from collections import Counter

from datetime import datetime, timedelta

from loader import get_data

class Range:

    def __init__(self, low, high):

        self.low = self.icd9_to_float(low)

        self.high = self.icd9_to_float(high)

    def icd9_to_float(self, icd9):

        try:

            return float(icd9)

        except ValueError:

            extension = float(icd9[1:])

            letter = icd9[0]

            return ord(letter)*1000 + extension

    def __eq__(self, other):

        other = self.icd9_to_float(other)

        return other >= self.low and other <= self.high

    def __ne__(self, other):

        return not self.__eq__(other)

num_patients = 1579

#num_patients = 100

dead_patients = []

gender = []

age = []

is_cancer = []

consult_time = []

cancer_time = []

cancer_mgh_time = []

cardio_mgh_time = []

noncancer_time = []

utilization = []

utilization_cancer = []

utilization_mgh_cancer = []

utilization_noncancer = []

utilization_mgh_cardio = []

for i in range(num_patients):

    p = get_data([i])[0]

    # Filter to only dead patients

    if p['Vital_status'] == 'Date of Death reported from SS Death Master File':

        if p['Consult_Date'] not in [None, '']:

            dead_patients.append(p['EMPI'])

            gender.append(p['Gender'])

            # Dates

            dob = datetime.strptime(p['Date_of_Birth'], "%m/%d/%Y")

            dod = datetime.strptime(p['Date_Of_Death\r'], "%m/%d/%Y")

            doc = datetime.strptime(p['Consult_Date'], "%m/%d/%Y")

            age.append((dod - dob).days/365.0)

            timing = dod - doc

            consult_time.append(timing.days)

            # Diagnoses

            cancer_icds = [Range(140.00, 209.99), Range(230.00, 239.99)]

            is_cancer_patient = False

            for d in p['Dia']:

                if d['Code_Type'] == 'ICD9':

                    try:

                        if d['Code'] in cancer_icds:

                            is_cancer_patient = True

                    except:

                        pass

            is_cancer.append(is_cancer_patient)

            # Stratify

            if is_cancer_patient:

                cancer_time.append(timing.days)

            else:

                noncancer_time.append(timing.days)

            # Utilization

            mgh_onc_enc_count = 0

            mgh_cardio_enc_count = 0

            utilization_cutoff = timedelta(days=30*3)

            num_eol_enc = 0

            len_eol_enc = 0

            died_in_hospital = False

            for enc in p['Enc']:

                admitted = datetime.strptime(enc['Admit_Date'], "%m/%d/%Y")

                # MGH?

                if (dod - admitted) < timedelta(days=365):

                    if enc['Clinic_Name'] == 'Medical Oncology Group (609)':

                        mgh_onc_enc_count += 1

                    elif enc['Clinic_Name'] == 'Cardiology (12)':

                        mgh_cardio_enc_count += 1

                if (dod - admitted) < utilization_cutoff:

                    num_eol_enc += 1

                    try:

                        discharged = datetime.strptime(enc['Discharge_Date'], "%m/%d/%Y")

                        if enc['Inpatient_Outpatient'] == 'Inpatient':

                            len_eol_enc += (discharged-admitted).days

                            if dod == discharged:

                                died_in_hospital = True

                    except:

                        pass

            utilization.append((timing.days, num_eol_enc, len_eol_enc, died_in_hospital))

            if is_cancer_patient:

                utilization_cancer.append((timing.days, num_eol_enc, len_eol_enc, died_in_hospital))

            else:

                utilization_noncancer.append((timing.days, num_eol_enc, len_eol_enc, died_in_hospital))

            # Is an MGH Oncology patient

            if mgh_onc_enc_count >= 2:

                utilization_mgh_cancer.append((timing.days, num_eol_enc, len_eol_enc, died_in_hospital))

                cancer_mgh_time.append(timing.days)

            if not is_cancer_patient and mgh_cardio_enc_count >= 2:

                utilization_mgh_cardio.append((timing.days, num_eol_enc, len_eol_enc, died_in_hospital))

                cardio_mgh_time.append(timing.days)

    else:

        if p['Vital_status'] != 'Not reported as deceased':

            print "***********************"

            print p['Vital_status'] 

            print "***********************"

# Step 1:

print "Percent of patients dead: " + str(float(len(dead_patients))/num_patients)

# Step 2:

# Age

print "Age distribution:"

print age

# Gender

print "Gender Distribution: " + str(Counter(gender))

# Cancer?

print "Is Cancer Patient: " + str(Counter(is_cancer))

# Step 3:

print "Consult timing distribution:"

print consult_time

# Step 4:

print "Cancer patient consult times:"

print cancer_time

print "MGH Cancer patient consult times:"

print cancer_mgh_time

print "Non-Cancer patient consult times:"

print noncancer_time 

print "MGH Cardio patient consult times:"

print cardio_mgh_time

# Step 5:

print "Utilization"

print utilization

print "Utilization: Cancer"

print utilization_cancer

print "Utilization: MGH Cancer"

print utilization_mgh_cancer

print "Utilization: Non Cancer"

print utilization_noncancer

print "Utilization: MGH Cardio"

print utilization_mgh_cardio