drawing elliptical lines between two circles without intersecting matplotlib

Example code:

from matplotlib
import pyplot as plt
from matplotlib.patches
import Circle, Arc

fig, ax = plt.subplots(figsize = (6, 6))

ax.add_patch(Circle((0.5, 0.75), 0.05, edgecolor = 'black', facecolor = 'white', zorder = 3))
ax.add_patch(Circle((0.5, 0.25), 0.05, edgecolor = 'black', facecolor = 'white', zorder = 3))
ax.add_patch(Arc((0.5, 0.5), 0.1, 0.5))

Suggestion : 2

I'm trying to draw elliptical lines using anycodings_matplotlib matplotlib to connect two circles but would anycodings_matplotlib like to make it so the elliptical lines do anycodings_matplotlib not intersect either circle.,Rather than adjusting the figure anycodings_matplotlib manually, consider using the zorder in anycodings_matplotlib the Patch constructor.,The various artists on a plot are anycodings_matplotlib stacked upon each other vertically, with anycodings_matplotlib those with the highest zorder on top. By anycodings_matplotlib setting the zorder, therefore, you will anycodings_matplotlib cause the circles to be drawn over the anycodings_matplotlib ellipse, obscuring it.,which as you can see has lines going through anycodings_matplotlib both circle A and B. I decided to use anycodings_matplotlib matplotlib.patches.Arc since I didn't want anycodings_matplotlib it filled and it allowed me to draw a left anycodings_matplotlib and right part. Here is what I have:

which as you can see has lines going through anycodings_matplotlib both circle A and B. I decided to use anycodings_matplotlib matplotlib.patches.Arc since I didn't want anycodings_matplotlib it filled and it allowed me to draw a left anycodings_matplotlib and right part. Here is what I have:

from matplotlib
import pyplot
from matplotlib.patches
import Arc
import math

def calculate_perimeter(a, b):
   perimeter = math.pi * (3 * (a + b) - math.sqrt((3 * a + b) * (a + 3 * b)))
return perimeter

def draw_circle(xy, radius, text):
   circle = pyplot.Circle(xy, radius = radius, fill = False)
pyplot.gca().add_patch(circle)
pyplot.gca().annotate(text, xy = xy, fontsize = 10, ha = 'center', va = 'center')

def draw_arc(xy1, xy2, a, b, theta1, theta2):
   # Calculate center of the elliptical arc
center = (xy1[0], (xy1[1] + xy2[1]) / 2.0)
arc = Arc(center, a, b, theta1 = theta1, theta2 = theta2)
pyplot.gca().add_patch(arc)

if __name__ == '__main__':
   pyplot.figure()
center_circle1 = (5, 5)
center_circle2 = (5, 20)
dist_y = center_circle2[1] - center_circle1[1]
adjustment = 5.3 # @TODO: How do I calculate what this needs to be ?
      # Circles
   draw_circle(center_circle1, 1, 'A')
draw_circle(center_circle2, 1, 'B')
# Draw right side of arc
theta1 = 270.0 + adjustment
theta2 = 90.0 - adjustment
draw_arc(center_circle1, center_circle2, 3, dist_y, theta1, theta2)
# Draw left side of arc
theta1 = 90.0 + adjustment
theta2 = 270.0 - adjustment
draw_arc(center_circle1, center_circle2, 3, dist_y, theta1, theta2)
pyplot.axis('scaled')
pyplot.axis('off')
pyplot.show()

Example code:

from matplotlib
import pyplot as plt
from matplotlib.patches
import Circle, Arc

fig, ax = plt.subplots(figsize = (6, 6))

ax.add_patch(Circle((0.5, 0.75), 0.05, edgecolor = 'black', facecolor = 'white', zorder = 3))
ax.add_patch(Circle((0.5, 0.25), 0.05, edgecolor = 'black', facecolor = 'white', zorder = 3))
ax.add_patch(Arc((0.5, 0.5), 0.1, 0.5))

Suggestion : 3

The use of the following functions, methods, classes and modules is shown in this example:,Draw many ellipses. Here individual ellipses are drawn. Compare this to the Ellipse collection example.,Draw many ellipses with different angles., Demo of the histogram function's different histtype settings

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches
import Ellipse

# Fixing random state
for reproducibility
np.random.seed(19680801)

NUM = 250

ells = [Ellipse(xy = np.random.rand(2) * 10,
      width = np.random.rand(), height = np.random.rand(),
      angle = np.random.rand() * 360)
   for i in range(NUM)
]

fig, ax = plt.subplots(subplot_kw = {
   'aspect': 'equal'
})
for e in ells:
   ax.add_artist(e)
e.set_clip_box(ax.bbox)
e.set_alpha(np.random.rand())
e.set_facecolor(np.random.rand(3))

ax.set_xlim(0, 10)
ax.set_ylim(0, 10)

plt.show()

angle_step = 45 # degrees
angles = np.arange(0, 180, angle_step)

fig, ax = plt.subplots(subplot_kw = {
   'aspect': 'equal'
})

for angle in angles:
   ellipse = Ellipse((0, 0), 4, 2, angle = angle, alpha = 0.1)
ax.add_artist(ellipse)

ax.set_xlim(-2.2, 2.2)
ax.set_ylim(-2.2, 2.2)

plt.show()

Suggestion : 4

At this point, any plt plot command will cause a figure window to open, and further commands can be run to update the plot. Some changes (such as modifying properties of lines that are already drawn) will not draw automatically; to force an update, use plt.draw(). Using plt.show() in Matplotlib mode is not required.,plt.imshow() will automatically adjust the axis aspect ratio to match the input data; you can change this by setting, for example, plt.axis(aspect='image') to make x and y units match., plt.imshow() will automatically adjust the axis aspect ratio to match the input data; you can change this by setting, for example, plt.axis(aspect='image') to make x and y units match. ,Additional keyword arguments to plt.plot specify a wide range of properties of the lines and markers (Figure 4-23):

Just as we use the np shorthand for NumPy and the pd shorthand for Pandas, we will use some standard shorthands for Matplotlib imports:

In[1]: import matplotlib as mpl
import matplotlib.pyplot as plt

We will use the plt.style directive to choose appropriate aesthetic styles for our figures. Here we will set the classic style, which ensures that the plots we create use the classic Matplotlib style:

In[2]: plt.style.use('classic')

So, for example, you may have a file called myplot.py containing the following:

#-- -- -- - file: myplot.py-- -- --
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)

plt.plot(x, np.sin(x))
plt.plot(x, np.cos(x))

plt.show()

You can then run this script from the command-line prompt, which will result in a window opening with your figure displayed:

$ python myplot.py

It can be very convenient to use Matplotlib interactively within an IPython shell (see Chapter 1). IPython is built to work well with Matplotlib if you specify Matplotlib mode. To enable this mode, you can use the %matplotlib magic command after starting ipython:

In[1]: % matplotlib
Using matplotlib backend: TkAgg

In[2]: import matplotlib.pyplot as plt

For this book, we will generally opt for %matplotlib inline:

In[3]: % matplotlib inline

After you run this command (it needs to be done only once per kernel/session), any cell within the notebook that creates a plot will embed a PNG image of the resulting graphic (Figure 4-1):

In[4]: import numpy as np
x = np.linspace(0, 10, 100)

fig = plt.figure()
plt.plot(x, np.sin(x), '-')
plt.plot(x, np.cos(x), '--');

One nice feature of Matplotlib is the ability to save figures in a wide variety of formats. You can save a figure using the savefig() command. For example, to save the previous figure as a PNG file, you can run this:

In[5]: fig.savefig('my_figure.png')

We now have a file called my_figure.png in the current working directory:

In[6]: !ls - lh my_figure.png

In[6]: !ls -lh my_figure.png

-rw - r--r--1 jakevdp staff 16 K Aug 11 10: 59 my_figure.png

In savefig(), the file format is inferred from the extension of the given filename. Depending on what backends you have installed, many different file formats are available. You can find the list of supported file types for your system by using the following method of the figure canvas object:

In[8]: fig.canvas.get_supported_filetypes()

In[8]: fig.canvas.get_supported_filetypes()

Out[8]: {
   'eps': 'Encapsulated Postscript',
   'jpeg': 'Joint Photographic Experts Group',
   'jpg': 'Joint Photographic Experts Group',
   'pdf': 'Portable Document Format',
   'pgf': 'PGF code for LaTeX',
   'png': 'Portable Network Graphics',
   'ps': 'Postscript',
   'raw': 'Raw RGBA bitmap',
   'rgba': 'Raw RGBA bitmap',
   'svg': 'Scalable Vector Graphics',
   'svgz': 'Scalable Vector Graphics',
   'tif': 'Tagged Image File Format',
   'tiff': 'Tagged Image File Format'
}

Suggestion : 5

Returns a Circle consisting of all points where two perpendicular tangent lines to the ellipse cross each other.,Returns a Circle whose diameter is the major axis of the ellipse.,Returns the equation of an ellipse aligned with the x and y axes; when slope is given, the equation returned corresponds to an ellipse with a major axis having that slope.,Section modulus is a geometric property of an ellipse defined as the ratio of second moment of area to the distance of the extreme end of the ellipse from the centroidal axis.

>>> from sympy
import Ellipse, Point, Rational
   >>>
   e1 = Ellipse(Point(0, 0), 5, 1) >>>
   e1.hradius, e1.vradius(5, 1) >>>
   e2 = Ellipse(Point(3, 1), hradius = 3, eccentricity = Rational(4, 5)) >>>
   e2
Ellipse(Point2D(3, 1), 3, 9 / 5)

>>> from sympy
import Point, Ellipse
   >>>
   p1 = Point(0, 0) >>>
   e1 = Ellipse(p1, 3, 1) >>>
   e1.apoapsis
2 * sqrt(2) + 3

>>> from sympy
import Point, Ellipse
   >>>
   e1 = Ellipse(Point(0, 0), 3, 2) >>>
   e1.arbitrary_point()
Point2D(3 * cos(t), 2 * sin(t))

>>> from sympy
import Point, Ellipse
   >>>
   p1 = Point(0, 0) >>>
   e1 = Ellipse(p1, 3, 1) >>>
   e1.area
3 * pi

>>> from sympy
import Ellipse, Point, symbols
   >>>
   c = Point(1, 2) >>>
   Ellipse(c, 8, 7).auxiliary_circle()
Circle(Point2D(1, 2), 8) >>>
   a, b = symbols('a b') >>>
   Ellipse(c, a, b).auxiliary_circle()
Circle(Point2D(1, 2), Max(a, b))

>>> from sympy
import Point, Ellipse
   >>>
   p1 = Point(0, 0) >>>
   e1 = Ellipse(p1, 3, 1) >>>
   e1.center
Point2D(0, 0)