diff --git a/predihood/classes/Data.py b/predihood/classes/Data.py
index 4057c473cc4429ca8c11ca1be48c2892056feed9..0b9eabdfc0effc9b0051022d2dcf906ffd129146 100644
--- a/predihood/classes/Data.py
+++ b/predihood/classes/Data.py
@@ -9,7 +9,8 @@ from area import area
from predihood import model
from predihood.cleaning import clean
-from predihood.config import FILE_CLEANED_DATA, FOLDER_DATASETS, ENVIRONMENT_VARIABLES, FILE_GROUPING, NEW_PREFIX, OLD_PREFIX
+from predihood.config import FILE_CLEANED_DATA, FOLDER_DATASETS, ENVIRONMENT_VARIABLES, FILE_GROUPING, NEW_PREFIX, \
+ OLD_PREFIX, FILE_MANUAL_ASSESSMENT
from predihood.utility_functions import address_to_code, append_indicator, append_target
log = logging.getLogger(__name__)
@@ -27,6 +28,8 @@ class Data:
self.old_path = FILE_CLEANED_DATA
self.dataset_path = os.path.join(FOLDER_DATASETS, "data_"+str(normalization)+".csv")
self.filtered_path = os.path.join(FOLDER_DATASETS, "data_"+str(normalization)+"_filtered.csv")
+ self.assessment_path = os.path.join(FOLDER_DATASETS, "data_" + str(normalization) + "with_assessment.csv")
+ self.assessment_filtered_path = os.path.join(FOLDER_DATASETS, "data_" + str(normalization) + "_filtered_with_assessment.csv")
self.data = None
self.indicators = None
self.normalization = normalization
@@ -62,23 +65,43 @@ class Data:
"""
Create or read the dataset. It applies normalization and/or filtering if needed.
"""
- if not os.path.exists(self.dataset_path):
- self.create()
- self.apply_normalization()
- if self.filtering: self.apply_filtering()
- elif not os.path.exists(self.filtered_path):
- if self.filtering: self.apply_filtering()
+ if self.add_assessment:
+ if not os.path.exists(self.assessment_path):
+ print("HERE")
+ # self.create()
+ self.add_manually_assessed_iris() # complete data with manually assessed IRIS
+ self.apply_normalization()
+ if self.filtering: self.apply_filtering()
+ elif not os.path.exists(self.assessment_filtered_path):
+ print("THERE")
+ if self.filtering: self.apply_filtering()
+ else:
+ print("NO")
+ self.read()
else:
- self.read()
+ if not os.path.exists(self.dataset_path):
+ self.create()
+ self.apply_normalization()
+ if self.filtering: self.apply_filtering()
+ elif not os.path.exists(self.filtered_path):
+ if self.filtering: self.apply_filtering()
+ else:
+ self.read()
def read(self):
"""
Read the dataset stored in the CSV file (and get indicators from this dataset).
"""
- if self.filtering:
- self.data = pd.read_csv(self.filtered_path)
+ if self.add_assessment:
+ if self.filtering:
+ self.data = pd.read_csv(self.assessment_filtered_path)
+ else:
+ self.data = pd.read_csv(self.assessment_path)
else:
- self.data = pd.read_csv(self.dataset_path)
+ if self.filtering:
+ self.data = pd.read_csv(self.filtered_path)
+ else:
+ self.data = pd.read_csv(self.dataset_path)
self.get_indicators()
def create(self):
@@ -250,7 +273,10 @@ class Data:
Remove (filter) too detailed indicators and constant columns from the dataset.
"""
if self.data is None:
- self.data = pd.read_csv(self.dataset_path)
+ if self.add_assessment:
+ self.data = pd.read_csv(self.assessment_path)
+ else:
+ self.data = pd.read_csv(self.dataset_path)
self.get_indicators()
# 1. remove indicators that have been defined as useless
@@ -261,7 +287,8 @@ class Data:
self.data.drop(constant_columns, axis=1, inplace=True)
self.indicators = [indicator for indicator in self.indicators if indicator not in constant_columns]
- self.data.to_csv(self.filtered_path, index=None) # index=None: avoid line numbering
+ if self.add_assessment: self.data.to_csv(self.assessment_filtered_path, index=None)
+ else: self.data.to_csv(self.filtered_path, index=None) # index=None: avoid line numbering
def apply_normalization(self):
"""
@@ -281,5 +308,28 @@ class Data:
self.data.at[index, col_name] = row[col_name] / density if density > 0 else 0
elif self.normalization is None:
self.data.at[index, col_name] = row[col_name]
- self.data.to_csv(self.dataset_path, index=None) # index=None: avoid line numbering
+ if self.add_assessment: self.data.to_csv(self.assessment_path, index=None)
+ else: self.data.to_csv(self.dataset_path, index=None) # index=None: avoid line numbering
+
+ def add_manually_assessed_iris(self):
+ print()
+ print("ADD MANUAL ASSESSMENT")
+ manually_assessed_iris = pd.read_csv(FILE_MANUAL_ASSESSMENT, header=0)
+ if self.data is None:
+ print("data is None")
+ self.read()
+ print(len(self.data))
+ else:
+ print("data exists")
+ print(len(self.data))
+ self.data = self.data.append(manually_assessed_iris)
+ print(len(self.data))
+ self.data["CODE"] = self.data["CODE"].astype(str)
+ self.data.sort_values("CODE", inplace=True)
+ self.fill_missing_values("median")
+ nan_columns = self.data.columns[self.data.isna().all()].tolist()
+ log.debug("There are %d NaN columns", len(nan_columns))
+ self.data.drop(nan_columns, axis=1, inplace=True)
+ self.indicators = [indicator for indicator in self.indicators if indicator not in nan_columns] # remove names of NaN columns in the list of indicators
+
diff --git a/predihood/classes/manual_assessment.csv b/predihood/classes/manual_assessment.csv
index 50c8c83b3b3a5a2157a1b7f9aa41cc72d0585078..409c662de93a364b76046fef1077936efaa86d7c 100644
--- a/predihood/classes/manual_assessment.csv
+++ b/predihood/classes/manual_assessment.csv
@@ -1,2 +1,9 @@
CODE,AREA,DENSITY,P14_POP,P14_POP0002,P14_POP0305,P14_POP0610,P14_POP1117,P14_POP1824,P14_POP2539,P14_POP4054,P14_POP5564,P14_POP6579,P14_POP80P,P14_POP0014,P14_POP1529,P14_POP3044,P14_POP4559,P14_POP6074,P14_POP75P,P14_POP0019,P14_POP2064,P14_POP65P,P14_POPH,P14_H0014,P14_H1529,P14_H3044,P14_H4559,P14_H6074,P14_H75P,P14_H0019,P14_H2064,P14_H65P,P14_POPF,P14_F0014,P14_F1529,P14_F3044,P14_F4559,P14_F6074,P14_F75P,P14_F0019,P14_F2064,P14_F65P,C14_POP15P,C14_POP15P_CS1,C14_POP15P_CS2,C14_POP15P_CS3,C14_POP15P_CS4,C14_POP15P_CS5,C14_POP15P_CS6,C14_POP15P_CS7,C14_POP15P_CS8,C14_H15P,C14_H15P_CS1,C14_H15P_CS2,C14_H15P_CS3,C14_H15P_CS4,C14_H15P_CS5,C14_H15P_CS6,C14_H15P_CS7,C14_H15P_CS8,C14_F15P,C14_F15P_CS1,C14_F15P_CS2,C14_F15P_CS3,C14_F15P_CS4,C14_F15P_CS5,C14_F15P_CS6,C14_F15P_CS7,C14_F15P_CS8,P14_POP_FR,P14_POP_ETR,P14_POP_IMM,P14_PMEN,P14_PHORMEN,P14_LOG,P14_RP,P14_RSECOCC,P14_LOGVAC,P14_MAISON,P14_APPART,P14_RP_1P,P14_RP_2P,P14_RP_3P,P14_RP_4P,P14_RP_5PP,P14_NBPI_RP,P14_RPMAISON,P14_NBPI_RPMAISON,P14_RPAPPART,P14_NBPI_RPAPPART,P14_RP_M30M2,P14_RP_3040M2,P14_RP_4060M2,P14_RP_6080M2,P14_RP_80100M2,P14_RP_100120M2,P14_RP_120M2P,P14_RP_ACHTOT,P14_RP_ACH19,P14_RP_ACH45,P14_RP_ACH70,P14_RP_ACH90,P14_RP_ACH05,P14_RP_ACH11,P14_RPMAISON_ACHTOT,P14_RPMAISON_ACH19,P14_RPMAISON_ACH45,P14_RPMAISON_ACH70,P14_RPMAISON_ACH90,P14_RPMAISON_ACH05,P14_RPMAISON_ACH11,P14_RPAPPART_ACHTOT,P14_RPAPPART_ACH19,P14_RPAPPART_ACH45,P14_RPAPPART_ACH70,P14_RPAPPART_ACH90,P14_RPAPPART_ACH05,P14_RPAPPART_ACH11,P14_MEN,P14_MEN_ANEM0002,P14_MEN_ANEM0204,P14_MEN_ANEM0509,P14_MEN_ANEM10P,P14_PMEN_ANEM0002,P14_PMEN_ANEM0204,P14_PMEN_ANEM0509,P14_PMEN_ANEM10P,P14_NBPI_RP_ANEM0002,P14_NBPI_RP_ANEM0204,P14_NBPI_RP_ANEM0509,P14_NBPI_RP_ANEM10P,P14_RP_PROP,P14_RP_LOC,P14_RP_LOCHLMV,P14_RP_GRAT,P14_NPER_RP,P14_NPER_RP_PROP,P14_NPER_RP_LOC,P14_NPER_RP_LOCHLMV,P14_NPER_RP_GRAT,P14_ANEM_RP,P14_ANEM_RP_PROP,P14_ANEM_RP_LOC,P14_ANEM_RP_LOCHLMV,P14_ANEM_RP_GRAT,P14_RP_SDB,P14_RP_CCCOLL,P14_RP_CCIND,P14_RP_CINDELEC,P14_RP_ELEC,P14_RP_EAUCH,P14_RP_BDWC,P14_RP_CHOS,P14_RP_CLIM,P14_RP_TTEGOU,P14_RP_GARL,P14_RP_VOIT1P,P14_RP_VOIT1,P14_RP_VOIT2P,NB_B101,NB_B102,NB_B103,NB_B201,NB_B202,NB_B203,NB_B204,NB_B205,NB_B206,NB_B301,NB_B302,NB_B303,NB_B304,NB_B305,NB_B306,NB_B307,NB_B308,NB_B309,NB_B310,NB_B311,NB_B312,NB_B313,NB_B315,NB_B316,DEC_PIMP14,DEC_TP6014,DEC_Q114,DEC_MED14,DEC_Q314,DEC_EQ14,DEC_D114,DEC_D214,DEC_D314,DEC_D414,DEC_D614,DEC_D714,DEC_D814,DEC_D914,DEC_RD14,DEC_S80S2014,DEC_GI14,DEC_PTSA14,DEC_PCHO14,DEC_PBEN14,DEC_PPEN14,DEC_PAUT14,note,NB_D201,NB_D202,NB_D203,NB_D204,NB_D205,NB_D206,NB_D207,NB_D208,NB_D209,NB_D210,NB_D211,NB_D212,NB_D213,NB_D221,NB_D231,NB_D232,NB_D233,NB_D235,NB_D236,NB_D237,NB_D238,NB_D239,NB_D240,NB_D242,NB_D243,C401,C402,C403,C409,C501,C502,C503,C504,C505,C505_NB_INT,C509,C601,C602,C603,C604,C605,C605_NB_INT,C609,C701,C702,C101,C101_NB_CANT,C101_NB_EP,C101_NB_RPIC,C102,C102_NB_CANT,C102_NB_EP,C104,C104_NB_CANT,C104_NB_PELEM,C104_NB_EP,C104_NB_RPIC,C105,C105_NB_CANT,C105_NB_PELEM,C105_NB_EP,NB_F101,NB_F101_NB_AIREJEU,NB_F101_NB_COU,NB_F101_NB_ECL,NB_F102,NB_F102_NB_AIREJEU,NB_F102_NB_COU,NB_F102_NB_ECL,NB_F103,NB_F103_NB_AIREJEU,NB_F103_NB_COU,NB_F103_NB_ECL,NB_F104,NB_F104_NB_AIREJEU,NB_F104_NB_COU,NB_F104_NB_ECL,NB_F105,NB_F105_NB_AIREJEU,NB_F105_NB_COU,NB_F105_NB_ECL,NB_F106,NB_F106_NB_AIREJEU,NB_F106_NB_COU,NB_F106_NB_ECL,NB_F107,NB_F107_NB_AIREJEU,NB_F107_NB_COU,NB_F107_NB_ECL,NB_F108,NB_F108_NB_AIREJEU,NB_F108_NB_COU,NB_F108_NB_ECL,NB_F109,NB_F109_NB_AIREJEU,NB_F109_NB_COU,NB_F109_NB_ECL,NB_F110,NB_F110_NB_AIREJEU,NB_F110_NB_COU,NB_F110_NB_ECL,NB_F111,NB_F111_NB_AIREJEU,NB_F111_NB_COU,NB_F111_NB_ECL,NB_F112,NB_F112_NB_AIREJEU,NB_F112_NB_COU,NB_F112_NB_ECL,NB_F113,NB_F113_NB_AIREJEU,NB_F113_NB_COU,NB_F113_NB_ECL,NB_F114,NB_F114_NB_AIREJEU,NB_F114_NB_COU,NB_F114_NB_ECL,NB_F116,NB_F116_NB_AIREJEU,NB_F116_NB_COU,NB_F116_NB_ECL,NB_F117,NB_F117_NB_AIREJEU,NB_F117_NB_COU,NB_F117_NB_ECL,NB_F118,NB_F118_NB_AIREJEU,NB_F118_NB_COU,NB_F118_NB_ECL,NB_F119,NB_F119_NB_AIREJEU,NB_F119_NB_COU,NB_F119_NB_ECL,NB_F120,NB_F120_NB_AIREJEU,NB_F120_NB_COU,NB_F120_NB_ECL,NB_F121,NB_F121_NB_AIREJEU,NB_F121_NB_COU,NB_F121_NB_ECL,NB_F201,NB_F201_NB_AIREJEU,NB_F202,NB_F202_NB_AIREJEU,NB_F203,NB_F203_NB_AIREJEU,NB_F302,NB_F302_NB_SALLES,NB_F303,NB_F303_NB_SALLES,NB_F304,NB_F305,NB_A101,NB_A104,NB_A105,NB_A106,NB_A107,NB_A108,NB_A109,NB_A115,NB_A119,NB_A120,NB_A121,NB_A122,NB_A123,NB_A124,NB_A125,NB_A203,NB_A205,NB_A206,NB_A207,NB_A208,NB_A301,NB_A302,NB_A303,NB_A304,NB_A401,NB_A402,NB_A403,NB_A404,NB_A405,NB_A406,NB_A501,NB_A502,NB_A503,NB_A504,NB_A505,NB_A506,NB_A507,P14_POP1564,P14_POP1524,P14_POP2554,P14_H1564,P14_H1524,P14_H2554,P14_H5564,P14_F1564,P14_F1524,P14_F2554,P14_F5564,P14_ACT1564,P14_ACT1524,P14_ACT2554,P14_ACT5564,P14_HACT1564,P14_HACT1524,P14_HACT2554,P14_HACT5564,P14_FACT1564,P14_FACT1524,P14_FACT2554,P14_FACT5564,P14_ACTOCC1564,P14_ACTOCC1524,P14_ACTOCC2554,P14_ACTOCC5564,P14_HACTOCC1564,P14_HACTOCC1524,P14_HACTOCC2554,P14_HACTOCC5564,P14_FACTOCC1564,P14_FACTOCC1524,P14_FACTOCC2554,P14_FACTOCC5564,P14_CHOM1564,P14_CHOM1524,P14_CHOM2554,P14_CHOM5564,P14_HCHOM1564,P14_FCHOM1564,P14_INACT1564,P14_HINACT1564,P14_FINACT1564,P14_ETUD1564,P14_HETUD1564,P14_FETUD1564,P14_RETR1564,P14_HRETR1564,P14_FRETR1564,P14_AINACT1564,P14_HAINACT1564,P14_FAINACT1564,C14_ACT1564,C14_ACT1564_CS1,C14_ACT1564_CS2,C14_ACT1564_CS3,C14_ACT1564_CS4,C14_ACT1564_CS5,C14_ACT1564_CS6,C14_ACTOCC1564,C14_ACTOCC1564_CS1,C14_ACTOCC1564_CS2,C14_ACTOCC1564_CS3,C14_ACTOCC1564_CS4,C14_ACTOCC1564_CS5,C14_ACTOCC1564_CS6,P14_ACTOCC15P,P14_HACTOCC15P,P14_FACTOCC15P,P14_SAL15P,P14_HSAL15P,P14_FSAL15P,P14_NSAL15P,P14_HNSAL15P,P14_FNSAL15P,P14_ACTOCC15P_TP,P14_SAL15P_TP,P14_HSAL15P_TP,P14_FSAL15P_TP,P14_NSAL15P_TP,P14_SAL15P_CDI,P14_SAL15P_CDD,P14_SAL15P_INTERIM,P14_SAL15P_EMPAID,P14_SAL15P_APPR,P14_NSAL15P_INDEP,P14_NSAL15P_EMPLOY,P14_NSAL15P_AIDFAM,P14_ACTOCC15P_ILT1,P14_ACTOCC15P_ILT2P,P14_ACTOCC15P_ILT2,P14_ACTOCC15P_ILT3,P14_ACTOCC15P_ILT4,P14_ACTOCC15P_ILT5,C14_ACTOCC15P,C14_ACTOCC15P_PAS,C14_ACTOCC15P_MAR,C14_ACTOCC15P_DROU,C14_ACTOCC15P_VOIT,C14_ACTOCC15P_TCOM,C201,C201_NB_CANT,C201_NB_EP,C201_NB_INT,C301,C301_NB_CANT,C301_NB_PGE,C301_NB_EP,C301_NB_INT,C302,C302_NB_CANT,C302_NB_PGE,C302_NB_EP,C302_NB_INT,C303,C303_NB_PGE,C303_NB_INT,C304,C304_NB_CANT,C304_NB_INT,C305,C305_NB_CANT,C305_NB_INT,NB_D401,NB_D402,NB_D403,NB_D404,NB_D405,NB_D502,NB_D601,NB_D602,NB_D603,NB_D604,NB_D605,NB_D606,NB_D701,NB_D702,NB_D703,NB_D704,NB_D705,NB_D709,NB_E101,NB_E102,NB_E103,NB_E106,NB_G101,NB_G102,NB_G103,NB_G104,C14_MEN,C14_MENPSEUL,C14_MENHSEUL,C14_MENFSEUL,C14_MENSFAM,C14_MENFAM,C14_MENCOUPSENF,C14_MENCOUPAENF,C14_MENFAMMONO,C14_PMEN,C14_PMEN_MENPSEUL,C14_PMEN_MENHSEUL,C14_PMEN_MENFSEUL,C14_PMEN_MENSFAM,C14_PMEN_MENFAM,C14_PMEN_MENCOUPSENF,C14_PMEN_MENCOUPAENF,C14_PMEN_MENFAMMONO,P14_POP15P,P14_POP5579,P14_POPMEN15P,P14_POPMEN1524,P14_POPMEN2554,P14_POPMEN5579,P14_POPMEN80P,P14_POP15P_PSEUL,P14_POP1524_PSEUL,P14_POP2554_PSEUL,P14_POP5579_PSEUL,P14_POP80P_PSEUL,P14_POP15P_MARIEE,P14_POP15P_NONMARIEE,C14_MEN_CS1,C14_MEN_CS2,C14_MEN_CS3,C14_MEN_CS4,C14_MEN_CS5,C14_MEN_CS6,C14_MEN_CS7,C14_MEN_CS8,C14_PMEN_CS1,C14_PMEN_CS2,C14_PMEN_CS3,C14_PMEN_CS4,C14_PMEN_CS5,C14_PMEN_CS6,C14_PMEN_CS7,C14_PMEN_CS8,C14_FAM,C14_COUPAENF,C14_FAMMONO,C14_COUPSENF,C14_NE24F0,C14_NE24F1,C14_NE24F2,C14_NE24F3,C14_NE24F4P,P14_POP0205,P14_POP1114,P14_POP1517,P14_POP2529,P14_POP30P,P14_SCOL0205,P14_SCOL0610,P14_SCOL1114,P14_SCOL1517,P14_SCOL1824,P14_SCOL2529,P14_SCOL30P,P14_NSCOL15P,P14_NSCOL15P_DIPLMIN,P14_NSCOL15P_CAPBEP,P14_NSCOL15P_BAC,P14_NSCOL15P_SUP,P14_HNSCOL15P,P14_HNSCOL15P_DIPLMIN,P14_HNSCOL15P_CAPBEP,P14_HNSCOL15P_BAC,P14_HNSCOL15P_SUP,P14_FNSCOL15P,P14_FNSCOL15P_DIPLMIN,P14_FNSCOL15P_CAPBEP,P14_FNSCOL15P_BAC,P14_FNSCOL15P_SUP,C15_POP01P_IRAN012,C15_POP01P_IRANAUT,C15_POP01P,building_type,building_usage,landscape,morphological_position,geographical_position,social_class
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areas,Peri-urban,West,Upper middle
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3.0,,1.0,,11.0,4.0,,1.0,1506.0252921839074,837.4585548312618,395.9153319248126,441.5432229064493,117.06208925577178,551.5046480968738,256.2447308278108,175.2803386415381,119.9795786275249,2623.692538124235,837.4585548312618,395.9153319248126,441.5432229064493,265.32933809272095,1520.9046452002522,519.4464746006155,670.7362131295271,330.7219574701096,2345.4764206848263,424.6339849796175,2330.476370878788,649.6093998698727,1156.0086785968492,423.6339816592149,101.22431075285094,837.458554831262,197.723531718673,350.76606253651806,225.72578644790843,63.24317412816234,570.320565619844,1775.1558550649825,,36.01667234436194,298.82563744476124,296.7057262391995,275.62309562221805,121.51445543906148,304.3059647148155,173.03374037948976,,71.8308988330326,511.4679880927306,527.4722551408305,565.5332335770662,281.20183214811044,428.0470148155189,238.13931551694563,551.5046480968738,175.2803386415381,119.9795786275249,256.2447308278108,290.17764493081376,110.75446008372406,114.68070899526428,25.2287066519212,10.6631274351505,78.27218496928106,63.72929983021402,68.65883914362084,352.0148561776601,1343.8521646372938,49.6186625548784,104.7040929925004,60.19239566611816,68.65883914362084,403.9943649647356,80.66446422564006,35.15918899098608,1756.999563359844,341.7937045411866,278.308439457051,307.31770573453224,829.579713627074,854.2754752870591,125.28008634546954,139.813599172246,148.0874662397181,441.0943235296255,902.7240880727848,216.5136181957171,138.494840284805,159.23023949481413,388.4853900974486,,,,Houses,Housing,Urban,Central,Centre,Lower
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+693830902,0.4592769432295982,4611.44989763692,2117.932612843128,42.82969123523884,68.63847536404099,128.1399834244933,156.49989422336952,209.7845435390191,335.0501224897462,422.37631474796734,309.1044058305852,324.31224914978395,121.1969328388838,320.98696447524355,397.5790780263369,345.40401993542235,459.2603461573309,401.2332881893769,193.46891605941755,441.1316638869824,1231.291766967478,445.50918198866776,931.0539145488228,151.11174475873474,155.2767453375324,177.89969670987634,201.64369219204792,183.1947349083289,61.92730064230243,210.526898047954,537.9782763762789,182.5487401245898,1186.8786982943054,169.8752197165088,242.3023326888045,167.50432322554602,257.616653965283,218.03855328104797,131.54161541711514,230.60476583902843,693.313490591199,262.96044186407795,1796.9456483678846,,40.88897356033723,439.6570737521417,272.3563790395758,215.8565778158016,57.46643050096992,477.938268758038,292.7819449410204,779.942169790088,,23.25580275536064,243.1693461267288,87.76112371247153,62.04919479371927,43.66146667098799,193.54091078415692,126.5043249466628,1017.0034785777966,,17.63317080497659,196.4877276254129,184.5952553271043,153.80738302208235,13.80496382998193,284.397357973881,166.2776199943575,2022.5557933375517,95.37681950557668,187.10527332755404,2117.932612843128,,1141.5033589959244,1011.6264515887116,28.902024722167027,100.9748826850456,446.9748647003768,688.3418589921749,78.45563959918982,143.39780432710214,218.0243236827636,203.920374631972,367.8283093476841,4006.0526878203714,404.9535577503335,2210.813493271268,600.4862585350055,1782.679308561401,21.95936387481595,100.16010333401434,240.2476182660968,122.8289965440634,168.75308024677173,132.26434042227783,225.4129489006716,1009.6317586653832,69.83817652303419,301.7810145773249,279.5492535551129,216.4731786844625,96.06511581471906,45.92501951072944,403.9562112886693,63.39159341084737,129.5459857606408,53.79420851444729,81.22379786103829,53.36460215352242,22.63602358817307,599.4889120733412,6.44658311218682,169.0484034745192,222.75503507945797,135.24938082342425,42.70051366119664,23.28899592255637,1011.6264515887116,113.3826008127544,167.2678650579861,204.02040009789545,526.9555856200758,173.32412699822012,393.57176108723934,482.95360264126055,1068.083122116408,245.4996135455264,540.9207040919616,803.6458995422277,2415.986470640656,577.395464139944,424.70248729218235,157.02198929171408,9.52850015658537,2117.932612843128,1360.8641616848374,744.484962139174,331.1703065529469,12.5834890191167,16894.397130596324,12362.235372404528,4451.951179719151,2839.736705737761,80.21057847264537,971.030158992854,196.9626075910064,574.276870551075,211.82840115874137,,,,,,,558.4300739171665,819.3005626422428,490.2207982028916,329.0797644393512,,,,,,,,,,,1.0,,,,,,,,,,,,,,71.47208121827411,14.422648238965673,18606.0,31692.0,49370.0,0.9707181623122555,7910.0,15684.0,20808.0,26362.0,38034.0,45992.0,55134.0,76420.0,9.66118836915297,11.823425953799578,0.4213728643,53.6,1.8,12.9,22.8,8.9,,3.0,,,,,,,,,,,10.0,1.0,,,1.0,7.0,,,,,,,,2.0,,,,,,,,,,,,,,,,,,,,,1.0,1.0,,,,,,1.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1.0,1.0,1.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1.0,,,,,3.0,,3.0,,,1.0,1.0,,2.0,3.0,,,1351.4364663792169,284.9056233109182,757.4264372377135,597.3934296654982,118.7098589643004,332.79436511018093,145.88920559101683,754.0430367137186,166.19576434661778,424.6320721275325,163.2152002395683,1000.8322415320022,96.41870382324149,709.7543940627578,194.65914364600292,440.3716918793397,32.50104478432292,311.5558546566664,96.31479243835044,560.4605496526625,63.91765903891856,398.1985394060914,98.34435120765252,935.7078194358866,92.36636849904588,655.3607874923823,187.9806634444584,418.0129749759192,31.50369832265864,293.5860784645656,92.92319818869495,517.6948444599674,60.86267017638723,361.7747090278168,95.0574652557634,65.12442209611562,4.05233532419561,54.39360657037542,6.67848020154459,22.35871690342052,42.7657051926951,350.6042248472145,157.0217377861585,193.58248706105618,188.2923335305046,88.20350710330605,100.08882642719857,78.56562031108386,33.57240170202698,44.99321860905688,83.74627100562613,35.24582898082543,48.500442024800705,1000.8322415320022,,40.88897356033723,423.36798447476286,268.1724072357466,209.4099947036148,50.88821090914949,935.7078194358866,,40.88897356033723,412.6371689490227,242.9351645502617,192.54227327094472,46.70423910532027,962.759100108915,434.14662290619225,528.6124772027229,798.9539191557424,338.73476723449846,460.2191519212439,163.8051809531727,95.4118556716938,68.39332528147892,233.0324970043413,192.76678446240905,21.88270629650593,170.88407816590313,40.26571254193225,670.9452057780437,84.30084246072092,12.06476737452864,3.05498886253133,28.58811467991774,102.75020930672272,61.05497164644999,,573.1626779909327,389.5964221179824,326.6410404625024,48.77779114270262,14.17759051277736,,962.759100108915,31.11399894754256,98.82478519716835,75.9279713420214,520.5142645402204,236.3780800819623,1.0,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,1.0,,,,,,,,,,,,1.0,,,,,1.0,,,1011.6264515887116,383.66368155357526,123.47671504639732,260.18696650717794,43.42171649391372,584.5410535412227,283.11568226463123,222.11599089751343,79.30938037907802,2117.932612843128,383.66368155357526,123.47671504639732,260.18696650717794,87.84077944949172,1646.4281518400612,579.4116085803755,866.3439524026858,200.6725908569998,1796.9456483678846,633.4166549803692,1796.9456483678846,284.90562331091814,757.4264372377136,633.4166549803692,121.1969328388838,383.66368155357526,47.57015092340902,155.45899714917692,124.89499067964873,55.7395428013406,855.5934639015758,941.3521844663088,,26.44242809752558,279.5155653130538,133.12376111353905,126.72686086630716,43.66146667098799,328.36487988872915,73.79148963856898,,59.27887278001794,767.3357633663865,271.51756842564225,223.71772622577524,110.30820350214594,539.521007525107,146.25347101805323,584.5410535412227,222.11599089751343,79.30938037907802,283.11568226463123,316.63290322927656,119.66167834207153,84.36047088614482,59.54658793279479,4.33941315093505,85.26653096719647,81.37881445147043,75.12107977189908,112.6734547154187,1399.3665703415477,62.29660054962056,124.95335808232836,81.37881445147043,75.12107977189908,165.67374906749114,13.37848078345206,28.97990080442357,1513.7924379406188,282.29354021089887,192.2646635831593,214.76534438274237,824.4688897638182,658.5014576506723,100.32505231990604,83.9888043168115,96.18627927311184,378.00132174084285,855.2909802899464,181.96848789099283,108.27585926634782,118.5790651096305,446.46756802297534,,,,Houses,Housing,Urban,Central,Centre,Lower
diff --git a/predihood/main.py b/predihood/main.py
index 8a267c3d62a19e204a5c02a856804d5462780421..7107833dd3449b717a91f2c627e6f342a4672f76 100755
--- a/predihood/main.py
+++ b/predihood/main.py
@@ -123,13 +123,14 @@ def run_algorithm():
test_size = parameters["test_size"]
remove_outliers = parameters["remove_outliers"]
remove_rural = parameters["remove_rural"]
+ add_manual_assessment = parameters["add_manual_iris"]
# 2. create an instance of the given classifier and tune it with user's parameters
clf = get_classifier(clf_name)
clf = set_classifier(clf, parameters)
# 3. run experiment on data to get accuracies for each EV and each list of selected indicators
- data = Data(normalization="density", filtering=True)
+ data = Data(normalization="density", filtering=True, add_assessment=add_manual_assessment)
data.init_all_in_one()
accuracies = compute_all_accuracies(data, clf, train_size, test_size, remove_outliers, remove_rural)
return {"results": accuracies, "tops_k": predihood.config.TOPS_K}
diff --git a/predihood/static/js/algorithms.js b/predihood/static/js/algorithms.js
index ffdb33b9dc803c6464cd0bfeec691bfc71a10b6c..2d29d2eaedcfc852c8c4a7df89e22ac7a1cc8127 100644
--- a/predihood/static/js/algorithms.js
+++ b/predihood/static/js/algorithms.js
@@ -91,6 +91,7 @@ $("#runBtn").click("on", function () {
userParameters["test_size"] = $("#testPercentage")[0].valueAsNumber;
userParameters["remove_outliers"] = $("#removeOutliers").prop("checked");
userParameters["remove_rural"] = $("#removeRural").prop("checked");
+ userParameters["add_manual_iris"] = $("#addAssessmentIris").prop("checked");
console.log(chosen_clf);
console.log(userParameters);
request_run = $.ajax({
diff --git a/predihood/static/js/carto.js b/predihood/static/js/carto.js
index c8828021d391d0f20f5a79a98901ef72924b3f53..b13931a0b8d47885a6831748d74763b4f2243c0e 100644
--- a/predihood/static/js/carto.js
+++ b/predihood/static/js/carto.js
@@ -105,53 +105,57 @@ function displayPopup(e) {
}
- // if($("#assessmentMode").is(":checked")) {
- // // alert("assessment mode");
- //
- // for(let env in environment_variables) {
- // let env_values = environment_variables[env]
- // let div_container = $("<div>").prop("id", "assessment"+env)
- // let list_values = $("<select>");
- // for(let value in env_values) { console.log(value); list_values.append($("<option>").prop("value", env_values[value]).text(env_values[value])) }
- // div_container.append(env).append(list_values)
- // divInformation.append(div_container)
- // }
- //
- // let to_csv_button = $("<button>").prop("id", "addAssessmentButton");
- // if(preferred_language_carto === "french") {
- // to_csv_button.text("Ajouter au jeu de données");
- // } else {
- // to_csv_button.text("Add to dataset");
- // }
- //
- // let messageTooltip = divInformation[0].outerHTML + to_csv_button[0].outerHTML;
- // layer.bindPopup(messageTooltip)
- // layer.bringToFront();
- // layer.openPopup();
- //
- // $("#addAssessmentButton").on("click", function() {
- // let data_param = {}
- // for(let env in environment_variables) {
- // data_param[env] = $("#assessment"+env)[0].children[0].value
- // }
- // data_param["code_iris"] = code_iris
- // console.log(data_param)
- // $.ajax({
- // type: "GET",
- // url: "/add_iris_to_csv",
- // data: data_param,
- // "async": false,
- // contentType: 'application/json;charset=UTF-8',
- // success: function(result) {
- // alert(result)
- // },
- // error: function(result, textStatus, errorThrown) {
- // console.log(errorThrown);
- // }
- // });
- // });
- // }
- // else {
+ if($("#assessmentMode").is(":checked")) {
+ // alert("assessment mode");
+
+ for(let env in environment_variables) {
+ let env_values = environment_variables[env]
+ let div_container = $("<div>").prop("id", "assessment"+env)
+ let list_values = $("<select>");
+ for(let value in env_values) { list_values.append($("<option>").prop("value", env_values[value]).text(env_values[value])) }
+ div_container.append(env).append(list_values)
+ divInformation.append(div_container)
+ }
+
+ if($("#addAssessmentButton").length > 0) {
+ $("#addAssessmentButton").removeAttr("id"); // remove id to avoid duplicates (fix the miss of event on button)
+ }
+
+ let to_csv_button = $("<button>").prop("id", "addAssessmentButton");
+ if(preferred_language_carto === "french") {
+ to_csv_button.text("Ajouter au jeu de données");
+ } else {
+ to_csv_button.text("Add to dataset");
+ }
+
+ let messageTooltip = divInformation[0].outerHTML + to_csv_button[0].outerHTML;
+ layer.bindPopup(messageTooltip)
+ layer.bringToFront();
+ layer.openPopup();
+
+ $("#addAssessmentButton").on("click", function() {
+ let data_param = {}
+ for(let env in environment_variables) {
+ data_param[env] = $("#assessment"+env)[0].children[0].value
+ }
+ data_param["code_iris"] = code_iris
+ console.log(data_param)
+ $.ajax({
+ type: "GET",
+ url: "/add_iris_to_csv",
+ data: data_param,
+ "async": false,
+ contentType: 'application/json;charset=UTF-8',
+ success: function(result) {
+ alert(result)
+ },
+ error: function(result, textStatus, errorThrown) {
+ console.log(errorThrown);
+ }
+ });
+ });
+ }
+ else {
if (selected_algorithm !== "undefined" && selected_algorithm !== undefined) {
predictions = predict(code_iris, selected_algorithm)
console.log(predictions)
@@ -180,7 +184,7 @@ function displayPopup(e) {
$("#selectAlgorithmTooltip").val(previously_selected_algorithm); // must be after binding the popup to be effective
$("#selectAlgorithmTooltip").on("click", function() { displayPopup(e)}) // update popup (env variables) when click on an algorithm
- // }
+ }
}
/**
diff --git a/predihood/templates/algorithmic-interface.html b/predihood/templates/algorithmic-interface.html
index 077259f44e440525bf66071ce1814c65baa2e8b7..9b4c6e52351dedf555b59e0a368f15ef2c94bd4a 100644
--- a/predihood/templates/algorithmic-interface.html
+++ b/predihood/templates/algorithmic-interface.html
@@ -95,6 +95,10 @@
<i class="fa fa-question-circle mr-3 text-primary fa-fw" title="Check it to remove rural neighbourhoods in the dataset."></i>
Remove rural
<input id="removeRural" type="checkbox" title="Check it to remove rural neighbourhoods.">
+ <br>
+ <i class="fa fa-question-circle mr-3 text-primary fa-fw" title="Check it to add IRIS that have been manually assessed."></i>
+ Add manually assessed IRIS
+ <input id="addAssessmentIris" type="checkbox" title="Check it to add IRIS that have been manually assessed.">
{% endif %}
</div>
</li>
diff --git a/predihood/templates/form.html b/predihood/templates/form.html
index 828650ca152baa7958ea828b39c7215061c8d952..2f114f0f862f1835162f0b4213ae25565ee624cd 100644
--- a/predihood/templates/form.html
+++ b/predihood/templates/form.html
@@ -53,15 +53,15 @@
</button>
</div>
<br>
+</div>
+<div>
+ {% if language == "french" %}
+ Expertise manuelle: <input type="checkbox" id="assessmentMode"/>
+ {% else %}
+ Manual assessment: <input type="checkbox" id="assessmentMode"/>
+ {% endif %}
</div>
-{#<div>#}
-{# {% if language == "french" %}#}
-{# Expertise manuelle: <input type="checkbox" id="assessmentMode"/>#}
-{# {% else %}#}
-{# Manual assessment: <input type="checkbox" id="assessmentMode"/>#}
-{# {% endif %}#}
-{#</div>#}
<div class="input-group mb-3">
<button class="btn" type="button" id="boutonEffacer">