File:Gaussian 2d 30 degrees.png
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Summary
DescriptionGaussian 2d 30 degrees.png |
English: Created in Python with Numpy and Matplotlib. |
Date | |
Source | Own work |
Author | Kopak999 |
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Creation
This file was created with Python:
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm
exp = np.exp
sqrt = np.sqrt
sin = np.sin
cos = np.cos
tau = 2 * np.pi
def ellipticalGaussian(
X, Y,
sigma_x = 1/sqrt(2),
sigma_y = 1/sqrt(2),
theta = 0,
):
"""
Returns values of a Gaussian surface whose bell curve is elliptical
instead of circular.
sigma_x: The standard deviation of the Gaussian in the X direction.
sigma_y: The standard deviation of the Gaussian in the Y direction.
sigma_x and sigma_y are comparable to the semimajor axes of an ellipse, and
affect the shape of the Gaussian mound.
theta: The angle the Gaussian is rotated about the Z-axis.
"""
a = cos(theta)**2 / (2*sigma_x**2) + sin(theta)**2 / (2*sigma_y**2)
b = -sin(2*theta) / (4*sigma_x**2) + sin(2*theta) / (4*sigma_y**2)
c = sin(theta)**2 / (2*sigma_x**2) + cos(theta)**2 / (2*sigma_y**2)
return exp(-(a*(X**2) + 2*b*(X*Y) + c*(Y**2)))
def plotGaussianSurface(
X, Y, Z,
colormap=cm.cividis,
title="",
filetype="png",
saveflag=False,
resolution=200,
dpi=300,
numticks_xy=7,
numticks_z=2,
numticks_xy_minor=25,
numticks_z_minor=5,
):
"""
Plots a 3D-surface of a 2D-Gaussian function.
X, Y: Meshgrids of x- and y-values for the Gaussian.
Z: The output of the Gaussian function.
colormap: The colormap for the surface, mapped to the Z-values of the
graph.
title: Title of the graph.
filetype: Three-letter extension of the image filetype for saving the
graph. Default is png.
saveflag: Boolean flag to check if the graph should be saved to a file.
Set to True if you want to save the graph to a file. Default is False.
resolution: Number of pixels to render along the x- and y-axes.
Default is 200, which gives a 200x200 grid.
dpi: Dots-per-inch of the image. Default is 300.
"""
plt.ioff()
# Set up kwargs:
limit = int(np.ceil(np.amax(X)))
zmin = int(np.floor(np.amin(Z)))
zmax = int(np.ceil(np.amax(Z)))
norm = mpl.colors.Normalize(vmin=zmin, vmax=zmax)
aspect = (limit*2 + 1, limit*2 + 1, zmax)
xy_major_params = dict(
direction = "in",
)
xy_minor_params = dict(
direction = "in",
which = "minor",
)
xy_major_ticks = dict(
ticks = np.linspace(-limit, limit, numticks_xy, endpoint=True,),
)
xy_minor_ticks = dict(
ticks = np.linspace(-limit, limit, numticks_xy_minor, endpoint=True,),
minor = True,
)
z_major_params = dict(
which = "major",
labelbottom = True,
labeltop = False,
)
z_minor_params = dict(
which = "minor",
)
z_major_ticks = dict(
ticks = np.linspace(0, zmax, numticks_z, endpoint=True,),
)
z_minor_ticks = dict(
ticks = np.linspace(0, zmax, numticks_z_minor, endpoint=True,),
minor = True,
)
tick_labelsize = 7
fig = plt.figure(dpi=dpi)
ax = fig.add_subplot(1, 1, 1, projection ='3d')
# Plot the surface
surf = ax.plot_surface(
X, Y, Z,
cmap = colormap,
linewidth=0,
antialiased=False,
vmin = zmin, vmax = zmax,
rcount = resolution,
ccount = resolution,
norm = norm,
)
# Customize the z axis.
ax.set_zlim(zmin, zmax)
# ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter('{x:.1f}')
ax.set_title(
title,
fontdict = dict(verticalalignment = "bottom"),
)
ax.set_box_aspect(aspect)
# ax.proj_type("ortho")
ax.set_facecolor('none')
# Set tick parameters
ax.xaxis.set_tick_params(**xy_major_params)
ax.xaxis.set_tick_params(**xy_minor_params)
ax.yaxis.set_tick_params(**xy_major_params)
ax.yaxis.set_tick_params(**xy_minor_params)
ax.zaxis.set_tick_params(**z_major_params)
ax.zaxis.set_tick_params(**z_minor_params)
ax.set_xticks(**xy_major_ticks)
ax.set_xticks(**xy_minor_ticks)
ax.set_yticks(**xy_major_ticks)
ax.set_yticks(**xy_minor_ticks)
ax.set_zticks(**z_major_ticks)
ax.set_zticks(**z_minor_ticks)
ax.tick_params(labelsize=tick_labelsize)
cbar = fig.colorbar(
surf,
ax=ax,
orientation='vertical',
shrink=0.5,
aspect=12,
pad = 0.10,
)
cbar.ax.tick_params(labelsize=tick_labelsize)
if saveflag:
savePlot(colormap, filetype)
plt.tight_layout()
plt.show()
x = y = np.linspace(-7, 7, 2**10, endpoint=True)
X, Y = np.meshgrid(x, y)
plotargs = dict(
saveflag = False,
dpi = 400,
resolution = 200,
numticks_xy=3,
numticks_xy_minor=15,
numticks_z=2,
numticks_z_minor=3,
)
plotGaussianSurface(X, Y, ellipticalGaussian(X, Y, sigma_x=1, sigma_y=2, theta=tau/12,), **plotargs)
Items portrayed in this file
depicts
16 December 2020
image/png
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Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 01:30, 17 December 2020 | 1,923 × 1,015 (182 KB) | Kopak999 | Uploaded own work with UploadWizard |
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