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]