jupyter working with explicit filename... data_MATCH.csv
parent
c2e670841a
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3f4b4ae717
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@ -2,21 +2,9 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'karoo_gp_base_class'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-1-f6e2bcf4ec4a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m;\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'modules/'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# add directory 'modules' to the current path\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0margparse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mkaroo_gp_base_class\u001b[0m\u001b[0;34m;\u001b[0m \u001b[0mgp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkaroo_gp_base_class\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBase_GP\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'clear'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'karoo_gp_base_class'"
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]
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}
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],
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"outputs": [],
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"source": [
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"# Karoo GP (desktop + server combined)\n",
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"# Use Genetic Programming for Classification and Symbolic Regression\n",
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@ -256,19 +244,44 @@
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"\tevolve_point = int(float(args.evo_p) * tree_pop_max)\n",
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"\tevolve_branch = int(float(args.evo_b) * tree_pop_max)\n",
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"\tevolve_cross = int(float(args.evo_c) * tree_pop_max)\n",
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"\tfilename = str(args.filename)\n",
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"\t\n",
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"\t#filename = str(args.filename)\n",
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"\tfilename='files/data_MATCH.csv'\n",
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"\tdisplay = 's' # display mode is set to (s)ilent\n",
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"\tprecision = 6 # number of floating points for the round function in 'fx_fitness_eval'\n",
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"\tswim = 'p' # require (p)artial or (f)ull set of features (operators) for each Tree entering the gene_pool\n",
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"\tmode = 's' # pause at the (d)esktop when complete, awaiting further user interaction; or terminate in (s)erver mode\n",
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"\t\n",
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"\n",
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"\t"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%connect_info"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"print(filename)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#++++++++++++++++++++++++++++++++++++++++++\n",
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"# Conduct the GP run |\n",
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"#++++++++++++++++++++++++++++++++++++++++++\n",
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"\n",
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"gp.fx_karoo_gp(kernel, tree_type, tree_depth_base, tree_depth_max, tree_depth_min, tree_pop_max, gen_max, tourn_size, filename, evolve_repro, evolve_point, evolve_branch, evolve_cross, display, precision, swim, mode)\n"
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"gp.fx_karoo_gp(kernel, tree_type, tree_depth_base, tree_depth_max, tree_depth_min, tree_pop_max, gen_max, tourn_size, filename, evolve_repro, evolve_point, evolve_branch, evolve_cross, display, precision, swim, mode)"
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]
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}
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],
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