulous math
tools and websites out there.
This morning I finally got around to writing my first matplotlib
program. See the Postscript.
This exercise has been a ton of fun. execute-script just works!
For me, Leo /is /the perfect platform for running Matplotlib programs.
The more I use Jupyter, the less I like it, so the title of this
thread seems about right :-)
Edward
P.S. Here is my first plot:
import matplotlib.pyplot as plt
import numpy as np
# Use a monospace font for
plt.rcParams["font.family"] = 'DejaVu Sans Mono'
a, b = [], []
for x in range(-50,50):
y=x**2
a.append(x)
b.append(y)
fig= plt.figure()
fig.suptitle('Parabola with Tangents')
axes=fig.add_subplot()
axes.plot(a,b)
# Cut the tangent lines off at y = 0
plt.ylim(bottom=0)
color = iter(plt.cm.rainbow(np.linspace(0, 1, 6)))
for i, x in enumerate(range(-50, 60, 20)):
if x == 0:
continue
y = x**2
slope = 2 * x
x_y_s = f"({x:3}, {y})"
label = f"{x_y_s:<11} slope: {slope:4}, x-intercept: {x - y/slope:>5}"
plt.axline((x, y), slope=slope, label=label, c=next(color))
axes.legend()
fig.canvas.manager.window.move(50,50) # Move the window.
plt.show()
EKR
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