return a
flist = [f1, f2, f3]
## APPLYING RK4 ALGO
from rk4_fnc_pre import rk4_gen
(y, time) = rk4_gen(flist, initials, timescale, maxt)
yA = y
y = y.tolist()
## PLOTS
fncs.plot_2d(y[2], y[0], 'Time', 'Position', str(p) + '.0', lw=0.5)
fncs.plot_2d(y[0], y[1], 'Position', 'Velocity', str(p) + '.1', lw=0.5)
## POINCARE
(p_maps_pos, p_maps_vel) = fncs.poincare_map(y[0], y[1], n, cycles)
fncs.plot_2d(p_maps_pos,
p_maps_vel,
'Position',
'Velocity',
str(p) + '.1',
linestyle='none',
marker='.')
## EMBEDDED DIMENSION
a = w
return a
flist = [f1,f2,f3]
## APPLYING RK4 ALGO
from rk4_fnc_pre import rk4_gen
(y, time) = rk4_gen(flist, initials, timescale, maxt)
y = y.tolist()
## PLOTS
fncs.plot_2d(y[2], y[0], 'Time', 'Position', str(i)+ '.0',lw = 0.5)
fncs.plot_2d(y[1], y[0], 'Velocity', 'Position', str(i)+ '.1',lw = 0.5)
## EMBEDDED DIMENSION
start = 5
length = len(y[0])
position_add1 = fncs.embed_dim(y[0],length,start)
fncs.plot_2d(position_add1,y[0],
'Position + ' + str(start), 'Position',
str(i)+ '.2', lw = 0.5)
plt.show()
a = r[p] * x * (1 - x / K)
return a
flist = [f1]
## APPLYING RK4 ALGO
from rk4_fnc_pre import rk4_gen
(y, time) = rk4_gen(flist, initials, timescale, maxt)
y = y.tolist()
## PLOTS
fncs.plot_2d(time, y[0], 'Time', 'Position', str(p) + '.0', lw=0.5)
## POINCARE
## (p_maps_pos,p_maps_vel) = fncs.poincare_map(y[0],y[1],n,cycles)
##
## fncs.plot_2d(p_maps_pos, p_maps_vel,
## 'Position', 'Velocity', str(p)+ '.1',
## linestyle = 'none', marker = '.')
##
## EMBEDDED DIMENSION
## start = 5
## length = len(y[0])
##
length = int(maxt / timescale)
idx = 0
def listmake(n):
return [0] * n
xA = listmake(length)
tA = listmake(length)
alist = [0.5, 0.75, 0.87, 0.9]
for p in range(0, len(alist)):
idx = 0
initial = 0.2
xA[0] = initial
tA[0] = 0
while idx < length - 1:
xA[idx + 1] = 4 * alist[p] * xA[idx] * (1 - xA[idx])
tA[idx + 1] = tA[idx] + timescale
idx = idx + 1
fncs.plot_2d(tA, xA, 'Time', 'Position', str(p) + '.0', lw=0.5)
plt.show()
xpos1[i] = m.sin(y[0][i])
xpos2[i] = m.sin(y[0][i]) + m.sin(y[1][i])
ypos1[i] = -m.cos(y[0][i])
ypos2[i] = -m.cos(y[0][i]) - m.cos(y[1][i])
# Poincare section when bob goes from -ve to +ve
filtered_array = fncs.bools_spatial_1var(xpos2, 0, 1)
poincare_array = nparray[:, filtered_array]
poin_phases = [(phases + np.pi) % (2 * np.pi) - np.pi
for phases in poincare_array[0]]
fncs.plot_2d(poin_phases,
poincare_array[2],
'Theta 1',
'Velocity 1',
str(p) + '.1',
linestyle='none',
marker='.')
## Mapping to pie plot
import operator as op
pie_plot_raw = np.ndarray(shape=(5, length), dtype=float)
pie_plot_raw[0] = time
#Overall direction (column 2)
direc_top = fncs.bools_spatial_2var(xpos1, op.ge, 0, ypos1, op.gt, 0)
posi_direc_moment = np.array([x < 0 for x in y[2]