Cplot ucsd5/24/2023 ![]() This software is published under the GPL-3.0 license. David Lowry-Duda, Visualizing modular forms, 2020.Ricky Reusser, Locally Scaled Domain Coloring, Part 1: Contour.Ricky Reusser, Domain Coloring with Adaptive.3Blue1Brown, Winding numbers and domain coloring, 2018.empet, Visualizing complex-valued functions with Matplotlib and Mayavi, Domain coloring method, 2014.Elias Wegert and Gunter Semmler, Phase Plots of Complex Functions:.Konstantin Poelke and Konrad Polthier, Lifted Domain Coloring,.Douglas Arnold and Jonathan Rogness, Möbius transformations.To run the cplot unit tests, check out this repository and run Lambert series with Liouville-coefficients Imprints also supports student, faculty, and staff printing from personal computers and smartphones, all. Document printing is now managed by Imprint's 20+ Wepa printers, and their on-campus poster printing service. Lambert series with von-Mangoldt-coefficients As of July 15, 2021, IT Services has retired poster printing (CPLOT) and computer lab document printing. Jacobi theta 1 with q=0.1 * exp(0.1j * np.pi)) log) GalleryĪll plots are created with default settings. For arg(z) = 0, the color is green, for arg(z) = pi/2 it's blue, for arg(z) = -pi / 2 it's orange, and for arg(z) = pi it's pink.This makes it easy to tell the absolte value The contour abs(z) = 1 is emphasized, other abs contours are at 2, 4, 8, etc.This avoids streaks of colors occurring with other color spaces, e.g., HSL. Uniform color space for the argument colors. ![]() ![]() Only show the phase/the argument in a color wheel (phase portrait)Ĭombining all three of them gives you a cplot: Only show the absolute value sometimes as a 3D plot Historically, plotting of complex functions was in one of three ways # abs_scaling=lambda x: x / (x + 1), # how to scale the lightness in domain coloring # contours_abs=2.0, # contours_arg=(-np.pi / 2, 0, np.pi / 2, np.pi), # emphasize_abs_contour_1: bool = True, # add_colorbars: bool = True, # add_axes_labels: bool = True, # saturation_adjustment: float = 1.28, # min_contour_length = None, # linewidth = None, Import numpy as np import cplot def f( z):
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