def test_dame_gender_features_list2csv(self):
# TODO: You can write asserts to verify the first line
g = Gender()
csv1 = g.features_list2csv(path="files/names/min.csv")
csv2 = g.features_list2csv(path="files/names/min.csv",
categorical="categorical")
csv3 = g.features_list2csv(path="files/names/min.csv",
categorical="nocategorical")
csv4 = g.features_list2csv(path="files/names/allnoundefined.csv",
categorical="noundefined")
self.assertTrue(os.path.isfile("files/features_list.csv"))
file = open("files/features_list.csv", "r")
if (file):
self.assertTrue(os.path.isfile("files/features_list_cat.csv"))
self.assertTrue(os.path.isfile("files/features_list_no_cat.csv"))
self.assertTrue(
os.path.isfile("files/features_list_no_undefined.csv"))
from app.dame_sexmachine import DameSexmachine
from app.dame_gender import Gender
## PARAMETERS
parser = argparse.ArgumentParser()
parser.add_argument("--categorical",
default="both",
choices=['both', 'noletters', 'nocategorical', 'all'])
parser.add_argument("--components", default=0, type=int)
args = parser.parse_args()
if (args.components > 0):
## LOAD DATASET
g = Gender()
if (args.categorical == "both"):
g.features_list2csv(categorical="both",
path="files/names/allnoundefined.csv")
features = "files/features_list_no_undefined.csv"
elif (args.categorical == "noletters"):
g.features_list2csv(categorical="noletters",
path="files/names/allnoundefined.csv")
features = "files/features_list_cat.csv"
elif (args.categorical == "nocategorical"):
g.features_list2csv(categorical="nocategorical",
path="files/names/allnoundefined.csv")
features = "files/features_list_no_cat.csv"
else:
g.features_list2csv(categorical="both", path="files/names/all.csv")
features = "files/features_list.csv"
## STEP1: N COMPONENTS + 1 TARGET
x = pd.read_csv(features)
#print(x.columns)
# Boston, MA 02110-1301 USA,
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from app.dame_gender import Gender
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--csv')
args = parser.parse_args()
g = Gender()
if (args.csv == 'nocategorical'):
g.features_list_no_categorical("files/names/all.csv")
g.features_list2csv(csv="nocategorical")
data = pd.read_csv('files/features_list_no_cat.csv', index_col=0)
elif (args.csv == 'categorical'):
g.features_list_categorical("files/names/all.csv")
g.features_list2csv(csv="categorical")
data = pd.read_csv('files/features_list_cat.csv', index_col=0)
else:
g.features_list2csv("files/names/all.csv")
data = pd.read_csv('files/features_list.csv', index_col=0)
#data = pd.read_csv('files/features_list_cat.csv', index_col=0)
#data = pd.read_csv('files/features_list.csv', index_col=0)
corr = data.corr()
fig = plt.figure()
ax = fig.add_subplot(111)
cax = ax.matshow(corr, cmap='coolwarm', vmin=-1, vmax=1)