'''TAQ data plot module.
The functions in the module plot the data obtained in the
taq_data_analysis_responses_physical_short_long module.
This script requires the following modules:
* matplotlib
* numpy
* pickle
* taq_data_tools_responses_physical_short_long
The module contains the following functions:
* taq_self_response_year_avg_responses_physical_short_long_plot - plots
the self-response average for a year.
* taq_cross_response_year_avg_responses_physical_short_long_plot - plots
the cross-response average for a year.
* main - the main function of the script.
.. moduleauthor:: Juan Camilo Henao Londono <www.github.com/juanhenao21>
'''
# ----------------------------------------------------------------------------
# Modules
from matplotlib import pyplot as plt
import numpy as np
import pickle
import taq_data_tools_responses_physical_short_long
# ----------------------------------------------------------------------------
[docs]def taq_self_response_year_avg_responses_physical_short_long_plot(ticker, year,
tau, tau_p):
"""Plots the self-response average for a year.
:param ticker: string of the abbreviation of the stock to be analyzed
(i.e. 'AAPL').
:param year: string of the year to be analyzed (i.e '2008').
:param tau: integer greater than zero (i.e. 50).
:param tau_p: integer greater than zero and smaller than tau (i.e. 10).
:return: None -- The function saves the plot in a file and does not return
a value.
"""
try:
function_name = \
taq_self_response_year_avg_responses_physical_short_long_plot. \
__name__
taq_data_tools_responses_physical_short_long \
.taq_function_header_print_plot(function_name, ticker, ticker,
year, '', '')
# Load data
(self_short,
self_long,
self_response,
self_shuffle) = pickle.load(open(
f'../../taq_data/responses_physical_short_long_data_{year}/taq'
+ f'_self_response_year_responses_physical_short_long_data_tau'
+ f'_{tau}_tau_p_{tau_p}/taq_self_response_year_responses'
+ f'_physical_short_long_data_tau_{tau}_tau_p_{tau_p}_{year}'
+ f'_{ticker}.pickle', 'rb'))
# Addition of the short and long response signal
sum = np.zeros(tau)
sum[:tau_p + 1] = self_short[:tau_p + 1]
sum[tau_p + 1:] = self_short[tau_p + 1:] + self_long[tau_p + 1:]
figure = plt.figure(figsize=(16, 9))
plt.semilogx(self_short, linewidth=5, label=f'{ticker} - Short')
plt.semilogx(self_long, linewidth=5, label=f'{ticker} - Long')
plt.semilogx(sum, linewidth=5, label=f'{ticker} - Sum')
plt.semilogx(self_response, linewidth=5,
label=f'{ticker} - Self-response')
plt.semilogx(self_shuffle, linewidth=5, label=f'{ticker} - Shuffle')
plt.plot((tau_p, tau_p), (0, max(self_short)), '--',
label=r"$\tau' $ = {}".format(tau_p))
plt.legend(loc='best', fontsize=25)
plt.title('Self-response', fontsize=40)
plt.xlabel(r'$\tau \, [s]$', fontsize=35)
plt.ylabel(r'$R_{ii}(\tau)$', fontsize=35)
plt.xticks(fontsize=25)
plt.yticks(fontsize=25)
plt.xlim(1, 1000)
# plt.ylim(1.35 * 10 ** -4, 1.53 * 10 ** -4)
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.grid(True)
plt.tight_layout()
# Plotting
taq_data_tools_responses_physical_short_long \
.taq_save_plot(f'{function_name}_tau_{tau}_tau_p_{tau_p}', figure,
ticker, ticker, year, '')
return None
except FileNotFoundError as e:
print('No data')
print(e)
print()
return None
# ----------------------------------------------------------------------------
[docs]def taq_cross_response_year_avg_responses_physical_short_long_plot(ticker_i,
ticker_j,
year, tau,
tau_p):
"""Plots the cross-response average for a year.
:param ticker_i: string of the abbreviation of the stock to be analyzed
(i.e. 'AAPL')
:param ticker_j: string of the abbreviation of the stock to be analyzed
(i.e. 'AAPL')
:param year: string of the year to be analyzed (i.e '2008')
:param tau: integer greater than zero (i.e. 50).
:param tau_p: integer greater than zero and smaller than tau (i.e. 10).
:return: None -- The function saves the plot in a file and does not return
a value.
"""
if (ticker_i == ticker_j):
# Self-response
return None
else:
try:
function_name = \
taq_cross_response_year_avg_responses_physical_short_long_plot. \
__name__
taq_data_tools_responses_physical_short_long \
.taq_function_header_print_plot(function_name, ticker_i,
ticker_j, year, '', '')
# Load data
(cross_short,
cross_long,
cross_response,
cross_shuffle) = pickle.load(open(
f'../../taq_data/responses_physical_short_long_data_{year}/taq'
+ f'_cross_response_year_responses_physical_short_long_data'
+ f'_tau_{tau}_tau_p_{tau_p}/taq_cross_response_year_responses'
+ f'_physical_short_long_data_tau_{tau}_tau_p_{tau_p}_{year}'
+ f'_{ticker_i}i_{ticker_j}j.pickle', 'rb'))
# Addition of the short and long response signal
sum = np.zeros(tau)
sum[:tau_p + 1] = cross_short[:tau_p + 1]
sum[tau_p + 1:] = cross_short[tau_p + 1:] + cross_long[tau_p + 1:]
figure = plt.figure(figsize=(16, 9))
plt.semilogx(cross_short, linewidth=5,
label=f'{ticker_i} - {ticker_j} - Short')
plt.semilogx(cross_long, linewidth=5,
label=f'{ticker_i} - {ticker_j} - Long')
plt.semilogx(sum, linewidth=5,
label=f'{ticker_i} - {ticker_j} - Sum')
plt.semilogx(cross_response, linewidth=5,
label=f'{ticker_i} - {ticker_j} - Cross-response')
plt.semilogx(cross_shuffle, linewidth=5,
label=f'{ticker_i} - {ticker_j} - Shuffle')
plt.plot((tau_p, tau_p), (0, max(cross_short)), '--',
label=r"$\tau' $ = {}".format(tau_p))
plt.legend(loc='best', fontsize=25)
plt.title('Cross-response', fontsize=40)
plt.xlabel(r'$\tau \, [s]$', fontsize=35)
plt.ylabel(r'$R_{ij}(\tau)$', fontsize=35)
plt.xticks(fontsize=25)
plt.yticks(fontsize=25)
plt.xlim(1, 1000)
# plt.ylim(4 * 10 ** -5, 9 * 10 ** -5)
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.grid(True)
plt.tight_layout()
# Plotting
taq_data_tools_responses_physical_short_long \
.taq_save_plot(f'{function_name}_tau_{tau}_tau_p_{tau_p}',
figure, ticker_i, ticker_j, year, '')
return None
except FileNotFoundError as e:
print('No data')
print(e)
print()
return None
# ----------------------------------------------------------------------------
[docs]def main():
"""The main function of the script.
The main function is used to test the functions in the script.
:return: None.
"""
pass
return None
# -----------------------------------------------------------------------------
if __name__ == '__main__':
main()