script.py

import tensorflow as tf
import numpy as np
import pandas
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"]="2" #ignore warnings
import tensorflow as tf
import csv
import argparse

def normalize_cols(m):
	col_max=m.max(axis=0)
	col_min=m.min(axis=0)
	return (m-col_min)/(col_max-col_min)

def calculate():
	# Input data for predictinig
	PredictingInput = pandas.read_csv("PredictingData.csv")
	dataset = PredictingInput[['P', 'V', 'h', 't']].values
	datasetN=np.nan_to_num(normalize_cols(dataset))
	P_num = 21
	V_num = 18
	h_num = 10
	t_num = 13

	#def predict():
	sess = tf.Session()
	sess.run(tf.global_variables_initializer())
	sess.run(tf.local_variables_initializer())
	saver=tf.train.import_meta_graph('D:/TensorFlow_ANN/ML-3DPrinterData/ML-3DPrinterData/tmp/trained.meta')
	saver.restore(sess, tf.train.latest_checkpoint('D:/TensorFlow_ANN/ML-3DPrinterData/ML-3DPrinterData/tmp/'))

	graph = tf.get_default_graph()

	X = graph.get_tensor_by_name('x_data:0')
	final_output = graph.get_tensor_by_name('final_output:0')
	result = sess.run(final_output, feed_dict={X: datasetN})

	Density_vals =np.array([[x[col] for col in range(1)] for x in result])
	Surface_vals =np.array([[x[col] for col in range(1,2)] for x in result])

	Density_vals_max=[Density_vals.max(axis=0)[i] for i in range(1)]
	Surface_vals_min=[Surface_vals.min(axis=0)[i] for i in range(1)]

	parser = argparse.ArgumentParser(description='Process input data')
	parser.add_argument('--Density', type = float, dest = 'Density', help = 'Density Ratio (%) ')
	parser.add_argument('--Ra', type= float, dest = 'Ra', help = 'Surface Roughness- Ra (um) ')
	args = parser.parse_args()

	#Density = float(input("Density Ratio (%): ")) # User input
	#Ra = float(input("Surface Roughness- Ra (um): ")) #User input

	filter1 = [i for i in range(dataset.shape[0]) if list(np.abs(result[i,:]- np.array([args.Density, args.Ra]))<=1) == [True, True]]
	filter1val = dataset[filter1]

	mark = np.abs(filter1val[:,0]*1e6/(filter1val[:,1]*filter1val[:,2]*filter1val[:,3])-50)<=0.005
	filter2 = filter1val[mark]

	return filter2