Thu, 25 Apr 2024 11:14:41 -0500
DualScaling parametrisation
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1 | __precompile__() |
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2 | |
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3 | module PlotResults |
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4 | |
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5 | |
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6 | ######################## |
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7 | # Load external modules |
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8 | ######################## |
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9 | |
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10 | using DelimitedFiles, CSV, DataFrames |
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11 | using PlotlyJS |
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12 | using Colors |
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13 | |
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14 | export fv_plot, ssim_plot, psnr_plot |
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15 | |
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16 | global mystart = 38 |
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17 | global myend = 75 |
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18 | |
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19 | function fv_plot(name :: String, save_plot::Bool=true) |
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20 | save_path = "./img/$(name)256x256_pdps_known_fv_plot.html" |
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21 | ################################################# |
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22 | orig = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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23 | ################################################# |
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24 | directory_path = "./img/" |
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25 | files = readdir(directory_path) |
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26 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_proximal") && endswith(file, "0.txt"), files) |
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27 | |
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28 | # Define an array of line styles and colors |
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29 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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30 | line_colors = distinguishable_colors(15) |
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31 | |
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32 | for (index,file) in enumerate(filtered_files) |
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33 | filename = directory_path*file |
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34 | #data = readdlm(filename, '\t', skipstart=1) |
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35 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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36 | |
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37 | # Extract the columns you want to plot |
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38 | X = Int64.(data[mystart:myend,:iter]) |
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39 | Y = Float64.(data[mystart:myend, :function_value]) |
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40 | |
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41 | #line_style = line_styles[i] |
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42 | line_color = line_colors[index] |
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43 | # Extract parameters for legend |
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44 | α, τ₀, σ₀ = extract_parameters(filename) |
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45 | |
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46 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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47 | line_color=line_color, line_dash="dot", name="proxi (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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48 | push!(orig, trace) |
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49 | end |
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50 | |
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51 | ##################################################### |
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52 | identity = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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53 | ##################################################### |
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54 | directory_path = "./img/" |
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55 | files = readdir(directory_path) |
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56 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_primalonly") && endswith(file, "0.txt"), files) |
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57 | |
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58 | # Define an array of line styles and colors |
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59 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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60 | line_colors = distinguishable_colors(15) |
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61 | |
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62 | for (index,file) in enumerate(filtered_files) |
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63 | filename = directory_path*file |
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64 | #data = readdlm(filename, '\t', skipstart=1) |
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65 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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66 | |
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67 | # Extract the columns you want to plot |
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68 | X = Int64.(data[mystart:myend,:iter]) |
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69 | Y = Float64.(data[mystart:myend, :function_value]) |
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70 | |
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71 | #line_style = line_styles[i] |
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72 | line_color = line_colors[index] |
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73 | # Extract parameters for legend |
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74 | α, τ₀, σ₀ = extract_parameters(filename) |
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75 | |
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76 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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77 | line_color=line_color, line_dash="dashdot", name="primo (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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78 | push!(identity, trace) |
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79 | end |
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80 | |
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81 | |
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82 | ##################################################### |
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83 | adhoc = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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84 | ##################################################### |
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85 | directory_path = "./img/" |
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86 | files = readdir(directory_path) |
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87 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_greedy") && endswith(file, "0.txt"), files) |
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88 | |
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89 | # Define an array of line styles and colors |
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90 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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91 | line_colors = distinguishable_colors(15) |
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92 | |
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93 | for (index,file) in enumerate(filtered_files) |
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94 | filename = directory_path*file |
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95 | #data = readdlm(filename, '\t', skipstart=1) |
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96 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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97 | |
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98 | # Extract the columns you want to plot |
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99 | X = Int64.(data[mystart:myend,:iter]) |
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100 | Y = Float64.(data[mystart:myend, :function_value]) |
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101 | |
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102 | #line_style = line_styles[i] |
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103 | line_color = line_colors[index] |
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104 | # Extract parameters for legend |
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105 | α, τ₀, σ₀ = extract_parameters(filename) |
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106 | |
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107 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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108 | line_color=line_color, line_dash="dash", name="greed (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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109 | push!(identity, trace) |
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110 | end |
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111 | |
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112 | |
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113 | ##################################################### |
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114 | rotation = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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115 | ##################################################### |
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116 | directory_path = "./img/" |
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117 | files = readdir(directory_path) |
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118 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_rotation") && endswith(file, "0.txt"), files) |
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119 | |
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120 | # Define an array of line styles and colors |
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121 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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122 | line_colors = distinguishable_colors(15) |
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123 | |
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124 | for (index,file) in enumerate(filtered_files) |
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125 | filename = directory_path*file |
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126 | #data = readdlm(filename, '\t', skipstart=1) |
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127 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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128 | |
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129 | # Extract the columns you want to plot |
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130 | X = Int64.(data[mystart:myend,:iter]) |
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131 | Y = Float64.(data[mystart:myend, :function_value]) |
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132 | |
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133 | #line_style = line_styles[i] |
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134 | line_color = line_colors[index] |
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135 | # Extract parameters for legend |
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136 | α, τ₀, σ₀ = extract_parameters(filename) |
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137 | |
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138 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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139 | line_color=line_color, line_dash="longdashdot", name="rotat (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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140 | push!(identity, trace) |
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141 | end |
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142 | |
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143 | |
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144 | ##################################################### |
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145 | affine = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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146 | ##################################################### |
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147 | directory_path = "./img/" |
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148 | files = readdir(directory_path) |
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149 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_dualscaling") && endswith(file, "0.txt"), files) |
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150 | |
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151 | # Define an array of line styles and colors |
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152 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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153 | line_colors = distinguishable_colors(15) |
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154 | |
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155 | for (index,file) in enumerate(filtered_files) |
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156 | filename = directory_path*file |
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157 | #data = readdlm(filename, '\t', skipstart=1) |
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158 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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159 | |
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160 | # Extract the columns you want to plot |
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161 | X = Int64.(data[mystart:myend,:iter]) |
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162 | Y = Float64.(data[mystart:myend, :function_value]) |
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163 | |
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164 | #line_style = line_styles[i] |
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165 | line_color = line_colors[index] |
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166 | # Extract parameters for legend |
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167 | α, τ₀, σ₀ = extract_parameters(filename) |
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168 | |
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169 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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170 | line_color=line_color, line_dash="solid", name="dusca (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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171 | push!(identity, trace) |
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172 | end |
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173 | |
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174 | ##################################################### |
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175 | zerodual = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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176 | ##################################################### |
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177 | directory_path = "./img/" |
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178 | files = readdir(directory_path) |
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179 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_zerodual") && endswith(file, "0.txt"), files) |
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180 | |
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181 | # Define an array of line styles and colors |
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182 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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183 | line_colors = distinguishable_colors(15) |
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184 | |
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185 | for (index,file) in enumerate(filtered_files) |
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186 | filename = directory_path*file |
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187 | #data = readdlm(filename, '\t', skipstart=1) |
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188 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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189 | |
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190 | # Extract the columns you want to plot |
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191 | X = Int64.(data[mystart:myend,:iter]) |
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192 | Y = Float64.(data[mystart:myend, :function_value]) |
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193 | |
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194 | #line_style = line_styles[i] |
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195 | line_color = line_colors[index] |
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196 | # Extract parameters for legend |
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197 | α, τ₀, σ₀ = extract_parameters(filename) |
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198 | |
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199 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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200 | line_color=line_color, line_dash="longdash", name="zerod (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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201 | push!(identity, trace) |
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202 | end |
25 | 203 | |
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204 | layout = Layout(legend_title_text="Function values") # Set legend title |
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205 | |
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206 | if save_plot && !isempty(save_path) |
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207 | plotlyjs = plot([orig;identity;adhoc;rotation;affine;zerodual], layout) |
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208 | open(save_path, "w") do io |
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209 | PlotlyBase.to_html(io, plotlyjs.plot) |
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210 | end |
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211 | elseif save_plot |
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212 | println("Please provide a valid save path.") |
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213 | end |
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214 | |
25 | 215 | return plot([orig;identity;adhoc;rotation;affine;zerodual],layout) |
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216 | end |
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217 | |
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218 | |
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219 | ######################################################### |
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220 | # FUNCTION FOR SSIM |
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221 | ######################################################### |
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222 | function ssim_plot(name :: String, save_plot::Bool=true) |
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223 | save_path = "./img/$(name)256x256_pdps_known_ssim_plot.html" |
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224 | ################################################# |
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225 | orig = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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226 | ################################################# |
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227 | directory_path = "./img/" |
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228 | files = readdir(directory_path) |
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229 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_proximal") && endswith(file, "0.txt"), files) |
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230 | |
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231 | # Define an array of line styles and colors |
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232 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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233 | line_colors = distinguishable_colors(15) |
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234 | |
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235 | for (index,file) in enumerate(filtered_files) |
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236 | filename = directory_path*file |
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237 | #data = readdlm(filename, '\t', skipstart=1) |
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238 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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239 | |
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240 | # Extract the columns you want to plot |
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241 | X = Int64.(data[mystart:myend,:iter]) |
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242 | Y = Float64.(data[mystart:myend, :ssim]) |
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243 | |
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244 | #line_style = line_styles[i] |
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245 | line_color = line_colors[index] |
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246 | # Extract parameters for legend |
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247 | α, τ₀, σ₀ = extract_parameters(filename) |
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248 | |
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249 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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250 | line_color=line_color, line_dash="dot", name="proxi (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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251 | push!(orig, trace) |
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252 | end |
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253 | |
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254 | ##################################################### |
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255 | identity = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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256 | ##################################################### |
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257 | directory_path = "./img/" |
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258 | files = readdir(directory_path) |
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259 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_primalonly") && endswith(file, "0.txt"), files) |
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260 | |
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261 | # Define an array of line styles and colors |
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262 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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263 | line_colors = distinguishable_colors(15) |
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264 | |
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265 | for (index,file) in enumerate(filtered_files) |
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266 | filename = directory_path*file |
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267 | #data = readdlm(filename, '\t', skipstart=1) |
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268 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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269 | |
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270 | # Extract the columns you want to plot |
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271 | X = Int64.(data[mystart:myend,:iter]) |
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272 | Y = Float64.(data[mystart:myend, :ssim]) |
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273 | |
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274 | #line_style = line_styles[i] |
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275 | line_color = line_colors[index] |
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276 | # Extract parameters for legend |
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277 | α, τ₀, σ₀ = extract_parameters(filename) |
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278 | |
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279 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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280 | line_color=line_color, line_dash="dashdot", name="primo (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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281 | push!(identity, trace) |
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282 | end |
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283 | |
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284 | |
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285 | ##################################################### |
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286 | adhoc = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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287 | ##################################################### |
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288 | directory_path = "./img/" |
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289 | files = readdir(directory_path) |
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290 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_greedy") && endswith(file, "0.txt"), files) |
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291 | |
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292 | # Define an array of line styles and colors |
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293 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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294 | line_colors = distinguishable_colors(15) |
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295 | |
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296 | for (index,file) in enumerate(filtered_files) |
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297 | filename = directory_path*file |
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298 | #data = readdlm(filename, '\t', skipstart=1) |
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299 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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300 | |
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301 | # Extract the columns you want to plot |
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302 | X = Int64.(data[mystart:myend,:iter]) |
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303 | Y = Float64.(data[mystart:myend, :ssim]) |
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304 | |
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305 | #line_style = line_styles[i] |
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306 | line_color = line_colors[index] |
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307 | # Extract parameters for legend |
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308 | α, τ₀, σ₀ = extract_parameters(filename) |
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309 | |
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310 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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311 | line_color=line_color, line_dash="dash", name="greed (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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312 | push!(identity, trace) |
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313 | end |
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314 | |
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315 | |
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316 | ##################################################### |
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317 | rotation = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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318 | ##################################################### |
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319 | directory_path = "./img/" |
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320 | files = readdir(directory_path) |
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321 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_rotation") && endswith(file, "0.txt"), files) |
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322 | |
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323 | # Define an array of line styles and colors |
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324 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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325 | line_colors = distinguishable_colors(15) |
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326 | |
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327 | for (index,file) in enumerate(filtered_files) |
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328 | filename = directory_path*file |
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329 | #data = readdlm(filename, '\t', skipstart=1) |
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330 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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331 | |
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332 | # Extract the columns you want to plot |
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333 | X = Int64.(data[mystart:myend,:iter]) |
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334 | Y = Float64.(data[mystart:myend, :ssim]) |
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335 | |
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336 | #line_style = line_styles[i] |
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337 | line_color = line_colors[index] |
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338 | # Extract parameters for legend |
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339 | α, τ₀, σ₀ = extract_parameters(filename) |
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340 | |
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341 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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342 | line_color=line_color, line_dash="longdashdot", name="rotat (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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343 | push!(identity, trace) |
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344 | end |
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345 | |
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346 | |
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347 | ##################################################### |
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348 | affine = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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349 | ##################################################### |
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350 | directory_path = "./img/" |
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351 | files = readdir(directory_path) |
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352 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_dualscaling") && endswith(file, "0.txt"), files) |
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353 | |
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354 | # Define an array of line styles and colors |
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355 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
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356 | line_colors = distinguishable_colors(15) |
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357 | |
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358 | for (index,file) in enumerate(filtered_files) |
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359 | filename = directory_path*file |
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parents:
diff
changeset
|
360 | #data = readdlm(filename, '\t', skipstart=1) |
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parents:
diff
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|
361 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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parents:
diff
changeset
|
362 | |
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parents:
diff
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|
363 | # Extract the columns you want to plot |
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parents:
diff
changeset
|
364 | X = Int64.(data[mystart:myend,:iter]) |
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parents:
diff
changeset
|
365 | Y = Float64.(data[mystart:myend, :ssim]) |
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parents:
diff
changeset
|
366 | |
7d3a75b875fa
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parents:
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changeset
|
367 | #line_style = line_styles[i] |
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parents:
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|
368 | line_color = line_colors[index] |
28
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diff
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|
369 | # Extract parameters for legend |
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diff
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|
370 | α, τ₀, σ₀ = extract_parameters(filename) |
20
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parents:
diff
changeset
|
371 | |
29
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diff
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|
372 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
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|
373 | line_color=line_color, line_dash="solid", name="dusca (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
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parents:
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|
374 | push!(identity, trace) |
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parents:
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|
375 | end |
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parents:
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changeset
|
376 | |
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|
377 | ##################################################### |
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parents:
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|
378 | zerodual = Vector{GenericTrace{Dict{Symbol, Any}}}() |
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|
379 | ##################################################### |
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parents:
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|
380 | directory_path = "./img/" |
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parents:
diff
changeset
|
381 | files = readdir(directory_path) |
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parents:
diff
changeset
|
382 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_zerodual") && endswith(file, "0.txt"), files) |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
383 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
384 | # Define an array of line styles and colors |
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parents:
diff
changeset
|
385 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
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parents:
25
diff
changeset
|
386 | line_colors = distinguishable_colors(15) |
20
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
387 | |
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parents:
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changeset
|
388 | for (index,file) in enumerate(filtered_files) |
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parents:
diff
changeset
|
389 | filename = directory_path*file |
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parents:
diff
changeset
|
390 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
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parents:
diff
changeset
|
391 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
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parents:
diff
changeset
|
392 | |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
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changeset
|
393 | # Extract the columns you want to plot |
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parents:
diff
changeset
|
394 | X = Int64.(data[mystart:myend,:iter]) |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
395 | Y = Float64.(data[mystart:myend, :ssim]) |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
396 | |
7d3a75b875fa
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parents:
diff
changeset
|
397 | #line_style = line_styles[i] |
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parents:
diff
changeset
|
398 | line_color = line_colors[index] |
28
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
399 | # Extract parameters for legend |
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parents:
25
diff
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|
400 | α, τ₀, σ₀ = extract_parameters(filename) |
20
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
401 | |
29
6a0ca7047f68
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
402 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
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parents:
25
diff
changeset
|
403 | line_color=line_color, line_dash="longdash", name="zerod (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
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parents:
diff
changeset
|
404 | push!(identity, trace) |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
405 | end |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
406 | |
28
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
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|
407 | layout = Layout(yaxis_type="log",legend_title_text="SSIM") # Set legend title |
20
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parents:
diff
changeset
|
408 | |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
409 | if save_plot && !isempty(save_path) |
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parents:
diff
changeset
|
410 | plotlyjs = plot([orig;identity;adhoc;rotation;affine;zerodual], layout) |
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parents:
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|
411 | open(save_path, "w") do io |
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parents:
diff
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|
412 | PlotlyBase.to_html(io, plotlyjs.plot) |
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parents:
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|
413 | end |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
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|
414 | elseif save_plot |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
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|
415 | println("Please provide a valid save path.") |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
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changeset
|
416 | end |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
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|
417 | |
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parents:
diff
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|
418 | return plot([orig;identity;adhoc;rotation;affine;zerodual],layout) |
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parents:
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|
419 | end |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
420 | |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
421 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
422 | |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
423 | ######################################################### |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
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|
424 | # FUNCTION FOR PSNR |
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
425 | ######################################################### |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
426 | function psnr_plot(name :: String, save_plot::Bool=true) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
427 | save_path = "./img/$(name)256x256_pdps_known_psnr_plot.html" |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
428 | ################################################# |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
429 | orig = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
430 | ################################################# |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
431 | directory_path = "./img/" |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
432 | files = readdir(directory_path) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
433 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_proximal") && endswith(file, "0.txt"), files) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
434 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
435 | # Define an array of line styles and colors |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
436 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
437 | line_colors = distinguishable_colors(15) |
20
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
438 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
439 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
440 | filename = directory_path*file |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
441 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
442 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
443 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
444 | # Extract the columns you want to plot |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
445 | X = Int64.(data[mystart:myend,:iter]) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
446 | Y = Float64.(data[mystart:myend, :psnr]) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
447 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
448 | #line_style = line_styles[i] |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
449 | line_color = line_colors[index] |
28
f7c1007f0127
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
450 | # Extract parameters for legend |
f7c1007f0127
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
451 | α, τ₀, σ₀ = extract_parameters(filename) |
20
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
452 | |
29
6a0ca7047f68
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
453 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
f7c1007f0127
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
454 | line_color=line_color, line_dash="dot", name="proxi (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
455 | push!(orig, trace) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
456 | end |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
457 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
458 | ##################################################### |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
459 | identity = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
460 | ##################################################### |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
461 | directory_path = "./img/" |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
462 | files = readdir(directory_path) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
463 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_primalonly") && endswith(file, "0.txt"), files) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
464 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
465 | # Define an array of line styles and colors |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
466 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
467 | line_colors = distinguishable_colors(15) |
20
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
468 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
469 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
470 | filename = directory_path*file |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
471 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
472 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
473 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
474 | # Extract the columns you want to plot |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
475 | X = Int64.(data[mystart:myend,:iter]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
476 | Y = Float64.(data[mystart:myend, :psnr]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
477 | |
7d3a75b875fa
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Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
478 | #line_style = line_styles[i] |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
479 | line_color = line_colors[index] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
480 | # Extract parameters for legend |
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
481 | α, τ₀, σ₀ = extract_parameters(filename) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
482 | |
29
6a0ca7047f68
added new plots and filmstrips
Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
483 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
484 | line_color=line_color, line_dash="dashdot", name="primo (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
485 | push!(identity, trace) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
486 | end |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
487 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
488 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
489 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
490 | adhoc = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
491 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
492 | directory_path = "./img/" |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
493 | files = readdir(directory_path) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
494 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_greedy") && endswith(file, "0.txt"), files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
495 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
496 | # Define an array of line styles and colors |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
497 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
498 | line_colors = distinguishable_colors(15) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
499 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
500 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
501 | filename = directory_path*file |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
502 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
503 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
504 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
505 | # Extract the columns you want to plot |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
506 | X = Int64.(data[mystart:myend,:iter]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
507 | Y = Float64.(data[mystart:myend, :psnr]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
508 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
509 | #line_style = line_styles[i] |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
510 | line_color = line_colors[index] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
511 | # Extract parameters for legend |
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
512 | α, τ₀, σ₀ = extract_parameters(filename) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
513 | |
29
6a0ca7047f68
added new plots and filmstrips
Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
514 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
515 | line_color=line_color, line_dash="dash", name="greed (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
516 | push!(identity, trace) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
517 | end |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
518 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
519 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
520 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
521 | rotation = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
522 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
523 | directory_path = "./img/" |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
524 | files = readdir(directory_path) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
525 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_rotation") && endswith(file, "0.txt"), files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
526 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
527 | # Define an array of line styles and colors |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
528 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
529 | line_colors = distinguishable_colors(15) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
530 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
531 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
532 | filename = directory_path*file |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
533 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
534 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
535 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
536 | # Extract the columns you want to plot |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
537 | X = Int64.(data[mystart:myend,:iter]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
538 | Y = Float64.(data[mystart:myend, :psnr]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
539 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
540 | #line_style = line_styles[i] |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
541 | line_color = line_colors[index] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
542 | # Extract parameters for legend |
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
543 | α, τ₀, σ₀ = extract_parameters(filename) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
544 | |
29
6a0ca7047f68
added new plots and filmstrips
Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
545 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
546 | line_color=line_color, line_dash="longdashdot", name="rotat (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
547 | push!(identity, trace) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
548 | end |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
549 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
550 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
551 | affine = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
552 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
553 | directory_path = "./img/" |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
554 | files = readdir(directory_path) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
555 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_dualscaling") && endswith(file, "0.txt"), files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
556 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
557 | # Define an array of line styles and colors |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
558 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
559 | line_colors = distinguishable_colors(15) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
560 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
561 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
562 | filename = directory_path*file |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
563 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
564 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
565 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
566 | # Extract the columns you want to plot |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
567 | X = Int64.(data[mystart:myend,:iter]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
568 | Y = Float64.(data[mystart:myend, :psnr]) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
569 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
570 | #line_style = line_styles[i] |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
571 | line_color = line_colors[index] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
572 | # Extract parameters for legend |
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
573 | α, τ₀, σ₀ = extract_parameters(filename) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
574 | |
29
6a0ca7047f68
added new plots and filmstrips
Neil Dizon <neil.dizon@helsinki.fi>
parents:
28
diff
changeset
|
575 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
576 | line_color=line_color, line_dash="solid", name="dusca (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
577 | push!(identity, trace) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
578 | end |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
579 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
580 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
581 | zerodual = Vector{GenericTrace{Dict{Symbol, Any}}}() |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
582 | ##################################################### |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
583 | directory_path = "./img/" |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
584 | files = readdir(directory_path) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
585 | filtered_files = filter(file -> startswith(file, "$(name)256x256_pdps_known_zerodual") && endswith(file, "0.txt"), files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
586 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
587 | # Define an array of line styles and colors |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
588 | # line_styles = ["solid", "dash", "dot", "dashdot", "longdash"] |
28
f7c1007f0127
added function to generate table
Neil Dizon <neil.dizon@helsinki.fi>
parents:
25
diff
changeset
|
589 | line_colors = distinguishable_colors(15) |
20
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
590 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
591 | for (index,file) in enumerate(filtered_files) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
592 | filename = directory_path*file |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
593 | #data = readdlm(filename, '\t', skipstart=1) |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
594 | data = CSV.File(filename, delim='\t'; header = 2) |> DataFrame |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
595 | |
7d3a75b875fa
added zero dual predictor for denoising
Neil Dizon <neil.dizon@helsinki.fi>
parents:
diff
changeset
|
596 | # Extract the columns you want to plot |
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597 | X = Int64.(data[mystart:myend,:iter]) |
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598 | Y = Float64.(data[mystart:myend, :psnr]) |
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599 | |
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600 | #line_style = line_styles[i] |
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601 | line_color = line_colors[index] |
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602 | # Extract parameters for legend |
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603 | α, τ₀, σ₀ = extract_parameters(filename) |
20
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604 | |
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605 | trace = PlotlyJS.scatter(;x=X, y=Y, mode="lines", hovertemplate="%{x:.0f},%{y:.3f}", |
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606 | line_color=line_color, line_dash="longdash", name="zerod (α=$α, τ₀=$τ₀, σ₀=$σ₀)") |
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607 | push!(identity, trace) |
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608 | end |
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609 | |
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610 | |
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611 | layout = Layout(yaxis_type="log", legend_title_text="PSNR") # Set legend title |
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612 | |
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613 | if save_plot && !isempty(save_path) |
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614 | plotlyjs = plot([orig;identity;adhoc;rotation;affine; zerodual], layout) |
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615 | open(save_path, "w") do io |
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616 | PlotlyBase.to_html(io, plotlyjs.plot) |
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617 | end |
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618 | elseif save_plot |
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619 | println("Please provide a valid save path.") |
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620 | end |
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621 | |
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622 | return plot([orig;identity;adhoc;rotation;affine;zerodual],layout) |
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623 | end |
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624 | |
28
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625 | ###################### |
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626 | # Parameter extraction |
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627 | ###################### |
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628 | function extract_parameters(filename :: String) |
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629 | # Extracting parameters |
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630 | params_line = readlines(filename)[1] |
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631 | |
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632 | # Split the line by commas and trim each part |
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633 | params_parts = map(strip, split(params_line, ',')) |
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634 | |
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635 | # Initialize variables to store parameter values |
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636 | α_value, τ₀_value, σ₀_value = missing, missing, missing |
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637 | |
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638 | # Look for specific substrings to identify the values of α, τ₀, and σ₀ |
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639 | for param_part in params_parts |
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640 | if contains(param_part, "α = ") |
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641 | α_value = parse(Float64, split(param_part, '=')[2]) |
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642 | elseif contains(param_part, "τ₀ = ") |
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643 | τ₀_value = parse(Float64, split(param_part, '=')[2]) |
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644 | elseif contains(param_part, "σ₀ = ") |
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645 | σ₀_value = parse(Float64, split(param_part, '=')[2]) |
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646 | end |
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647 | end |
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648 | |
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649 | # Assign the values to α, τ₀, and σ₀ |
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650 | α = α_value |
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651 | τ₀ = τ₀_value |
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652 | σ₀ = σ₀_value |
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653 | return α, τ₀, σ₀ |
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654 | end |
20
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655 | |
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656 | end # Module |