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 |
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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 | #slope, _ = csv2dict(file_sim) |
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27 | |
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28 | # Read the depth file |
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29 | dfid = open(quantity_file) |
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30 | lines = dfid.readlines() |
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31 | dfid.close() |
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32 | |
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33 | title = lines.pop(0) |
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34 | n_time = len(lines) |
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35 | n_sensors = len(lines[0].split(','))-1 # -1 to remove time |
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36 | dtimes = zeros(n_time, Float) #Time |
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37 | depths = zeros(n_time, Float) # |
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38 | sensors = zeros((n_time,n_sensors), Float) |
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39 | quantity_locations = title.split(',') #(',') |
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40 | quantity_locations.pop(0) # remove 'time' |
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41 | |
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42 | locations = [float(j.split(':')[0]) for j in quantity_locations] |
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43 | |
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44 | for i, line in enumerate(lines): |
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45 | fields = line.split(',') #(',') |
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46 | fields = [float(j) for j in fields] |
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47 | dtimes[i] = fields[0] |
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48 | sensors[i] = fields[1:] # 1: to remove time |
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49 | |
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50 | #print "dtimes",dtimes |
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51 | #print "locations", locations |
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52 | #print "sensors", sensors |
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53 | return dtimes, locations, sensors |
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54 | |
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55 | def load_slopes(stage_file): |
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56 | """ |
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57 | Finds the slope, wrt distance of a distance, time, quantity csv file. |
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58 | |
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59 | returns the times and slope_locations vectors and the slopes array. |
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60 | """ |
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61 | times, locations, sensors = load_sensors(stage_file) |
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62 | n_slope_locations = len(locations)-1 |
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63 | n_time = len(times) |
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64 | slope_locations = zeros(n_slope_locations, Float) # |
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65 | slopes = zeros((n_time,n_slope_locations), Float) |
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66 | |
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67 | # An array of the sensor spacing values |
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68 | delta_locations = zeros(n_slope_locations, Float) |
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69 | |
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70 | for i in arange(n_slope_locations): |
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71 | slope_locations[i] = (locations[i+1] + locations[i+1])/2. |
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72 | delta_locations[i] = (locations[i+1] - locations[i]) |
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73 | |
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74 | for j in arange(n_time): |
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75 | for i in arange(n_slope_locations): |
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76 | slopes[j,i] = (sensors[j,i+1] - sensors[j,i])/delta_locations[i] |
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77 | |
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78 | return times, slope_locations, slopes |
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79 | |
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80 | |
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81 | def graph_contours(times, x_data, z_data, |
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82 | y_label='Time, seconds', |
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83 | plot_title="slope", |
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84 | x_label='x location, m', |
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85 | save_as=None, |
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86 | is_interactive=False, |
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87 | break_xs=None, |
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88 | break_times=None): |
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89 | # Do not move these imports. Tornado doesn't have pylab |
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90 | from pylab import meshgrid, cm, contourf, contour, ion, plot, xlabel, \ |
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91 | ylabel, close, legend, savefig, title, figure ,colorbar, show , axis |
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92 | |
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93 | origin = 'lower' |
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94 | |
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95 | if is_interactive: |
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96 | ion() |
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97 | |
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98 | # Can't seem to reshape this info once it is in the function |
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99 | CS = contourf(x_data, times, z_data, 10, |
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100 | cmap=cm.bone, |
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101 | origin=origin) |
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102 | |
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103 | #CS2 = contour(x_data, times, z_data, CS.levels[::1], |
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104 | # colors = 'r', |
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105 | # origin=origin, |
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106 | # hold='on') |
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107 | |
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108 | title(plot_title) |
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109 | xlabel(x_label) |
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110 | ylabel(y_label) |
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111 | |
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112 | if break_times is not None and break_xs is not None: |
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113 | plot(break_xs, break_times, 'ro') |
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114 | |
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115 | |
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116 | # Make a colorbar for the ContourSet returned by the contourf call. |
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117 | cbar = colorbar(CS) |
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118 | |
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119 | # Add the contour line levels to the colorbar |
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120 | cbar.ax.set_ylabel('verbosity coefficient') |
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121 | #cbar.add_lines(CS2) |
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122 | |
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123 | if is_interactive: |
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124 | raw_input() # Wait for enter pressed |
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125 | |
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126 | if save_as is not None: |
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127 | savefig(save_as) |
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128 | close() #Need to close this plot |
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129 | |
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130 | def graph_froude(times, x_data, z_data, |
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131 | y_label='Time, seconds', |
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132 | plot_title="Froude Number", |
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133 | x_label='x location, m', |
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134 | save_as=None, |
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135 | is_interactive=False, |
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136 | break_xs=None, |
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137 | break_times=None): |
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138 | # Do not move these imports. Tornado doesn't have pylab |
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139 | from pylab import meshgrid, cm, contourf, contour, ion, plot, xlabel, \ |
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140 | ylabel, close, legend, savefig, title, figure ,colorbar, show , axis |
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141 | |
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142 | origin = 'lower' |
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143 | |
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144 | if is_interactive: |
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145 | ion() |
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146 | |
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147 | # Can't seem to reshape this info once it is in the function |
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148 | CS = contourf(x_data, times, z_data, [-1,0.6,0.8,1,2,4], |
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149 | colors = ('black', 'r', 'g', 'b','r'), |
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150 | #cmap=cm.bone, |
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151 | origin=origin) |
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152 | |
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153 | #CS2 = contour(x_data, times, z_data, CS.levels[::1], |
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154 | # colors = 'r', |
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155 | # origin=origin, |
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156 | # hold='on') |
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157 | |
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158 | title(plot_title) |
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159 | xlabel(x_label) |
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160 | ylabel(y_label) |
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161 | |
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162 | if break_times is not None and break_xs is not None: |
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163 | plot(break_xs, break_times, 'yo') |
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164 | |
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165 | |
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166 | # Make a colorbar for the ContourSet returned by the contourf call. |
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167 | cbar = colorbar(CS) |
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168 | |
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169 | # Add the contour line levels to the colorbar |
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170 | cbar.ax.set_ylabel('verbosity coefficient') |
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171 | #cbar.add_lines(CS2) |
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172 | |
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173 | if is_interactive: |
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174 | raw_input() # Wait for enter pressed |
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175 | |
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176 | if save_as is not None: |
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177 | savefig(save_as) |
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178 | close() #Need to close this plot |
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179 | |
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180 | def auto_graph_slopes(outputdir_tag, scenarios, is_interactive=False): |
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181 | plot_type = ".pdf" |
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182 | for run_data in scenarios: |
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183 | id = run_data['scenario_id'] |
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184 | outputdir_name = id + outputdir_tag |
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185 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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186 | outputdir_name=outputdir_name) |
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187 | end = id + ".csv" |
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188 | anuga_break_times = [] |
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189 | for break_time in run_data['break_times']: |
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190 | anuga_break_times.append( \ |
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191 | break_time - run_data['ANUGA_start_time']) |
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192 | plot_title = "Stage slope " + id |
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193 | stage_file = pro_instance.outputdir + "fslope_stage_" + end |
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194 | save_as = pro_instance.plots_dir + sep + \ |
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195 | outputdir_name + "_slope_stage" + plot_type |
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196 | times, locations, slopes = load_slopes(stage_file) |
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197 | times, slopes = get_band(anuga_break_times[0]-TIME_BORDER, |
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198 | 100, times, slopes, 0) |
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199 | locations, slopes = get_band( |
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200 | run_data['break_xs'][0]- 2*LOCATION_BORDER, |
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201 | 100, locations, slopes, -1) |
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202 | graph_contours(times, locations, slopes, |
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203 | plot_title=plot_title, |
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204 | break_xs=run_data['break_xs'], |
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205 | break_times=anuga_break_times, |
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206 | save_as=save_as, |
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207 | is_interactive=is_interactive) |
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208 | |
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209 | def auto_graph_froudes(outputdir_tag, scenarios, is_interactive=False): |
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210 | |
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211 | plot_type = ".pdf" |
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212 | |
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213 | for run_data in scenarios: |
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214 | id = run_data['scenario_id'] |
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215 | outputdir_name = id + outputdir_tag |
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216 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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217 | outputdir_name=outputdir_name) |
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218 | end = id + ".csv" |
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219 | anuga_break_times = [] |
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220 | for break_time in run_data['break_times']: |
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221 | anuga_break_times.append( \ |
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222 | break_time - run_data['ANUGA_start_time']) |
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223 | plot_title = "Froude Number" + id |
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224 | |
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225 | froude_file = pro_instance.outputdir + "fslope_froude_" + end |
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226 | save_as = pro_instance.plots_dir + sep + \ |
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227 | outputdir_name + "_froude" + plot_type |
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228 | dtimes, locations, sensors = load_sensors(froude_file) |
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229 | dtimes, sensors = get_band(anuga_break_times[0]-TIME_BORDER, |
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230 | 100, dtimes, sensors, 0) |
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231 | locations, sensors = get_band(run_data['break_xs'][0]-LOCATION_BORDER, |
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232 | 100, locations, sensors, -1) |
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233 | #print "dtimes", dtimes |
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234 | #print "sensors", sensors |
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235 | #times, slope_locations, slopes = load_slopes(stage_file) |
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236 | graph_froude(dtimes, locations, sensors, |
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237 | plot_title=plot_title, |
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238 | break_xs=run_data['break_xs'], |
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239 | break_times=anuga_break_times, |
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240 | save_as=save_as, |
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241 | is_interactive=is_interactive) |
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242 | |
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243 | |
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244 | def auto_find_min_slopes(outputdir_tag, scenarios): |
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245 | """ |
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246 | |
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247 | """ |
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248 | |
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249 | for run_data in scenarios: |
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250 | id = run_data['scenario_id'] |
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251 | outputdir_name = id + outputdir_tag |
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252 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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253 | outputdir_name=outputdir_name) |
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254 | end = id + ".csv" |
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255 | anuga_break_times = [] |
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256 | for break_time in run_data['break_times']: |
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257 | anuga_break_times.append( \ |
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258 | break_time - run_data['ANUGA_start_time']) |
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259 | |
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260 | stage_file = pro_instance.outputdir + "fslope_stage_" + end |
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261 | |
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262 | times, slope_locations, slopes = load_slopes(stage_file) |
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263 | waves = find_min_slopes(times, slope_locations, slopes, |
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264 | run_data['break_times'], |
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265 | anuga_break_times, |
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266 | run_data['band_offset']) |
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267 | # write the wave info here |
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268 | # return the keys actually. |
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269 | for wave_key in waves.iterkeys(): |
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270 | wave_file = stage_file[:-3] + '_'+ wave_key + ".csv" |
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271 | print "wave_file", wave_file |
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272 | wave_writer = writer(file(wave_file, "wb")) |
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273 | wave_writer.writerow(["x location", "min slope", "Time"]) |
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274 | wave_writer.writerows(map(None, |
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275 | slope_locations, |
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276 | waves[wave_key][SLOPE_STR], |
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277 | waves[wave_key][TIME_STR])) |
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278 | |
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279 | #wave_writer.close() |
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280 | |
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281 | |
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282 | |
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283 | |
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284 | def gauges_for_slope(outputdir_tag, scenarios): |
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285 | """ |
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286 | This is used to create a stage file, using gauges relivent to |
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287 | finding a slope. |
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288 | """ |
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289 | dx = 0.05 |
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290 | for run_data in scenarios: |
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291 | point_x = arange(run_data['start_slope_x'], |
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292 | run_data['finish_slope_x'], |
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293 | dx).tolist() |
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294 | flume_y_middle = 0.5 |
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295 | points = [] |
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296 | for gauge_x in point_x: |
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297 | points.append([gauge_x, flume_y_middle]) |
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298 | id = run_data['scenario_id'] |
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299 | |
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300 | basename = 'zz_' + run_data['scenario_id'] |
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301 | outputdir_name = id + outputdir_tag |
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302 | pro_instance = project.Project(['data','flumes','Hinwood_2008'], |
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303 | outputdir_name=outputdir_name) |
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304 | end = id + ".csv" |
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305 | interpolate_sww2csv( \ |
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306 | pro_instance.outputdir + basename +".sww", |
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307 | points, |
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308 | pro_instance.outputdir + "fslope_depth_" + end, |
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309 | pro_instance.outputdir + "fslope_velocity_x_" + end, |
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310 | pro_instance.outputdir + "fslope_velocity_y_" + end, |
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311 | pro_instance.outputdir + "fslope_stage_" + end, |
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312 | pro_instance.outputdir + "fslope_froude_" + end, |
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313 | time_thinning=1) |
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314 | |
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315 | def find_min_slopes(times, slope_locations, slopes, |
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316 | break_times, anuga_break_times, band_offset): |
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317 | bands = break_times2bands(break_times, band_offset) |
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318 | |
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319 | waves = {} |
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320 | for i,_ in enumerate(bands[0:-1]): |
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321 | id = "wave " + str(i) |
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322 | max_q, max_q_times = get_min_in_band(bands[i], bands[i+1], |
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323 | times, slopes) |
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324 | waves[id] = {SLOPE_STR:max_q, |
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325 | TIME_STR:max_q_times} |
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326 | return waves |
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327 | |
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328 | |
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329 | def get_band(min, max, vector, quantity_array, axis): |
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330 | """ |
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331 | Return a band of vector and quantity, within (not including) the |
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332 | min, max. |
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333 | |
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334 | For a time band, set the axis to 0. |
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335 | For a location band, set the axis to -1. |
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336 | |
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337 | """ |
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338 | |
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339 | SMALL_MIN = -1e10 # Not that small, but small enough |
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340 | vector = ensure_numeric(vector) |
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341 | quantity_array = ensure_numeric(quantity_array) |
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342 | |
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343 | assert min > SMALL_MIN |
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344 | no_maxs = where(less(vector,max), vector, SMALL_MIN) |
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345 | #print "no_maxs", no_maxs |
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346 | band_condition = greater(no_maxs, min) |
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347 | band_vector = compress(band_condition, vector, axis=axis) |
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348 | #print "band_time", band_time |
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349 | #print "quantity_array", quantity_array.shape |
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350 | band_quantity = compress(band_condition, quantity_array, axis=axis) |
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351 | return band_vector, band_quantity |
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352 | |
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353 | def get_min_in_band(min_time, max_time, time_vector, quantity_array): |
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354 | """ |
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355 | given a quantity array, with the 2nd axis being |
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356 | time, represented by the time_vector, find the minimum within |
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357 | the time band. |
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358 | |
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359 | Assumes times are positive |
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360 | """ |
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361 | |
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362 | time_vector = ensure_numeric(time_vector) |
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363 | quantity_array = ensure_numeric(quantity_array) |
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364 | |
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365 | band_time, band_quantity = get_band(min_time, max_time, |
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366 | time_vector, quantity_array, 0) |
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367 | #print "band_quantity",band_quantity |
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368 | max_quantity_indices = argmin(band_quantity, axis=0) |
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369 | #print "max_quantity_indices", max_quantity_indices |
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370 | max_quantity_times = choose(max_quantity_indices, band_time) |
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371 | #print "max_quantity_times", max_quantity_times |
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372 | max_quantities = choose(max_quantity_indices, band_quantity) |
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373 | #print "max_quantities", max_quantities |
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374 | |
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375 | return max_quantities, max_quantity_times |
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376 | |
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377 | def break_times2bands(break_times, band_offset): |
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378 | """ |
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379 | Break_times is a list of times, ascending. |
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380 | bands is a list of times, being the midpoints of break_times, with a min |
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381 | and max band added. |
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382 | """ |
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383 | assert len(break_times)>2 |
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384 | |
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385 | bands = [] #deepcopy(break_times) |
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386 | bands.append(break_times[0]-0.5*(break_times[1]-break_times[0])) |
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387 | |
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388 | for i,break_x in enumerate(break_times[0:-1]): |
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389 | bands.append(break_times[i]+0.5*(break_times[i+1]-break_times[i])) |
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390 | |
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391 | bands.append(break_times[-1]+0.5*(break_times[-1]-break_times[-2])) |
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392 | bands = ensure_numeric(bands) |
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393 | bands += band_offset |
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394 | return bands |
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395 | |
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396 | #------------------------------------------------------------- |
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397 | if __name__ == "__main__": |
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398 | """ |
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399 | """ |
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400 | from scenarios import scenarios |
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401 | #scenarios = [scenarios[0]] |
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402 | outputdir_tag = "_good_tri_area_0.01_limiterC" |
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403 | #outputdir_tag = "_test_limiterC" |
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404 | #scenarios = [scenarios[0]] # !!!!!!!!!!!!!!!!!!!!!! |
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405 | #gauges_for_slope(outputdir_tag, scenarios) |
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406 | auto_graph_slopes(outputdir_tag, scenarios) #, is_interactive=True) |
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407 | #auto_find_min_slopes(outputdir_tag, scenarios) |
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408 | auto_graph_froudes(outputdir_tag, scenarios) |
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