import seaborn as sns
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np

# p1ajor
# p1beton
# p1gach
# p1sang
# p1chub

df = pd.read_csv("navid01.csv")
df["a1ajor"] = pd.to_numeric(df['a1ajor'], errors='coerce')
df["a2ajor"] = pd.to_numeric(df['a2ajor'], errors='coerce')
df["a3ajor"] = pd.to_numeric(df['a3ajor'], errors='coerce')

df["a1beton"] = pd.to_numeric(df['a1beton'], errors='coerce')
df["a2beton"] = pd.to_numeric(df['a2beton'], errors='coerce')
df["a3beton"] = pd.to_numeric(df['a3beton'], errors='coerce')

df["a1gach"] = pd.to_numeric(df['a1gach'], errors='coerce')
df["a2gach"] = pd.to_numeric(df['a2gach'], errors='coerce')
df["a3gach"] = pd.to_numeric(df['a3gach'], errors='coerce')

df["a1sang"] = pd.to_numeric(df['a1sang'], errors='coerce')
df["a2sang"] = pd.to_numeric(df['a2sang'], errors='coerce')
df["a3sang"] = pd.to_numeric(df['a3sang'], errors='coerce')

df["a1chub"] = pd.to_numeric(df['a1chub'], errors='coerce')
df["a2chub"] = pd.to_numeric(df['a2chub'], errors='coerce')
df["a3chub"] = pd.to_numeric(df['a3chub'], errors='coerce')

# sum_of_cols = np.array([df["a1ajor"] + df["a1beton"] + df["a1gach"] + df["a1sang"] + df["a1chub"], df["a2ajor"] + df["a2beton"] + df["a2gach"] + df["a2sang"] + df["a2chub"] + df["a3ajor"] + df["a3beton"] + df["a3gach"] + df["a3sang"] + df["a3chub"]])


col_names0 = pd.Series(("B1" for i in range(len(df["a1ajor"]))))
col_names1 = pd.Series(("Brick2" for i in range(len(df["a2ajor"]))))
col_names2 = pd.Series(("B3" for i in range(len(df["a3ajor"]))))

bricks_values = []

col_names3 = pd.Series(("c1" for i in range(len(df["a1beton"]))))
col_names4 = pd.Series(("Concrete2" for i in range(len(df["a2beton"]))))
col_names5 = pd.Series(("c3" for i in range(len(df["a3beton"]))))

col_names6 = pd.Series(("P1" for i in range(len(df["a1gach"]))))
col_names7 = pd.Series(("Plaster2" for i in range(len(df["a2gach"]))))
col_names8 = pd.Series(("P3" for i in range(len(df["a3gach"]))))

col_names9 = pd.Series(("S1" for i in range(len(df["a1sang"]))))
col_names10 = pd.Series(("Stone2" for i in range(len(df["a2sang"]))))
col_names11 = pd.Series(("S3" for i in range(len(df["a3sang"]))))

col_names12 = pd.Series(("W1" for i in range(len(df["a1chub"]))))
col_names13= pd.Series(("Wood2" for i in range(len(df["a2chub"]))))
col_names14 = pd.Series(("W3" for i in range(len(df["a3chub"]))))



# col_names2 = pd.Series(("Concrete" for i in range(len(sum1))))
# col_names3 = pd.Series(("Plaster" for i in range(len(sum1))))
# col_names4 = pd.Series(("stone" for i in range(len(sum1))))
# col_names5 = pd.Series(("wood" for i in range(len(sum1))))

names_below = pd.concat([col_names0,col_names1,col_names2,col_names3, col_names4, col_names5,col_names6,col_names7,col_names8, col_names9, col_names10,col_names11,col_names12,col_names13, col_names14], axis=0)
sums_below = pd.concat([df["a1ajor"],df["a2ajor"],df["a3ajor"],df["a1beton"],df["a2beton"],df["a3beton"],
                       df["a1gach"],df["a2gach"],df["a3gach"],df["a1sang"],df["a2sang"],df["a3sang"],
                       df["a1chub"],df["a2chub"],df["a3chub"]], axis=0)

#e2f3fd
#ffe1a0
#e07d54

plt.figure(figsize=(16, 6))
ax = sns.violinplot(x=names_below, y=sums_below,inner=None, linewidth=1, saturation=1, palette=['#e2f3fd','#ffe1a0','#e07d54','#e2f3fd','#ffe1a0','#e07d54',
                                                                                                 '#e2f3fd','#ffe1a0','#e07d54','#e2f3fd','#ffe1a0','#e07d54',
                                                                                                 '#e2f3fd','#ffe1a0','#e07d54'])
# sns.color_palette("viridis", as_cmap=True)
sns.boxplot(x=names_below, y=sums_below, saturation=1, linewidth=1.5, palette=['#015d83'], width=0.4,
            boxprops={'zorder': 2}, ax=ax)

ax.legend(frameon=False,loc='lower center',labels=["Cold","Daylight","Warm"], fontsize = 11, ncol=3)
plt.xlabel("CCT", fontsize=12)
plt.ylabel("Arousal", fontsize=12)

plt.show()