├── LICENSE
├── basicLinePlotting.py
├── curvePlot_VideoPrep_3dPlot.py
└── curvePlot_VideoPrep_fitPlot.py


/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2022 codinglikemad
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/basicLinePlotting.py:
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 1 | import numpy as np
 2 | import matplotlib
 3 | import matplotlib.pyplot as plt
 4 | from matplotlib.animation import FFMpegWriter
 5 | 
 6 | # This needs to be changed for your code
 7 | plt.rcParams['animation.ffmpeg_path'] = 'C:\\Users\\spsha\\Desktop\\ffmpeg-4.4-full_build\\bin\\ffmpeg.exe'
 8 | 
 9 | # This is the final example I showed in the code - notice I have 2 "cursor marks" not shown in the video
10 | fig = plt.figure()
11 | l, = plt.plot([], [], 'k-')
12 | l2, = plt.plot([], [], 'm--')
13 | p1, = plt.plot([], [], 'ko')
14 | p2, = plt.plot([], [], 'mo')
15 | 
16 | plt.xlabel('xlabel')
17 | plt.ylabel('ylabel')
18 | plt.title('title')
19 | 
20 | plt.xlim(-5, 5)
21 | plt.ylim(-5, 5)
22 | 
23 | def func(x):
24 |     return np.sin(x)*3
25 | 
26 | def func2(x):
27 |     return np.cos(x)*3
28 | 
29 | metadata = dict(title='Movie', artist='codinglikemad')
30 | writer = FFMpegWriter(fps=15, metadata=metadata)
31 | 
32 | 
33 | xlist = []
34 | xlist2 = []
35 | ylist = []
36 | ylist2 = []
37 | 
38 | with writer.saving(fig, "sinWave2.mp4", 100):
39 | 
40 |     # Plot the first line and cursor
41 |     for xval in np.linspace(-5,5,100):
42 |         xlist.append(xval)
43 |         ylist.append(func(xval))
44 | 
45 |         l.set_data(xlist,ylist)
46 |         l2.set_data(xlist2,ylist2)
47 | 
48 |         p1.set_data(xval,func(xval))
49 | 
50 |         writer.grab_frame()
51 | 
52 |     # plot the second line and cursor
53 |     for xval in np.linspace(-5,5,100):
54 |         xlist2.append(xval)
55 |         ylist2.append(func2(xval))
56 | 
57 |         l.set_data(xlist,ylist)
58 |         l2.set_data(xlist2,ylist2)
59 | 
60 |         p2.set_data(xval,func2(xval))
61 | 
62 |         writer.grab_frame()
63 | 


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/curvePlot_VideoPrep_3dPlot.py:
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 1 | import numpy as np
 2 | import matplotlib
 3 | # matplotlib.use("Agg") # useful for a webserver case where you don't want to ever visualize the result live.
 4 | from matplotlib import cm
 5 | import matplotlib.pyplot as plt
 6 | from matplotlib.animation import FFMpegWriter, PillowWriter
 7 | 
 8 | # Change to reflect your file location!
 9 | plt.rcParams['animation.ffmpeg_path'] = 'C:\\Users\\spsha\\Desktop\\ffmpeg-4.4-full_build\\bin\\ffmpeg.exe'
10 | 
11 | 
12 | # Fixing random state for reproducibility
13 | np.random.seed(19680801)
14 | 
15 | 
16 | metadata = dict(title='Movie', artist='codinglikemad')
17 | # writer = PillowWriter(fps=15, metadata=metadata)
18 | writer = FFMpegWriter(fps=15, metadata=metadata)
19 | 
20 | fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
21 | 
22 | plt.xlim(-5, 5)
23 | plt.ylim(-5, 5)
24 | 
25 | 
26 | def func(x,y,r,t):
27 |     return np.cos(r/2+t)*np.exp(-np.square(r)/50)
28 | 
29 | xvec = np.linspace(-10, 10, 1000)
30 | yvec = np.linspace(-10, 10, 1000)
31 | 
32 | xlist, ylist = np.meshgrid(xvec, yvec)
33 | 
34 | rlist = np.sqrt( np.square(xlist) + np.square(ylist) )
35 | 
36 | with writer.saving(fig, "exp3d.mp4", 100):
37 |     for tval in np.linspace(0,20,160):
38 |         print(tval)
39 |         zval = func(xlist,ylist,rlist, tval)
40 |         ax.set_zlim(-1, 1)
41 |         ax.plot_surface(xlist,ylist,zval,cmap=cm.viridis)
42 | 
43 |         writer.grab_frame()
44 |         plt.cla()


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/curvePlot_VideoPrep_fitPlot.py:
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 1 | import numpy as np
 2 | import matplotlib
 3 | # matplotlib.use("Agg") # You can uncomment this line to have a totally non-gui experience - useful for webserver use where the file is rendered and shown to a user.
 4 | import matplotlib.pyplot as plt
 5 | from matplotlib.animation import FFMpegWriter, PillowWriter
 6 | 
 7 | # This will need to be changed to match your directory.
 8 | plt.rcParams['animation.ffmpeg_path'] = 'C:\\Users\\spsha\\Desktop\\ffmpeg-4.4-full_build\\bin\\ffmpeg.exe'
 9 | 
10 | # To make sure your example looks like mine, set the random seed. Helps with fine tuning the graph too.
11 | np.random.seed(102434201)
12 | 
13 | metadata = dict(title='Movie', artist='codinglikemad')
14 | # writer = PillowWriter(fps=15, metadata=metadata)
15 | writer = FFMpegWriter(fps=15, metadata=metadata)
16 | 
17 | fig = plt.figure()
18 | plt.xlim(-8, 8)
19 | plt.ylim(-8, 8)
20 | 
21 | # Generate some random linear data to fit:
22 | def func(x):
23 |     return x*1.2 + 0.1 + np.random.normal(0,2, x.shape)
24 | 
25 | x = np.random.uniform(-7,7,10)
26 | x = np.sort(x) # Sort the x values here so we get a nice left to right progression in the animation
27 | y = func(x)
28 | 
29 | coeff = np.polyfit(x,y,1)
30 | print(coeff)
31 | xline = np.linspace(-6,6,40) # This controls how long the animation takes below.
32 | yline = np.polyval(coeff, xline)
33 | 
34 | lPnt, = plt.plot(x, y, 'o')
35 | l, = plt.plot(xline, yline, 'k-', linewidth=3)
36 | 
37 | plt.show()
38 | # You need to close the figure for the 2nd half of the script to run - remove the plotting above if you want to generate without intervention.
39 | 
40 | 
41 | fig = plt.figure()
42 | plt.xlim(-10, 10)
43 | plt.ylim(-10, 10)
44 | 
45 | lPnt, = plt.plot([], [], 'o')
46 | l, = plt.plot([], [], 'k-', linewidth=3)
47 | 
48 | xLineList = []
49 | yLineList = []
50 | 
51 | xPntList = []
52 | yPntList = []
53 | 
54 | # We generate each plot sequentially here
55 | with writer.saving(fig, "fitPlot.mp4", 100):
56 | 
57 |     # First show the data points
58 |     for xval,yval in zip(x,y):
59 | 
60 |         xPntList.append(xval)
61 |         yPntList.append(yval)
62 | 
63 |         lPnt.set_data(xPntList,yPntList)
64 |         l.set_data(xLineList,yLineList)
65 | 
66 |         # Double up the frames to slow things down a bit here.
67 |         writer.grab_frame()
68 |         writer.grab_frame()
69 | 
70 |     # Add the line fit
71 |     for xval,yval in zip(xline,yline):
72 | 
73 |         xLineList.append(xval)
74 |         yLineList.append(yval)
75 | 
76 |         lPnt.set_data(xPntList,yPntList)
77 |         l.set_data(xLineList,yLineList)
78 | 
79 |         writer.grab_frame()
80 | 
81 |     # We pad at the end to create some "pauseing space"
82 |     for ii in range(10):
83 |         writer.grab_frame()
84 | 


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