#!/usr/bin/env bash RESET=`tput sgr0` BOLD="`tput bold`" RED="$RESET`tput setaf 1`$BOLD" GREEN="$RESET`tput setaf 2`" YELLOW="$RESET`tput setaf 3`" BLUE="$RESET`tput setaf 4`$BOLD" export PYTHONPATH="$PWD:$PYTHONPATH" echo "${YELLOW}This script will prepare the data." echo "${YELLOW}You should run it from inside the repository." echo "${YELLOW}You should set the TAXI_PATH variable to where the data downloaded from kaggle is." echo "${YELLOW}Three data files are needed: ${BOLD}train.csv.zip${YELLOW}, ${BOLD}test.csv.zip${YELLOW} and ${BOLD}metaData_taxistandsID_name_GPSlocation.csv.zip${YELLOW}. They can be found at the following url: ${BOLD}https://www.kaggle.com/c/pkdd-15-predict-taxi-service-trajectory-i/data" if [ ! -e train.py ]; then echo "${RED}train.py not found, you are not inside the taxi repository." exit 1 fi echo -e "\n$BLUE# Checking dependencies" python_import(){ echo -n "${YELLOW}$1... $RESET" if ! python2 -c "import $1; print '${GREEN}version', $1.__version__, '${YELLOW}(we used version $2)'"; then echo "${RED}failed, $1 is not installed" exit 1 fi } python_import h5py 2.5.0 python_import theano 0.7.0.dev python_import fuel 0.0.1 python_import blocks 0.0.1 python_import sklearn 0.16.1 echo -e "\n$BLUE# Checking data" echo "${YELLOW}TAXI_PATH is set to $TAXI_PATH" md5_check(){ echo -n "${YELLOW}md5sum $1... $RESET" if [ ! -e "$TAXI_PATH/$1" ]; then echo "${RED}file not found, are you sure you set the TAXI_PATH variable correctly?" exit 1 fi if command -v md5 >/dev/null 2>&1; then md5=`md5 "$TAXI_PATH/$1" | sed -e 's/^.* //'` elif command -v md5sum >/dev/null 2>&1; then md5=`md5sum "$TAXI_PATH/$1" | sed -e 's/ .*//'` else echo "${RED} no md5 utility" return fi if [ $md5 = $2 ]; then echo "$GREEN$md5 ok" else echo "$RED$md5 failed" exit 1 fi } md5_check train.csv.zip 87a1b75adfde321dc163160b495964e8 md5_check test.csv.zip 47133bf7349cb80cc668fa56af8ce743 md5_check metaData_taxistandsID_name_GPSlocation.csv.zip fecec7286191af868ce8fb208f5c7643 echo -e "\n$BLUE# Extracting data" zipextract(){ echo -n "${YELLOW}unziping $1... $RESET" unzip -o "$TAXI_PATH/$1" -d "$TAXI_PATH" echo "${GREEN}ok" } zipextract train.csv.zip md5_check train.csv 68cc499ac4937a3079ebf69e69e73971 zipextract test.csv.zip md5_check test.csv f2ceffde9d98e3c49046c7d998308e71 zipextract metaData_taxistandsID_name_GPSlocation.csv.zip echo -n "${YELLOW}patching error in metadata csv... $RESET" cat "$TAXI_PATH/metaData_taxistandsID_name_GPSlocation.csv" | sed -e 's/41,Nevogilde,41.163066654-8.67598304213/41,Nevogilde,41.163066654,-8.67598304213/' > "$TAXI_PATH/metaData_taxistandsID_name_GPSlocation.csv.tmp" mv "$TAXI_PATH/metaData_taxistandsID_name_GPSlocation.csv.tmp" "$TAXI_PATH/metaData_taxistandsID_name_GPSlocation.csv" echo "${GREEN}ok" md5_check metaData_taxistandsID_name_GPSlocation.csv 724805b0b1385eb3efc02e8bdfe9c1df echo -e "\n$BLUE# Conversion of training set to HDF5" echo "${YELLOW}This might take some time$RESET" python2 data/csv_to_hdf5.py "$TAXI_PATH" "$TAXI_PATH/data.hdf5" echo -e "\n$BLUE# Generation of validation set" echo "${YELLOW}This might take some time$RESET" echo -n "${YELLOW}initialization... $RESET" python2 data/init_valid.py echo "${GREEN}ok" echo -n "${YELLOW}cutting... $RESET" python2 data/make_valid_cut.py test_times_0 echo "${GREEN}ok" echo -e "\n$BLUE# Generation of destination cluster" echo "${YELLOW}This might take some time$RESET" echo -n "${YELLOW}generating... $RESET" python2 data_analysis/cluster_arrival.py echo "${GREEN}ok" echo -e "\n$BLUE# Creating output folders" echo -n "${YELLOW}mkdir model_data... $RESET"; mkdir model_data; echo "${GREEN}ok" echo -n "${YELLOW}mkdir output... $RESET"; mkdir output; echo "${GREEN}ok" echo -e "\n$GREEN${BOLD}The data was successfully prepared" echo "${YELLOW}To train the winning model on gpu, you can now run the following command:" echo "${YELLOW}THEANO_FLAGS=floatX=float32,device=gpu,optimizer=FAST_RUN python2 train.py dest_mlp_tgtcls_1_cswdtx_alexandre"