Plot Features

Collapse Tensorflow Coupon Figure

Features Extracted from the Tensorflow Coupon Network

Features Extracted from the Tensorflow Coupon Network

Collapse Pytorch Nested Cylinder Figure

Features Extracted from the Pytorch Nested Cylinder Network

Features Extracted from the Pytorch Nested Cylinder Network


Code Documentation

Plots one or multiple features extracted from a given layer over the model’s input field

  • Can plot all features from a layer on the same plot (-T Grid)

  • Can plot all features from a layer on their own plots (-T All)

  • Can plot some features from a layer on their own plots (-T # #)

Saves all features to a .npz file.

Input Line for TF Coupon Models: python plot_features.py -P tensorflow -E coupon -M ../examples/tf_coupon/trained_pRad2TePla_model.h5 -IF pRad -IN ../examples/tf_coupon/data/r60um_tpl112_complete_idx00110.npz -DF ../examples/tf_coupon/coupon_design_file.csv -L activation_15 -T Grid -NM ft01 -S ../examples/tf_coupon/figures/

Input Line for PYT Nested Cylinder Models: python plot_features.py -P pytorch -E nestedcylinder -M ../examples/pyt_nestedcyl/trained_rho2PTW_model.pth -IF rho -IN ../examples/pyt_nestedcyl/data/nc231213_Sn_id0643_pvi_idx00112.npz -DF ../examples/pyt_nestedcyl/nestedcyl_design_file.csv -L interp_module.interpActivations.10 -T Grid -NM ft01 -S ../examples/pyt_nestedcyl/figures/

Arguments

Plots one or multiple features extracted from a given layer over the model’s input field

usage: python plot_features.py [-h] [--PACKAGE] [--EXPERIMENT] [--MODEL]
                               [--INPUT_FIELD] [--INPUT_NPZ] [--DESIGN_FILE]
                               [--PRINT_LAYERS] [--PRINT_FEATURES]
                               [--PRINT_FIELDS] [--LAYER] [--FEATURES  [...]]
                               [--MAT_NORM] [--ALPHA1] [--ALPHA2] [--COLOR1]
                               [--COLOR2] [--SAVE_FIG]

Named Arguments

--PACKAGE, -P

Possible choices: tensorflow, pytorch

Which python package was used to create the model

Default: “tensorflow”

--EXPERIMENT, -E

Possible choices: coupon, nestedcylinder

Which experiment the model was trained on

Default: “coupon”

--MODEL, -M

Model file

Default: “../examples/tf_coupon/trained_pRad2TePla_model.h5”

--INPUT_FIELD, -IF

The radiographic/hydrodynamic field the model is trained on

Default: “pRad”

--INPUT_NPZ, -IN

The .npz file with an input image to the model

Default: “../examples/tf_coupon/data/r60um_tpl112_complete_idx00110.npz”

--DESIGN_FILE, -DF

The .csv file with master design study parameters

Default: “../examples/tf_coupon/coupon_design_file.csv”

--PRINT_LAYERS, -PL

Prints list of layer names in a model (passed with -M) and quits program

Default: False

--PRINT_FEATURES, -PT

Prints number of features extracted by a layer (passed with -L) and quits program

Default: False

--PRINT_FIELDS, -PF

Prints list of hydrodynamic/radiographic fields present in a given .npz file (passed with -IN) and quits program

Default: False

--LAYER, -L

Name of model layer that features will be extracted from

Default: “None”

--FEATURES, -T

List of features to include; “Grid” plots all features in one figure using subplots; “All” plots all features each in a new figure; A list of integers can be passed to plot those features each in a new figure. Integer convention starts at 1.

Default: [‘Grid’]

--MAT_NORM, -NM

Possible choices: ft01, all01, none

How the extracted features will be normalized, resulting in a scaled matrix; “ft01” normalizes by the min and max of each feature separately; “all01” normalizes by the min and max of all extracted features; “none” does not normalize features.

Default: “ft01”

--ALPHA1, -A1

Opacity of colormap at value 0

Default: 0.25

--ALPHA2, -A2

Opacity of colormap at value 1

Default: 1.0

--COLOR1, -C1

Possible choices: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgreen, darkgrey, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, green, greenyellow, grey, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgreen, lightgrey, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, rebeccapurple, red, rosybrown, royalblue, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen

Color of colormap at value 0; Choose from matplotlib CSS4 color list.

Default: “yellow”

--COLOR2, -C2

Possible choices: aliceblue, antiquewhite, aqua, aquamarine, azure, beige, bisque, black, blanchedalmond, blue, blueviolet, brown, burlywood, cadetblue, chartreuse, chocolate, coral, cornflowerblue, cornsilk, crimson, cyan, darkblue, darkcyan, darkgoldenrod, darkgray, darkgreen, darkgrey, darkkhaki, darkmagenta, darkolivegreen, darkorange, darkorchid, darkred, darksalmon, darkseagreen, darkslateblue, darkslategray, darkslategrey, darkturquoise, darkviolet, deeppink, deepskyblue, dimgray, dimgrey, dodgerblue, firebrick, floralwhite, forestgreen, fuchsia, gainsboro, ghostwhite, gold, goldenrod, gray, green, greenyellow, grey, honeydew, hotpink, indianred, indigo, ivory, khaki, lavender, lavenderblush, lawngreen, lemonchiffon, lightblue, lightcoral, lightcyan, lightgoldenrodyellow, lightgray, lightgreen, lightgrey, lightpink, lightsalmon, lightseagreen, lightskyblue, lightslategray, lightslategrey, lightsteelblue, lightyellow, lime, limegreen, linen, magenta, maroon, mediumaquamarine, mediumblue, mediumorchid, mediumpurple, mediumseagreen, mediumslateblue, mediumspringgreen, mediumturquoise, mediumvioletred, midnightblue, mintcream, mistyrose, moccasin, navajowhite, navy, oldlace, olive, olivedrab, orange, orangered, orchid, palegoldenrod, palegreen, paleturquoise, palevioletred, papayawhip, peachpuff, peru, pink, plum, powderblue, purple, rebeccapurple, red, rosybrown, royalblue, saddlebrown, salmon, sandybrown, seagreen, seashell, sienna, silver, skyblue, slateblue, slategray, slategrey, snow, springgreen, steelblue, tan, teal, thistle, tomato, turquoise, violet, wheat, white, whitesmoke, yellow, yellowgreen

Color of colormap at value 1; Choose from matplotlib CSS4 color list.

Default: “red”

--SAVE_FIG, -S

Directory to save the outputs to.

Default: “../examples/tf_coupon/figures/”