| 1 | |
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| 2 | """ |
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| 3 | Plot up files from the Hinwood project. |
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| 4 | """ |
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| 5 | from os import sep |
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| 6 | import project |
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| 7 | from copy import deepcopy |
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| 8 | #from scipy import arange |
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| 9 | from csv import writer |
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| 10 | |
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| 11 | from Numeric import arange, array, zeros, Float, where, greater, less, \ |
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| 12 | compress, argmin, choose, searchsorted |
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| 13 | |
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| 14 | from anuga.fit_interpolate.interpolate import interpolate_sww2csv |
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| 15 | from anuga.shallow_water.data_manager import csv2dict |
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| 16 | from anuga.utilities.numerical_tools import ensure_numeric |
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| 17 | |
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| 18 | |
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| 19 | SLOPE_STR = 'stage_slopes' |
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| 20 | TIME_STR = 'times' |
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| 21 | |
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| 22 | TIME_BORDER = 5 |
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| 23 | LOCATION_BORDER = .5 |
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| 24 | |
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| 25 | def load_sensors(quantity_file): |
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| 26 | """ |
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| 27 | Load a csv file, where the first row is the column header and |
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| 28 | the first colum explains the rows. |
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| 29 | """ |
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| 30 | #slope, _ = csv2dict(file_sim) |
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| 31 | |
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| 32 | # Read the depth file |
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| 33 | dfid = open(quantity_file) |
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| 34 | lines = dfid.readlines() |
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| 35 | dfid.close() |
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| 36 | |
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| 37 | title = lines.pop(0) |
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| 38 | n_time = len(lines) |
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| 39 | n_sensors = len(lines[0].split(','))-1 # -1 to remove time |
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| 40 | times = zeros(n_time, Float) #Time |
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| 41 | depths = zeros(n_time, Float) # |
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| 42 | sensors = zeros((n_time,n_sensors), Float) |
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| 43 | quantity_locations = title.split(',') #(',') |
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| 44 | quantity_locations.pop(0) # remove 'time' |
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| 45 | |
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| 46 | # Doing j.split(':')[0] drops the y location |
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| 47 | locations = [float(j.split(':')[0]) for j in quantity_locations] |
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| 48 | |
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| 49 | for i, line in enumerate(lines): |
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| 50 | fields = line.split(',') #(',') |
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| 51 | fields = [float(j) for j in fields] |
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| 52 | times[i] = fields[0] |
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| 53 | sensors[i] = fields[1:] # 1: to remove time |
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| 54 | |
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| 55 | #print "times",times |
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| 56 | #print "locations", locations |
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| 57 | #print "sensors", sensors |
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| 58 | return times, locations, sensors |
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| 59 | |
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| 60 | def load_slopes(stage_file): |
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| 61 | """ |
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| 62 | Finds the slope, wrt distance of a distance, time, quantity csv file. |
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| 63 | |
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| 64 | returns the times and slope_locations vectors and the slopes array. |
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| 65 | """ |
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| 66 | times, locations, sensors = load_sensors(stage_file) |
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| 67 | n_slope_locations = len(locations)-1 |
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| 68 | n_time = len(times) |
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| 69 | slope_locations = zeros(n_slope_locations, Float) # |
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| 70 | slopes = zeros((n_time,n_slope_locations), Float) |
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| 71 | |
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| 72 | # An array of the sensor spacing values |
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| 73 | delta_locations = zeros(n_slope_locations, Float) |
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| 74 | |
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| 75 | for i in arange(n_slope_locations): |
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| 76 | delta_locations[i] = (locations[i+1] - locations[i]) |
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| 77 | slope_locations[i] = locations[i] + 0.5*delta_locations[i] |
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| 78 | |
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| 79 | for j in arange(n_time): |
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| 80 | for i in arange(n_slope_locations): |
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| 81 | slopes[j,i] = (sensors[j,i+1] - sensors[j,i])/delta_locations[i] |
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| 82 | |
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| 83 | return times, slope_locations, slopes |
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| 84 | |
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| 85 | |
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| 86 | def graph_contours(times, x_data, z_data, |
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| 87 | y_label='Time, seconds', |
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| 88 | plot_title="slope", |
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| 89 | x_label='x location, m', |
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| 90 | save_as=None, |
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| 91 | is_interactive=False, |
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| 92 | break_xs=None, |
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| 93 | break_times=None): |
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| 94 | """ |
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| 95 | Currently used to generate stage slope contour graphs. |
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| 96 | |
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| 97 | Has been generalised a bit. |
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| 98 | """ |
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| 99 | # Do not move these imports. Tornado doesn't have pylab |
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| 100 | from pylab import meshgrid, cm, contourf, contour, ion, plot, xlabel, \ |
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| 101 | ylabel, close, legend, savefig, title, figure ,colorbar, show , axis |
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| 102 | |
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| 103 | origin = 'lower' |
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| 104 | |
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| 105 | if is_interactive: |
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| 106 | ion() |
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| 107 | |
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| 108 | # Can't seem to reshape this info once it is in the function |
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| 109 | CS = contourf(x_data, times, z_data, 10, |
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| 110 | cmap=cm.bone, |
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| 111 | origin=origin) |
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| 112 | |
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| 113 | #CS2 = contour(x_data, times, z_data, CS.levels[::1], |
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| 114 | # colors = 'r', |
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| 115 | # origin=origin, |
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| 116 | # hold='on') |
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| 117 | |
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| 118 | title(plot_title) |
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| 119 | xlabel(x_label) |
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| 120 | ylabel(y_label) |
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| 121 | |
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| 122 | if break_times is not None and break_xs is not None: |
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| 123 | plot(break_xs, break_times, 'ro') |
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| 124 | |
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| 125 | |
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| 126 | # Make a colorbar for the ContourSet returned by the contourf call. |
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| 127 | cbar = colorbar(CS) |
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| 128 | |
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| 129 | # Add the contour line levels to the colorbar |
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| 130 | cbar.ax.set_ylabel('stage slope') |
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| 131 | #cbar.add_lines(CS2) |
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| 132 | |
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| 133 | if is_interactive: |
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| 134 | raw_input() # Wait for enter pressed |
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| 135 | |
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| 136 | if save_as is not None: |
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| 137 | savefig(save_as) |
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| 138 | close() #Need to close this plot |
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| 139 | |
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| 140 | def graph_froude(times, x_data, z_data, |
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| 141 | y_label='Time, seconds', |
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| 142 | plot_title="Froude Number", |
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| 143 | x_label='x location, m', |
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| 144 | save_as=None, |
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| 145 | is_interactive=False, |
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| 146 | break_xs=None, |
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| 147 | break_times=None): |
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| 148 | """ |
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| 149 | Used to generate a froude Number contour graphs. |
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| 150 | |
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| 151 | """ |
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| 152 | # Do not move these imports. Tornado doesn't have pylab |
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| 153 | from pylab import meshgrid, cm, contourf, contour, ion, plot, xlabel, \ |
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| 154 | ylabel, close, legend, savefig, title, figure ,colorbar, show , axis |
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| 155 | |
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| 156 | origin = 'lower' |
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| 157 | |
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| 158 | if is_interactive: |
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| 159 | ion() |
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| 160 | |
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| 161 | # Can't seem to reshape this info once it is in the function |
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| 162 | #CS = contourf(x_data, times, z_data, [-1,0.6,0.8,1,2,4], |
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| 163 | # colors = ('black', 'r', 'g', 'b','r'), |
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| 164 | # #cmap=cm.bone, |
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| 165 | # origin=origin) |
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| 166 | CS = contourf(x_data, times, z_data, 10, |
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| 167 | #colors = ('black', 'r', 'g', 'b','r'), |
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| 168 | cmap=cm.bone, |
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| 169 | origin=origin) |
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| 170 | |
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| 171 | #CS2 = contour(x_data, times, z_data, CS.levels[::1], |
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| 172 | # colors = 'r', |
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| 173 | # origin=origin, |
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| 174 | # hold='on') |
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| 175 | |
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| 176 | title(plot_title) |
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| 177 | xlabel(x_label) |
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| 178 | ylabel(y_label) |
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| 179 | |
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| 180 | if break_times is not None and break_xs is not None: |
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| 181 | plot(break_xs, break_times, 'yo') |
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| 182 | |
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| 183 | |
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| 184 | # Make a colorbar for the ContourSet returned by the contourf call. |
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| 185 | cbar = colorbar(CS) |
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| 186 | |
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| 187 | # Add the contour line levels to the colorbar |
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| 188 | cbar.ax.set_ylabel('Froude Number') |
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| 189 | #cbar.add_lines(CS2) |
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| 190 | |
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| 191 | if is_interactive: |
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| 192 | raw_input() # Wait for enter pressed |
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| 193 | |
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| 194 | if save_as is not None: |
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| 195 | savefig(save_as) |
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| 196 | close() #Need to close this plot |
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| 197 | |
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| 198 | def auto_graph_slopes(outputdir_tag, scenarios, is_interactive=False): |
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| 199 | """ |
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| 200 | Used to generate all the stage slope contour graphs of a scenario list |
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| 201 | """ |
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| 202 | plot_type = ".pdf" |
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| 203 | for run_data in scenarios: |
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| 204 | id = run_data['scenario_id'] |
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| 205 | outputdir_name = id + outputdir_tag |
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| 206 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 207 | outputdir_name=outputdir_name) |
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| 208 | end = id + ".csv" |
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| 209 | anuga_break_times = [] |
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| 210 | for break_time in run_data['break_times']: |
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| 211 | anuga_break_times.append( \ |
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| 212 | break_time - run_data['ANUGA_start_time']) |
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| 213 | stage_file = pro_instance.outputdir + "fslope_stage_" + end |
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| 214 | plot_title = "Stage slope " + id + "\n file:" + \ |
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| 215 | outputdir_name + "_slope_stage" + plot_type |
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| 216 | print "Creating ", stage_file |
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| 217 | save_as = pro_instance.plots_dir + sep + \ |
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| 218 | outputdir_name + "_slope_stage" + plot_type |
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| 219 | times, locations, slopes = load_slopes(stage_file) |
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| 220 | #times, slopes = get_band(anuga_break_times[0]-TIME_BORDER, |
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| 221 | # 100, times, slopes, 0) |
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| 222 | #locations, slopes = get_band( |
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| 223 | # min(run_data['break_xs'])- 2*LOCATION_BORDER, |
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| 224 | # 100, locations, slopes, -1) |
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| 225 | graph_contours(times, locations, slopes, |
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| 226 | plot_title=plot_title, |
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| 227 | break_xs=run_data['break_xs'], |
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| 228 | break_times=anuga_break_times, |
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| 229 | save_as=save_as, |
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| 230 | is_interactive=is_interactive) |
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| 231 | |
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| 232 | def auto_graph_froudes(outputdir_tag, scenarios, is_interactive=False): |
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| 233 | """ |
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| 234 | Used to generate all the Froude number contour graphs of a scenario list |
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| 235 | """ |
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| 236 | |
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| 237 | plot_type = ".pdf" |
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| 238 | |
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| 239 | for run_data in scenarios: |
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| 240 | id = run_data['scenario_id'] |
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| 241 | outputdir_name = id + outputdir_tag |
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| 242 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 243 | outputdir_name=outputdir_name) |
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| 244 | end = id + ".csv" |
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| 245 | anuga_break_times = [] |
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| 246 | for break_time in run_data['break_times']: |
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| 247 | anuga_break_times.append( \ |
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| 248 | break_time - run_data['ANUGA_start_time']) |
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| 249 | plot_title = "Froude Number" + id + "\n file:" + \ |
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| 250 | outputdir_name + "_froude" + plot_type |
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| 251 | froude_file = pro_instance.outputdir + "fslope_froude_" + end |
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| 252 | print "Creating ", froude_file |
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| 253 | save_as = pro_instance.plots_dir + sep + \ |
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| 254 | outputdir_name + "_froude" + plot_type |
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| 255 | dtimes, locations, sensors = load_sensors(froude_file) |
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| 256 | dtimes, sensors = get_band(anuga_break_times[0]-TIME_BORDER, |
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| 257 | 100, dtimes, sensors, 0) |
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| 258 | locations, sensors = get_band( |
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| 259 | min(run_data['break_xs'])-LOCATION_BORDER, |
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| 260 | 100, locations, sensors, -1) |
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| 261 | #print "dtimes", dtimes |
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| 262 | #print "sensors", sensors |
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| 263 | #times, slope_locations, slopes = load_slopes(stage_file) |
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| 264 | graph_froude(dtimes, locations, sensors, |
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| 265 | plot_title=plot_title, |
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| 266 | break_xs=run_data['break_xs'], |
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| 267 | break_times=anuga_break_times, |
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| 268 | save_as=save_as, |
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| 269 | is_interactive=is_interactive) |
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| 270 | |
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| 271 | def find_froude(times_froude, locations_froude, froudes_array, |
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| 272 | times, locations): |
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| 273 | """ |
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| 274 | interpolate across location to find froude number values |
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| 275 | """ |
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| 276 | |
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| 277 | if len(times) == 0: |
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| 278 | return [] |
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| 279 | time_indexes = searchsorted(times_froude, times) |
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| 280 | location_indexes = searchsorted(locations_froude, locations) |
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| 281 | |
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| 282 | |
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| 283 | assert len(time_indexes) == len(location_indexes) |
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| 284 | |
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| 285 | froudes = [] |
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| 286 | for time_i, loc_i, time, location in map(None, time_indexes, |
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| 287 | location_indexes, |
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| 288 | times, locations): |
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| 289 | # the time values should be the same |
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| 290 | assert times_froude[time_i] == time |
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| 291 | |
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| 292 | # The distance value should be half way between the froude locations |
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| 293 | midpoint = locations_froude[loc_i-1] + \ |
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| 294 | (locations_froude[loc_i]-locations_froude[loc_i-1])*0.5 |
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| 295 | #print "location", location |
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| 296 | #print "midpoint", midpoint |
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| 297 | assert location == midpoint |
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| 298 | froude = froudes_array[time_i, loc_i-1] + \ |
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| 299 | (froudes_array[time_i, loc_i]- \ |
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| 300 | froudes_array[time_i, loc_i-1])*0.5 |
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| 301 | froudes.append(froude) |
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| 302 | |
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| 303 | return froudes |
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| 304 | |
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| 305 | def auto_find_min_slopes(slope_tag, outputdir_tag, scenarios): |
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| 306 | """ |
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| 307 | Given stage and froude wrt time and location csv files, |
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| 308 | find the waves and get the froude number and stage slope |
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| 309 | at the wave face. |
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| 310 | |
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| 311 | For each wave write a csv file giving the location, stage slope, time and |
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| 312 | froude number. |
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| 313 | """ |
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| 314 | |
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| 315 | for run_data in scenarios: |
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| 316 | id = run_data['scenario_id'] |
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| 317 | outputdir_name = id + outputdir_tag |
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| 318 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 319 | outputdir_name=outputdir_name) |
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| 320 | end = id + ".csv" |
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| 321 | anuga_break_times = [] |
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| 322 | for break_time in run_data['break_times']: |
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| 323 | anuga_break_times.append( \ |
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| 324 | break_time - run_data['ANUGA_start_time']) |
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| 325 | |
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| 326 | stage_file = pro_instance.outputdir + slope_tag + "slope_stage_" + end |
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| 327 | froude_file = pro_instance.outputdir + slope_tag + "slope_froude_" + \ |
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| 328 | end |
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| 329 | |
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| 330 | times, slope_locations, slopes = load_slopes(stage_file) |
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| 331 | #print "slope_locations", slope_locations |
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| 332 | times_froude, locations_froude, froudes_a = load_sensors(froude_file) |
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| 333 | #print "locations_froude", locations_froude |
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| 334 | waves = find_min_slopes(times, slope_locations, slopes, |
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| 335 | anuga_break_times, |
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| 336 | run_data['band_offset']) |
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| 337 | |
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| 338 | # write the wave info here |
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| 339 | # and find the froude values |
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| 340 | for i, wave in enumerate(waves): |
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| 341 | |
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| 342 | id = "wave_" + str(i) |
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| 343 | wave_file = stage_file[:-4] + '_'+ id + ".csv" |
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| 344 | print "wave_file", wave_file |
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| 345 | froudes = find_froude(times_froude, locations_froude, |
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| 346 | froudes_a, wave[TIME_STR], |
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| 347 | slope_locations) |
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| 348 | wave_writer = writer(file(wave_file, "wb")) |
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| 349 | wave_writer.writerow(["x location", "min slope", "Time", "Froude"]) |
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| 350 | wave_writer.writerows(map(None, |
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| 351 | slope_locations, |
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| 352 | wave[SLOPE_STR], |
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| 353 | wave[TIME_STR], |
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| 354 | froudes)) |
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| 355 | |
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| 356 | def calc_wave_file_min_slope_max_froude(slope_tag, outputdir_tag, scenarios): |
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| 357 | """ |
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| 358 | Calc the min slope and max froude number in the wave files |
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| 359 | Used so all graphs have the same axis. |
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| 360 | """ |
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| 361 | min_slope = 0 |
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| 362 | max_froude = 0 |
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| 363 | |
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| 364 | for run_data in scenarios: |
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| 365 | for wave_file, save_as, wave_number in Get_file_name( |
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| 366 | run_data, outputdir_tag, slope_tag): |
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| 367 | simulation, _ = csv2dict(wave_file) |
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| 368 | slope = [float(x) for x in simulation['min slope']] |
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| 369 | froude = [float(x) for x in simulation['Froude']] |
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| 370 | |
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| 371 | min_slope = min(min(slope), min_slope) |
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| 372 | |
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| 373 | max_froude = max(max(froude), max_froude) |
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| 374 | |
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| 375 | |
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| 376 | return min_slope, max_froude |
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| 377 | |
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| 378 | class Get_file_name: |
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| 379 | """ |
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| 380 | Used to make the file names, and workout the wave number. |
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| 381 | """ |
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| 382 | |
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| 383 | def __init__(self, run_data, outputdir_tag, slope_tag): |
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| 384 | |
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| 385 | self.plot_type = ".pdf" |
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| 386 | # The scenario data |
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| 387 | id = run_data['scenario_id'] |
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| 388 | |
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| 389 | self.outputdir_name = id + outputdir_tag |
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| 390 | self.pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 391 | outputdir_name=self.outputdir_name) |
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| 392 | self.wave_number = -1 |
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| 393 | self.max_waves = len(run_data['break_type']) |
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| 394 | self.slope_tag = slope_tag |
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| 395 | self.end = id + ".csv" |
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| 396 | |
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| 397 | def next(self): |
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| 398 | self.wave_number += 1 |
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| 399 | if self.wave_number >= self.max_waves: raise StopIteration |
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| 400 | wave_tag = "wave_" + str(self.wave_number) |
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| 401 | stage_file = self.pro_instance.outputdir + self.slope_tag + \ |
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| 402 | "slope_stage_" + self.end |
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| 403 | wave_file = stage_file[:-4] + '_'+ wave_tag + ".csv" |
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| 404 | save_as = self.pro_instance.plots_dir + sep + \ |
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| 405 | self.outputdir_name + "_" + wave_tag + self.plot_type |
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| 406 | return wave_file, save_as, self.wave_number |
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| 407 | |
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| 408 | def __iter__(self): |
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| 409 | return self |
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| 410 | |
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| 411 | |
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| 412 | |
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| 413 | |
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| 414 | def auto_plot_froude_slopes(slope_tag, outputdir_tag, scenarios): |
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| 415 | """ |
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| 416 | Used to generate all the Froude number, stage slope, time graphs |
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| 417 | of a scenario list |
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| 418 | """ |
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| 419 | |
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| 420 | slope_min, froude_max = calc_wave_file_min_slope_max_froude( |
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| 421 | slope_tag, outputdir_tag, scenarios) |
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| 422 | |
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| 423 | |
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| 424 | for run_data in scenarios: |
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| 425 | assert len(run_data['break_times']) == len(run_data['break_xs']) |
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| 426 | assert len(run_data['break_times']) == len(run_data['break_type']) |
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| 427 | |
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| 428 | anuga_break_times = [] |
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| 429 | for break_time in run_data['break_times']: |
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| 430 | anuga_break_times.append( \ |
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| 431 | break_time - run_data['ANUGA_start_time']) |
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| 432 | |
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| 433 | for wave_file, save_as, wave_number in Get_file_name( |
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| 434 | run_data, outputdir_tag, slope_tag): |
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| 435 | print "wave_file", wave_file |
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| 436 | break_type = run_data['break_type'][wave_number] |
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| 437 | plot_title = run_data['scenario_id'] + \ |
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| 438 | ' Wave: ' + str(wave_number) + \ |
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| 439 | ' Break Type: ' + break_type + '\n' + \ |
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| 440 | 'File: ' + wave_file[34:] # not good! |
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| 441 | plot_foude_slope_stage(wave_file, |
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| 442 | anuga_break_times[wave_number], |
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| 443 | run_data['break_xs'][wave_number], |
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| 444 | plot_title=plot_title, |
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| 445 | break_type=break_type, |
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| 446 | save_as=save_as, |
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| 447 | is_interactive=False, |
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| 448 | froude_min=0, |
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| 449 | froude_max=froude_max, |
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| 450 | slope_min=slope_min, |
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| 451 | slope_max=0) |
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| 452 | |
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| 453 | |
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| 454 | |
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| 455 | def gauges_for_slope(slope_tag, outputdir_tag, scenarios): |
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| 456 | """ |
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| 457 | This is used to create a stage file, using gauges relivent to |
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| 458 | finding a slope. |
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| 459 | |
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| 460 | It also create's a frounde file. |
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| 461 | """ |
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| 462 | dx = 0.005 |
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| 463 | for run_data in scenarios: |
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| 464 | point_x = arange(run_data['start_slope_x'], |
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| 465 | run_data['finish_slope_x'], |
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| 466 | dx).tolist() |
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| 467 | flume_y_middle = 0.0 |
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| 468 | points = [] |
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| 469 | for gauge_x in point_x: |
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| 470 | points.append([gauge_x, flume_y_middle]) |
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| 471 | id = run_data['scenario_id'] |
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| 472 | |
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| 473 | basename = 'zz_' + run_data['scenario_id'] |
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| 474 | outputdir_name = id + outputdir_tag |
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| 475 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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| 476 | outputdir_name=outputdir_name) |
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| 477 | end = id + ".csv" |
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| 478 | interpolate_sww2csv( \ |
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| 479 | pro_instance.outputdir + basename +".sww", |
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| 480 | points, |
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| 481 | pro_instance.outputdir + slope_tag + "slope_depth_" + end, |
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| 482 | pro_instance.outputdir + slope_tag + "slope_velocity_x_" + end, |
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| 483 | pro_instance.outputdir + slope_tag + "slope_velocity_y_" + end, |
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| 484 | pro_instance.outputdir + slope_tag + "slope_stage_" + end, |
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| 485 | pro_instance.outputdir + slope_tag + "slope_froude_" + end, |
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| 486 | time_thinning=1) |
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| 487 | |
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| 488 | def find_min_slopes(times, slope_locations, slopes, |
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| 489 | anuga_break_times, band_offset): |
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| 490 | """ |
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| 491 | |
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| 492 | """ |
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| 493 | bands = break_times2bands(anuga_break_times, band_offset) |
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| 494 | |
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| 495 | waves = [] |
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| 496 | for i,_ in enumerate(bands[0:-1]): |
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| 497 | max_q, max_q_times = get_min_in_band(bands[i], bands[i+1], |
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| 498 | times, slopes) |
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| 499 | waves.append({SLOPE_STR:max_q, TIME_STR:max_q_times}) |
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| 500 | return waves |
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| 501 | |
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| 502 | |
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| 503 | def get_band(min, max, vector, quantity_array, axis): |
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| 504 | """ |
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| 505 | Return a band of vector and quantity, within (not including) the |
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| 506 | min, max. |
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| 507 | |
|---|
| 508 | For a time band, set the axis to 0. |
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| 509 | For a location band, set the axis to -1. |
|---|
| 510 | |
|---|
| 511 | """ |
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| 512 | |
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| 513 | SMALL_MIN = -1e10 # Not that small, but small enough |
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| 514 | vector = ensure_numeric(vector) |
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| 515 | quantity_array = ensure_numeric(quantity_array) |
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| 516 | |
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| 517 | assert min > SMALL_MIN |
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| 518 | no_maxs = where(less(vector,max), vector, SMALL_MIN) |
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| 519 | #print "no_maxs", no_maxs |
|---|
| 520 | band_condition = greater(no_maxs, min) |
|---|
| 521 | band_vector = compress(band_condition, vector, axis=axis) |
|---|
| 522 | #print "band_time", band_time |
|---|
| 523 | #print "quantity_array", quantity_array.shape |
|---|
| 524 | band_quantity = compress(band_condition, quantity_array, axis=axis) |
|---|
| 525 | return band_vector, band_quantity |
|---|
| 526 | |
|---|
| 527 | def get_min_in_band(min_time, max_time, time_vector, quantity_array): |
|---|
| 528 | """ |
|---|
| 529 | given a quantity array, with the 2nd axis being |
|---|
| 530 | time, represented by the time_vector, find the minimum within |
|---|
| 531 | the time band. |
|---|
| 532 | |
|---|
| 533 | Assumes times are positive |
|---|
| 534 | """ |
|---|
| 535 | |
|---|
| 536 | time_vector = ensure_numeric(time_vector) |
|---|
| 537 | quantity_array = ensure_numeric(quantity_array) |
|---|
| 538 | |
|---|
| 539 | band_time, band_quantity = get_band(min_time, max_time, |
|---|
| 540 | time_vector, quantity_array, 0) |
|---|
| 541 | #print "band_quantity",band_quantity |
|---|
| 542 | try: |
|---|
| 543 | max_quantity_indices = argmin(band_quantity, axis=0) |
|---|
| 544 | except: |
|---|
| 545 | #print "time_vector", time_vector |
|---|
| 546 | print "min_time",min_time |
|---|
| 547 | print "max_time", max_time |
|---|
| 548 | return [],[] |
|---|
| 549 | |
|---|
| 550 | #print "max_quantity_indices", max_quantity_indices |
|---|
| 551 | max_quantity_times = choose(max_quantity_indices, band_time) |
|---|
| 552 | #print "max_quantity_times", max_quantity_times |
|---|
| 553 | max_quantities = choose(max_quantity_indices, band_quantity) |
|---|
| 554 | #print "max_quantities", max_quantities |
|---|
| 555 | |
|---|
| 556 | return max_quantities, max_quantity_times |
|---|
| 557 | |
|---|
| 558 | def break_times2bands(break_times, band_offset): |
|---|
| 559 | """ |
|---|
| 560 | Break_times is a list of times, ascending. |
|---|
| 561 | bands is a list of times, being the midpoints of break_times, with a min |
|---|
| 562 | and max band added. |
|---|
| 563 | """ |
|---|
| 564 | assert len(break_times)>2 |
|---|
| 565 | |
|---|
| 566 | bands = [] #deepcopy(break_times) |
|---|
| 567 | bands.append(break_times[0]-0.5*(break_times[1]-break_times[0])) |
|---|
| 568 | |
|---|
| 569 | |
|---|
| 570 | for i,break_x in enumerate(break_times[0:-1]): |
|---|
| 571 | bands.append(break_times[i]+0.5*(break_times[i+1]-break_times[i])) |
|---|
| 572 | |
|---|
| 573 | bands.append(break_times[-1]+0.5*(break_times[-1]-break_times[-2])) |
|---|
| 574 | bands = ensure_numeric(bands) |
|---|
| 575 | bands += band_offset |
|---|
| 576 | return bands |
|---|
| 577 | |
|---|
| 578 | def plot_foude_slope_stage(wave_file, |
|---|
| 579 | break_time, |
|---|
| 580 | break_x, |
|---|
| 581 | save_as=None, |
|---|
| 582 | plot_title="", |
|---|
| 583 | is_interactive=False, |
|---|
| 584 | break_type="", |
|---|
| 585 | froude_min=None, |
|---|
| 586 | froude_max=None, |
|---|
| 587 | slope_min=None, |
|---|
| 588 | slope_max=None): |
|---|
| 589 | """ |
|---|
| 590 | """ |
|---|
| 591 | from pylab import ion, plot, xlabel, ylabel, close, legend, \ |
|---|
| 592 | savefig, title, axis, setp, subplot, grid, axvspan |
|---|
| 593 | from anuga.shallow_water.data_manager import csv2dict |
|---|
| 594 | |
|---|
| 595 | |
|---|
| 596 | |
|---|
| 597 | # Load in the csv files and convert info from strings to floats |
|---|
| 598 | simulation, _ = csv2dict(wave_file) |
|---|
| 599 | location = [float(x) for x in simulation['x location']] |
|---|
| 600 | slope = [float(x) for x in simulation['min slope']] |
|---|
| 601 | time = [float(x) for x in simulation['Time']] |
|---|
| 602 | froude = [float(x) for x in simulation['Froude']] |
|---|
| 603 | |
|---|
| 604 | min_location = min(location) |
|---|
| 605 | max_location = max(location) |
|---|
| 606 | |
|---|
| 607 | if is_interactive: |
|---|
| 608 | ion() |
|---|
| 609 | # The upper subplot |
|---|
| 610 | subplot(311) |
|---|
| 611 | l_froude = plot(location, froude) |
|---|
| 612 | #setp(l_froude, color='r') |
|---|
| 613 | |
|---|
| 614 | # Add axis stuff |
|---|
| 615 | title(plot_title) |
|---|
| 616 | y_label = "Froude Number" |
|---|
| 617 | ylabel(y_label) |
|---|
| 618 | grid(True) |
|---|
| 619 | axvspan(break_x-0.001,break_x+0.001, facecolor='g') |
|---|
| 620 | if froude_min is not None and froude_max is not None: |
|---|
| 621 | axis(ymin=froude_min, ymax=froude_max) |
|---|
| 622 | |
|---|
| 623 | # The slope subplot |
|---|
| 624 | subplot(312) |
|---|
| 625 | l_slope = plot(location, slope) |
|---|
| 626 | setp(l_slope, color='r') |
|---|
| 627 | |
|---|
| 628 | # Add axis stuff and legend |
|---|
| 629 | x_label = "X location, m" |
|---|
| 630 | y_label = "Stage slope" |
|---|
| 631 | #xlabel(x_label) |
|---|
| 632 | ylabel(y_label) |
|---|
| 633 | grid(True) |
|---|
| 634 | axvspan(break_x-0.001,break_x+0.001, facecolor='g') |
|---|
| 635 | if slope_min is not None and slope_max is not None: |
|---|
| 636 | axis(ymin=slope_min, ymax=slope_max ) |
|---|
| 637 | |
|---|
| 638 | # The time, x location subplot |
|---|
| 639 | subplot(313) |
|---|
| 640 | l_time = plot(location, time) |
|---|
| 641 | setp(l_time, color='g') |
|---|
| 642 | #print "break_x", break_x |
|---|
| 643 | #print "break_time", break_time |
|---|
| 644 | plot([break_x], [break_time], 'yo') |
|---|
| 645 | #plot([break_x-1], [], 'yo') |
|---|
| 646 | |
|---|
| 647 | # Add axis stuff and legend |
|---|
| 648 | x_label = "X location, m" |
|---|
| 649 | y_label = "time, sec" |
|---|
| 650 | xlabel(x_label) |
|---|
| 651 | ylabel(y_label) |
|---|
| 652 | grid(True) |
|---|
| 653 | |
|---|
| 654 | |
|---|
| 655 | # The order defines the label |
|---|
| 656 | #legend((legend_exp, legend_sim),'upper left') |
|---|
| 657 | #legend(('Wave front'),'upper left') |
|---|
| 658 | |
|---|
| 659 | if is_interactive: |
|---|
| 660 | # Wait for enter pressed |
|---|
| 661 | raw_input() |
|---|
| 662 | |
|---|
| 663 | if save_as is not None: |
|---|
| 664 | savefig(save_as) |
|---|
| 665 | |
|---|
| 666 | #Need to close this plot |
|---|
| 667 | close() |
|---|
| 668 | |
|---|
| 669 | #------------------------------------------------------------- |
|---|
| 670 | if __name__ == "__main__": |
|---|
| 671 | """ |
|---|
| 672 | """ |
|---|
| 673 | from scenarios import scenarios |
|---|
| 674 | #scenarios = [scenarios[0]] |
|---|
| 675 | outputdir_tag = "_good_tri_area_0.01_limiterD" |
|---|
| 676 | outputdir_tag = "_good_lmts_wdth_0.1_z_0.012_ys_0.01_mta_0.0001_F" |
|---|
| 677 | slope_tag = "" |
|---|
| 678 | #outputdir_tag = "_test_limiterC" |
|---|
| 679 | scenarios = [scenarios[4]] # !!!!!!!!!!!!!!!!!!!!!! |
|---|
| 680 | #scenarios = scenarios[4:] # !!!!!!!!!!!!!!!!!!!!!! |
|---|
| 681 | |
|---|
| 682 | #gauges_for_slope(slope_tag, outputdir_tag, scenarios) |
|---|
| 683 | #auto_graph_slopes(outputdir_tag, scenarios) #, is_interactive=True) |
|---|
| 684 | #auto_find_min_slopes(slope_tag, outputdir_tag, scenarios) |
|---|
| 685 | #auto_graph_froudes(outputdir_tag, scenarios) |
|---|
| 686 | auto_plot_froude_slopes(slope_tag, outputdir_tag, scenarios) |
|---|
| 687 | #g = Get_file_name(scenarios[0], outputdir_tag, slope_tag) |
|---|
| 688 | #for wave_file, save_as, wave_number in Get_file_name( |
|---|
| 689 | # scenarios[0], outputdir_tag, slope_tag): |
|---|
| 690 | # print "**************" |
|---|
