/
frequencies_histogram_type_sites.py
75 lines (56 loc) · 3.09 KB
/
frequencies_histogram_type_sites.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
# -*- coding: utf-8 -*-
"""
File name: frequencies_histogram_type_sites.py
Author: Mario Gutiérrez-Roig
Date created: 14/07/2016
Python Version: 3.4.3
Description: This code plots the frequency histogram of calibrated dates
medians. The Radiocarbon dates are imported from databases. It only takes into
account filtered dates according an archaeological criteria. Dates with a
certain percentage of marine source carbon-14 are calibrated with a mixture
of atmospherical-marine curve. Dates coming from different sites type
(Open sites, shelters, caves) are distinguished with different colors.
"""
import numpy as np
import iosacal
# Input data file name
input_file="./Data/All_dataset_F2.csv"
# Output file name
output_file="./Plots/Frequencies_F2_type_sites.pdf"
# Raw data taking some colums of the input file (fields should be delimited by ";")
raw = np.genfromtxt(input_file, delimiter=";", names=True, usecols=("ID_date", "C14Age", "Std", "Type_site", "Marine", "Marine_err", "Reservoir", "Reservoir_err", "Filtered"), dtype=('|S16', float, float, '|S16', float, float, float, float, int), skip_footer=0)
# Consider only the filtered dates
filtered = [[x[0], x[1], x[2], x[3]] for x in raw if x[8] == 1]
unfiltered = [[x[0], x[1], x[2], x[3]] for x in raw if x[8] == 0]
# Radiocarbon dates classified by site type
shelter_dates = [iosacal.core.RadiocarbonDetermination(x[1], x[2], x[0]) for x in filtered if x[3].decode('utf-8') == "Shelter" ]
cave_dates = [iosacal.core.RadiocarbonDetermination(x[1], x[2], x[0]) for x in filtered if x[3].decode('utf-8') == "Cave"]
open_dates = [iosacal.core.RadiocarbonDetermination(x[1], x[2], x[0]) for x in filtered if x[3].decode('utf-8') == "Open"]
# Calibrating dates for each site type
calshelter = [x.calibrate('intcal13') for x in shelter_dates]
calcave = [x.calibrate('intcal13') for x in cave_dates]
calopen = [x.calibrate('intcal13') for x in open_dates]
# Define bins
binwidth = 200
bins=np.arange(7000, 20001, binwidth)
# Generating Frequency Histrogram for each site type
freqs_open = iosacal.core.FreqHist(calopen, bins)
freqs_shelter = iosacal.core.FreqHist(calshelter, bins)
freqs_cave = iosacal.core.FreqHist(calcave, bins)
# x-range limits
maxx = 18000
minx = 7500
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLocator
minorLocator = AutoMinorLocator()
fig, ax = plt.subplots(figsize=(12,6))
plt.xlim(maxx, minx)
plt.tick_params(labelsize=14)
plt.xlabel("Calendar Age (BP)", fontsize=14)
plt.ylabel("Frequency", fontsize=14)
ax.xaxis.set_minor_locator(minorLocator)
p1 = plt.bar(freqs_cave.T[0] - 0.5*binwidth, freqs_cave.T[1], width=binwidth, color='grey', label="Cave")
p2 = plt.bar(freqs_shelter.T[0] - 0.5*binwidth, freqs_shelter.T[1], width=binwidth, color='#b0b2b1', bottom=freqs_cave.T[1], label="Rock Shelters")
p3 = plt.bar(freqs_open.T[0] - 0.5*binwidth, freqs_open.T[1], width=binwidth, color='white', bottom=freqs_shelter.T[1] + freqs_cave.T[1], label="Open Sites")
plt.legend(loc=2)
plt.savefig(output_file, format='pdf')