Functions | |
| def | lin_fit |
Variables | |
| tuple | f = open("c.txt") |
| tuple | data = np.loadtxt(f) |
| list | ch1_a = data[:,0] |
| list | ch2_a = data[:,1] |
| list | ch3_a = data[:,2] |
| list | ref = data[:,8] |
| int | past_location = 0 |
| list | rightVisual = [] |
| list | leftVisual = [] |
| list | upVisual = [] |
| list | downVisual = [] |
| int | clue_1 = 1000 |
| int | clue_2 = 1000 |
| int | left_location = 0 |
| int | past_left_location = 0 |
| int | clue_3 = 1000 |
| int | clue_4 = 1000 |
| int | right_location = 0 |
| int | past_right_location = 0 |
| int | clue_5 = 1000 |
| int | clue_6 = 1000 |
| int | clue_7 = 1000 |
| int | up_location = 0 |
| int | past_up_location = 0 |
| int | clue_8 = 1000 |
| int | clue_9 = 1000 |
| int | clue_10 = 1000 |
| int | down_location = 0 |
| int | past_down_location = 0 |
| int | BoxSize = 25 |
| int | BoxSize2 = 200 |
| int | BoxSize3 = 50 |
| tuple | ch1_b = np.array([]) |
| tuple | ch2_b = np.array([]) |
| tuple | ch3_b = np.array([]) |
| tuple | ch1_c = np.array([]) |
| tuple | ch2_c = np.array([]) |
| tuple | ch3_c = np.array([]) |
| int | countD = 0 |
| int | countU = 0 |
| int | countR = 0 |
| int | countL = 0 |
| string | Qorder = "Start" |
| tuple | ch1_y = copy(ch1_c) |
| tuple | ch2_y = copy(ch2_c) |
| tuple | ch3_y = copy(ch3_c) |
| tuple | ch1_m = copy(ch1_c) |
| tuple | ch2_m = copy(ch2_c) |
| tuple | ch3_m = copy(ch3_c) |
| tuple | ch1_n = copy(ch1_c) |
| tuple | ch2_n = copy(ch2_c) |
| tuple | ch3_n = copy(ch3_c) |
| tuple | ch1_o = copy(ch1_c) |
| tuple | ch2_o = copy(ch2_c) |
| tuple | ch3_o = copy(ch3_c) |
| tuple | ch1_p = copy(ch1_c) |
| tuple | ch2_p = copy(ch2_c) |
| tuple | ch3_p = copy(ch3_c) |
| tuple | fig1 = figure() |
| tuple | ch1_what = diff(copy(ch1_c[200:10000])) |
| list | ch1_where = ch1_what[numpy.logical_not(numpy.isnan(ch1_what))] |
| tuple | ch2_what = diff(copy(ch2_c[200:10000])) |
| list | ch2_where = ch2_what[numpy.logical_not(numpy.isnan(ch2_what))] |
| tuple | ch3_what = diff(copy(ch3_c[200:10000])) |
| list | ch3_where = ch3_what[numpy.logical_not(numpy.isnan(ch3_what))] |
| tuple | maxThresh = min([max(ch1_where),max(ch2_where),max(ch3_where)]) |
| tuple | minThresh = max([min(ch1_where),min(ch2_where),min(ch3_where)]) |
| tuple | x = np.linspace(n-9999,n,num=10000) |
| tuple | coefs = np.polyfit(x,ch1_a[n-10000:n],1) |
| tuple | ch1_z = copy(ch1_c) |
| tuple | ch2_z = copy(ch2_c) |
| tuple | ch3_z = copy(ch3_c) |
| tuple | ch1_X = diff(ch1_y) |
| tuple | ch2_X = diff(ch2_y) |
| tuple | ch3_X = diff(ch3_y) |
| tuple | p1 = plot(ch1_y, label='ch1') |
| tuple | p2 = plot(ch2_y, label='ch2') |
| tuple | p3 = plot(ch3_y, label='ch3') |
| tuple | fig2 = plt.figure() |
| def vemg.lin_fit | ( | signal | ) |
| int vemg.BoxSize = 25 |
| int vemg.BoxSize2 = 200 |
| int vemg.BoxSize3 = 50 |
| list vemg.ch1_a = data[:,0] |
| tuple vemg::ch1_b = np.array([]) |
| tuple vemg::ch1_c = np.array([]) |
| tuple vemg::ch1_m = copy(ch1_c) |
| tuple vemg::ch1_n = copy(ch1_c) |
| tuple vemg::ch1_o = copy(ch1_c) |
| tuple vemg::ch1_p = copy(ch1_c) |
| tuple vemg.ch1_what = diff(copy(ch1_c[200:10000])) |
| list vemg.ch1_where = ch1_what[numpy.logical_not(numpy.isnan(ch1_what))] |
| tuple vemg.ch1_X = diff(ch1_y) |
| tuple vemg::ch1_y = copy(ch1_c) |
| tuple vemg::ch1_z = copy(ch1_c) |
| list vemg.ch2_a = data[:,1] |
| tuple vemg::ch2_b = np.array([]) |
| tuple vemg::ch2_c = np.array([]) |
| tuple vemg::ch2_m = copy(ch2_c) |
| tuple vemg::ch2_n = copy(ch2_c) |
| tuple vemg::ch2_o = copy(ch2_c) |
| tuple vemg::ch2_p = copy(ch2_c) |
| tuple vemg.ch2_what = diff(copy(ch2_c[200:10000])) |
| list vemg.ch2_where = ch2_what[numpy.logical_not(numpy.isnan(ch2_what))] |
| tuple vemg.ch2_X = diff(ch2_y) |
| tuple vemg::ch2_y = copy(ch2_c) |
| tuple vemg::ch2_z = copy(ch2_c) |
| list vemg.ch3_a = data[:,2] |
| tuple vemg::ch3_b = np.array([]) |
| tuple vemg::ch3_c = np.array([]) |
| tuple vemg::ch3_m = copy(ch3_c) |
| tuple vemg::ch3_n = copy(ch3_c) |
| tuple vemg::ch3_o = copy(ch3_c) |
| tuple vemg::ch3_p = copy(ch3_c) |
| tuple vemg.ch3_what = diff(copy(ch3_c[200:10000])) |
| list vemg.ch3_where = ch3_what[numpy.logical_not(numpy.isnan(ch3_what))] |
| tuple vemg.ch3_X = diff(ch3_y) |
| tuple vemg::ch3_y = copy(ch3_c) |
| tuple vemg::ch3_z = copy(ch3_c) |
| int vemg::clue_1 = 1000 |
| int vemg::clue_10 = 1000 |
| int vemg::clue_2 = 1000 |
| int vemg::clue_3 = 1000 |
| int vemg::clue_4 = 1000 |
| int vemg::clue_5 = 1000 |
| int vemg::clue_6 = 1000 |
| int vemg::clue_7 = 1000 |
| int vemg::clue_8 = 1000 |
| int vemg::clue_9 = 1000 |
| tuple vemg::coefs = np.polyfit(x,ch1_a[n-10000:n],1) |
| int vemg.countD = 0 |
| int vemg.countL = 0 |
| int vemg.countR = 0 |
| int vemg.countU = 0 |
| tuple vemg::down_location = 0 |
| list vemg.downVisual = [] |
| tuple vemg.f = open("c.txt") |
| tuple vemg::fig1 = figure() |
| tuple vemg.fig2 = plt.figure() |
| tuple vemg::left_location = 0 |
| list vemg.leftVisual = [] |
| tuple vemg.minThresh = max([min(ch1_where),min(ch2_where),min(ch3_where)]) |
| string vemg.Qorder = "Start" |
| tuple vemg::right_location = 0 |
| list vemg.rightVisual = [] |
| tuple vemg::up_location = 0 |
| list vemg.upVisual = [] |
| tuple vemg.x = np.linspace(n-9999,n,num=10000) |
1.7.1