From 004f3ab8628c9b78c996233662095bb1887ad2f0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=88=9A=28noham=29=C2=B2?= <noham.rivoirard@gmail.com>
Date: Tue, 18 Jul 2023 16:20:23 +0200
Subject: [PATCH] Initial commit

---
 .gitattributes                     |   2 +
 modelv.py                          |  54 ++++++++
 polaired.py                        |  98 ++++++++++++++
 polaired_results.txt               | 200 +++++++++++++++++++++++++++++
 resultats/vidéos/accordéon clip.py | 106 +++++++++++++++
 test/color.py                      |  15 +++
 test/model.py                      |  45 +++++++
 test/phi(ww).png                   | Bin 0 -> 136214 bytes
 test/phi(ww).py                    |  18 +++
 test/polaire.py                    |  59 +++++++++
 test/status.py                     |  34 +++++
 11 files changed, 631 insertions(+)
 create mode 100644 .gitattributes
 create mode 100644 modelv.py
 create mode 100644 polaired.py
 create mode 100644 polaired_results.txt
 create mode 100644 resultats/vidéos/accordéon clip.py
 create mode 100644 test/color.py
 create mode 100644 test/model.py
 create mode 100644 test/phi(ww).png
 create mode 100644 test/phi(ww).py
 create mode 100644 test/polaire.py
 create mode 100644 test/status.py

diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..dfe0770
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+# Auto detect text files and perform LF normalization
+* text=auto
diff --git a/modelv.py b/modelv.py
new file mode 100644
index 0000000..cbe6dcd
--- /dev/null
+++ b/modelv.py
@@ -0,0 +1,54 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+
+t0 = 0
+tf = 20
+# tf=3
+dt = 0.5
+t = t0
+
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+
+def phi(ww): # prend en entrée la distance entre les deux véhicules
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI  # retourne la vitesse du véhicule
+
+y = np.linspace(0, 0, 11)
+xxbase = np.linspace(0, 1, 11)
+
+def position(fposition, newv):
+    newp = fposition + newv * dt
+    return newp
+
+def vitesses(fposition):
+    dist = np.diff(fposition)
+    vitesses = phi(dist)
+    newv = np.insert(vitesses, 10, 1.25)
+    return newv
+
+xxold = xxbase.copy()
+
+while(t<tf):
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+    plt.xlim([-1,20])
+    plt.ylim([-0.5, 1.5])
+    vt = vitesses(xxold)
+    xx = position(xxold, vt)
+    color = ['#ff0000', '#ff5300', '#ffa500', '#ffd200', '#ffff00', '#80c000', '#008000', '#004080', '#0000ff', '#2600c1', '#4b0082']
+    plt.scatter(xx, vt)
+    print(xx)
+    plt.scatter(xx, y, c=color)
+    plt.plot([0,20],[1.25, 1.25], color='k', linestyle='-', linewidth=1)
+    plt.xlabel('distance w  en m')
+    plt.ylabel('vitesse en m.s-¹')
+    plt.title('Evolution de la vitesse des voitures\nvitesse du leader : ' + str(U) + 'm.s-¹\ndistance minimale entre deux voitures : ' + str(Wm) + 'm')
+    plt.draw()
+    # plt.savefig(str(t)+'.png')
+    plt.pause(0.00001)
+    t += dt
+    xxold = xx.copy()
diff --git a/polaired.py b/polaired.py
new file mode 100644
index 0000000..ff5c58d
--- /dev/null
+++ b/polaired.py
@@ -0,0 +1,98 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+from colour import Color
+
+t0 = 0
+tf = 100
+dt = 0.5
+t = t0
+
+nbv = 20
+
+def rainbow_gradient(num_colors):
+    colors = []
+    base_color = Color("violet")
+    gradient = list(base_color.range_to(Color("red"), num_colors))
+    for color in gradient:
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    return colors
+colors = rainbow_gradient(nbv)
+
+def status(distances):
+    num_colors = len(distances)
+    colors = []
+    base_color = Color("green")
+    target_color = Color("red")
+    luminance_start = base_color.get_luminance()
+    luminance_end = target_color.get_luminance()
+    for i in range(num_colors):
+        moydist = distances[i]
+        t = i / (num_colors - 1)
+        adjusted_luminance = luminance_start + (luminance_end - luminance_start) * (1 - t) * (moydist - 1) / 18
+        color = Color(rgb=(base_color.rgb[0] * (1 - t) + target_color.rgb[0] * t,
+                           base_color.rgb[1] * (1 - t) + target_color.rgb[1] * t,
+                           base_color.rgb[2] * (1 - t) + target_color.rgb[2] * t))
+        color.set_luminance(adjusted_luminance)
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    return colors
+
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+
+def phi(ww): # prend en entrée la distance entre les deux véhicules
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI  # retourne la vitesse du véhicule
+
+y = np.linspace(1, 1, nbv)
+xxbase = np.linspace(0, 1, nbv)
+
+def distances(fposition):
+    # print('fposition', fposition)
+    dist = np.diff(fposition)
+    inter = fposition[0]+20-fposition[-1]
+    newdist = np.insert(dist, len(dist), inter)
+    return newdist
+
+def position(fposition, newv):
+    newp = fposition + newv * dt
+    return newp
+
+xxold = xxbase.copy()
+
+while(t<tf):
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+
+    nb = 360
+
+    r=np.linspace(1,1,nb)
+    theta=np.linspace(0,2*np.pi,nb)
+
+    plt.polar(theta, r)
+    # plt.scatter(1*np.pi, 0.5)
+
+    dst = distances(xxold)
+    statusc = status(dst)
+    print(statusc)
+
+    vt = phi(dst)
+    # print('vitesses : ', vt)
+
+    xx = position(xxold, vt)
+    # print('position : ', xx)
+
+    plt.scatter(xx/10*np.pi, y, c=colors)
+
+    for i in range(len(xx)):
+        plt.plot(xx[i]/10*np.pi, y[i], color=statusc[i])
+
+    plt.title('Vitesse maximale : ' + str(U) + 'm.s-¹\ndistance minimale entre deux voitures : ' + str(Wm) + 'm\nnombre de voitures : ' + str(nbv))
+    plt.draw()
+    plt.pause(0.00001)
+    t += dt
+    xxold = xx.copy()
\ No newline at end of file
diff --git a/polaired_results.txt b/polaired_results.txt
new file mode 100644
index 0000000..b2f41e4
--- /dev/null
+++ b/polaired_results.txt
@@ -0,0 +1,200 @@
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diff --git a/resultats/vidéos/accordéon clip.py b/resultats/vidéos/accordéon clip.py
new file mode 100644
index 0000000..611dfe2
--- /dev/null
+++ b/resultats/vidéos/accordéon clip.py	
@@ -0,0 +1,106 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+from colour import Color
+
+t0 = -10
+tf = 100
+dt = 0.5
+t = t0
+
+nbv = 30
+
+def rainbow_gradient(num_colors):
+    colors = []
+    base_color = Color("violet")
+    gradient = list(base_color.range_to(Color("red"), num_colors))
+    for color in gradient:
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    return colors
+colors = rainbow_gradient(nbv)
+
+def status(distances):
+    num_colors = len(distances)
+    colors = []
+    base_color = Color("green")
+    target_color = Color("red")
+    luminance_start = base_color.get_luminance()
+    luminance_end = target_color.get_luminance()
+    for i in range(num_colors):
+        moydist = distances[i]
+        t = i / (num_colors - 1)
+        adjusted_luminance = luminance_start + (luminance_end - luminance_start) * (1 - t) * (moydist - 1) / 18
+        color = Color(rgb=(base_color.rgb[0] * (1 - t) + target_color.rgb[0] * t,
+                           base_color.rgb[1] * (1 - t) + target_color.rgb[1] * t,
+                           base_color.rgb[2] * (1 - t) + target_color.rgb[2] * t))
+        color.set_luminance(adjusted_luminance)
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    return colors
+
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+
+def phi(ww): # prend en entrée la distance entre les deux véhicules
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI  # retourne la vitesse du véhicule
+
+y = np.linspace(1, 1, nbv)
+xxbase = np.linspace(0, 1, nbv)
+
+def distances(fposition):
+    # print('fposition', fposition)
+    dist = np.diff(fposition)
+    inter = fposition[0]+20-fposition[-1]
+    newdist = np.insert(dist, len(dist), inter)
+    return newdist
+
+def position(fposition, newv):
+    newp = fposition + newv * dt
+    return newp
+
+xxold = xxbase.copy()
+while t<0:
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+
+    plt.draw()
+    plt.pause(1 )
+    print(t)
+    t += 2*dt
+    
+while(t<tf):
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+
+    nb = 360
+
+    r=np.linspace(1,1,nb)
+    theta=np.linspace(0,2*np.pi,nb)
+
+    # plt.polar(theta, r)
+    # plt.scatter(1*np.pi, 0.5)
+
+    dst = distances(xxold)
+    statusc = status(dst)
+    print(statusc)
+
+    vt = phi(dst)
+    # print('vitesses : ', vt)
+
+    xx = position(xxold, vt)
+    # print('position : ', xx)
+
+    plt.scatter(xx/10*np.pi, y, c=colors)
+
+    for i in range(len(xx)):
+        plt.plot(xx[i]/10*np.pi, y[i], color=statusc[i])
+
+    plt.title('Vitesse maximale : ' + str(U) + 'm.s-¹\ndistance minimale entre deux voitures : ' + str(Wm) + 'm\nnombre de voitures : ' + str(nbv))
+    plt.draw()
+    plt.pause(0.00001)
+    t += dt
+    xxold = xx.copy()
\ No newline at end of file
diff --git a/test/color.py b/test/color.py
new file mode 100644
index 0000000..5bd3236
--- /dev/null
+++ b/test/color.py
@@ -0,0 +1,15 @@
+from colour import Color
+
+def rainbow_gradient(num_colors):
+    colors = []
+    base_color = Color("red")
+    gradient = list(base_color.range_to(Color("violet"), num_colors))
+    for color in gradient:
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    return colors
+
+num_colors = 10
+gradient = rainbow_gradient(num_colors)
+
+print(gradient)
\ No newline at end of file
diff --git a/test/model.py b/test/model.py
new file mode 100644
index 0000000..69741d8
--- /dev/null
+++ b/test/model.py
@@ -0,0 +1,45 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+
+t0 = 0
+tf = 20
+# tf=3
+dt = 1
+t = t0
+
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+
+ww = np.linspace(0, 10, 200)
+
+def phi(ww): # prend en entrée la distance entre les deux véhicules
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI  # retourne la vitesse du véhicule
+
+y = np.linspace(0, 0, 11)
+xxbase = np.linspace(0, 1, 11)
+
+def position(fposition):
+    dist = np.diff(fposition)
+    vitesses = phi(dist)
+    newv = np.insert(vitesses, 10, 1.25)
+    newp = fposition + newv * dt
+    return newp
+
+xxold = xxbase.copy()
+
+while(t<tf):
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+    plt.xlim([-1,10])
+    xx = position(xxold)
+    color = ['#ff0000', '#ff5300', '#ffa500', '#ffd200', '#ffff00', '#80c000', '#008000', '#004080', '#0000ff', '#2600c1', '#4b0082']
+    plt.scatter(xx, y, c=color)
+    plt.draw()
+    # plt.savefig(str(t)+'.png')
+    plt.pause(0.1)    
+    t += dt
+    xxold = xx.copy()
diff --git a/test/phi(ww).png b/test/phi(ww).png
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diff --git a/test/phi(ww).py b/test/phi(ww).py
new file mode 100644
index 0000000..63b52ba
--- /dev/null
+++ b/test/phi(ww).py
@@ -0,0 +1,18 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+ww = np.linspace(0, 10, 200)
+
+def phi(ww):
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI
+
+plt.figure(figsize=[16,9])
+plt.xlabel('distance w  en m')
+plt.ylabel('vitesse en m.s-¹')
+plt.plot(ww, phi(ww))
+plt.savefig('phi(ww).png', dpi=300)
+plt.show()
\ No newline at end of file
diff --git a/test/polaire.py b/test/polaire.py
new file mode 100644
index 0000000..450bd1f
--- /dev/null
+++ b/test/polaire.py
@@ -0,0 +1,59 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import time
+
+t0 = 0
+tf = 100
+dt = 0.5
+t = t0
+
+U = 1.25 # vitesse m.s-¹
+Wm = 0.3 # distance minimale entre la voiture et celle qui la précède m
+Ws = 0.9 # m
+
+def phi(ww): # prend en entrée la distance entre les deux véhicules
+    PHI = (U*(1 - np.exp(- (ww-Wm)/Ws)))
+    return (ww >= Wm)* PHI  # retourne la vitesse du véhicule
+
+y = np.linspace(1, 1, 11)
+xxbase = np.linspace(0, 1, 11)
+
+def position(fposition, newv):
+    newp = fposition + newv * dt
+    return newp
+
+def vitesses(fposition):
+    print('fposition', fposition)
+    dist = np.diff(fposition)
+    print('distance : ', dist)
+    vitesses = phi(dist)
+    newv = np.insert(vitesses, 10, 1.25)
+    return newv
+
+xxold = xxbase.copy()
+
+while(t<tf):
+    plt.figure(1,figsize=[16,9])
+    plt.clf()
+
+    nb = 360
+
+    r=np.linspace(1,1,nb)
+    theta=np.linspace(0,2*np.pi,nb)
+
+    plt.polar(theta, r)
+    # plt.scatter(1*np.pi, 0.5)
+
+    vt = vitesses(xxold)
+    print('vitesses : ', vt)
+
+    xx = position(xxold, vt)
+    print('position : ', xx)
+
+    color = ['#ff0000', '#ff5300', '#ffa500', '#ffd200', '#ffff00', '#80c000', '#008000', '#004080', '#0000ff', '#2600c1', '#4b0082']
+    plt.scatter(xx/10*np.pi, y, c=color)
+
+    plt.draw()
+    plt.pause(0.00001)
+    t += dt
+    xxold = xx.copy()
\ No newline at end of file
diff --git a/test/status.py b/test/status.py
new file mode 100644
index 0000000..199d475
--- /dev/null
+++ b/test/status.py
@@ -0,0 +1,34 @@
+from colour import Color
+
+def rainbow_gradient(distances):
+    num_colors = len(distances)
+    colors = []
+    base_color = Color("green")
+    target_color = Color("red")
+    
+    luminance_start = base_color.get_luminance()
+    luminance_end = target_color.get_luminance()
+    
+    for i in range(num_colors):
+        moydist = distances[i]
+        t = i / (num_colors - 1)  # Interpolation paramètre t
+        
+        adjusted_luminance = luminance_start + (luminance_end - luminance_start) * (1 - t) * (moydist - 1) / 18
+        color = Color(rgb=(base_color.rgb[0] * (1 - t) + target_color.rgb[0] * t,
+                           base_color.rgb[1] * (1 - t) + target_color.rgb[1] * t,
+                           base_color.rgb[2] * (1 - t) + target_color.rgb[2] * t))
+        color.set_luminance(adjusted_luminance)
+        
+        hex_code = color.hex_l
+        colors.append(hex_code)
+    
+    return colors
+
+distances = [0.05263158, 0.05263158, 0.05263158, 0.05263158, 0.05263158,
+             0.05263158, 0.05263158, 0.05263158, 0.05263158, 0.05263158,
+             0.05263158, 0.05263158, 0.05263158, 0.05263158, 0.05263158,
+             0.05263158, 0.05263158, 0.05263158, 19.0]
+
+gradient = rainbow_gradient(distances)
+
+print(gradient)