def all_obs(bins512 = False, date_lim=False): if bins512: template = '/data1/Daniele/B2217+47/ephemeris/160128_profile_template_512.std' else: template = '/data1/Daniele/B2217+47/ephemeris/151109_profile_template.std' template = psrchive.Archive_load(template).get_data().flatten() dates,obs_list = cum_profile.plot_lists(template=template, bin_reduc=bins512, date_lim=date_lim) observations = np.array(obs_list) date_list = np.array(dates) #Remove bad observation #if bins512: # idx = np.where(date_list == datetime.date(2011,10,30))[0][0] # date_list = np.hstack((date_list[:idx],date_list[idx+1:])) # observations = np.vstack((observations[:idx],observations[idx+1:])) #Add earliest LOFAR observations old_date, old_obs = cum_profile.load_early_obs(template=template,bin_reduc=bins512) old_date = np.array(old_date) old_obs = np.array(old_obs) #if bins512: # old_obs = np.mean(np.reshape(old_obs,(old_obs.shape[0],old_obs.shape[1]/2,2)),axis=2) observations = np.vstack((old_obs,observations)) date_list = np.hstack((old_date,date_list)) idx = np.argsort(date_list) date_list = date_list[idx] observations = observations[idx] return date_list,observations
def weak_comp(): date_lim = [datetime.date(2013,01,01),datetime.date(2017,01,01)] dates,obs_list = cum_profile.plot_lists(template=template,date_lim=date_lim) observations = np.array(obs_list) date_list = np.array(dates) idx = np.argsort(date_list) date_list = date_list[idx] observations = observations[idx] #Average over dt avg = [] avg_date = [] avg_num = [] date0 = date_list[0] dt = 60 for idx,date in enumerate(date_list): if date - date0 < datetime.timedelta(dt): temp.append(observations[idx]) else: if len(temp) > 5: avg.append(np.mean(temp,axis=0)) if len(temp) > 5: avg_date.append(date0+datetime.timedelta(dt/2)) if len(temp) > 5: avg_num.append(len(temp)) temp = [] date0 += datetime.timedelta(dt) #avg.append(np.mean(temp,axis=0)) #avg_date.append(date0+datetime.timedelta(dt/2)) avg = np.array(avg) avg_date = np.array(avg_date)
def shifting_post(): date_lim = [datetime.date(2000,01,01),datetime.date(2013,01,01)] dates,obs_list = cum_profile.plot_lists(template=template,date_lim=date_lim) observations = np.array(obs_list) date_list = np.array(dates) idx = np.argsort(date_list) date_list = date_list[idx] observations = observations[idx] date_list = np.hstack((date_list[0:2],date_list[3],date_list[14:])) observations = np.vstack((observations[0:2],np.mean(observations[2:14],axis=0),observations[14:])) old_obs = ['L25192','L22946','L08909'] for obs in old_obs: file = '/data1/Daniele/B2217+47/Products/{obs}/{obs}_Profile.b512.dat'.format(obs=obs) prof = np.loadtxt(file,skiprows=30,usecols=[1,]) prof = normalize_profile(prof,template) observations = np.vstack((prof,observations)) date_list = np.hstack(([datetime.date(2010,07,28),datetime.date(2011,01,25),datetime.date(2011,04,13)],date_list)) observations = observations[:,200:320] for n in observations: n -= np.median(n) n /= n.max()
import numpy as np import matplotlib.pyplot as plt import psrchive import matplotlib as mpl import cum_profile import os from mpl_toolkits.axes_grid1 import make_axes_locatable plt.rc('font',size=15,weight='bold') bins512 = False if bins512: template = '/data1/Daniele/B2217+47/ephemeris/160128_profile_template_512.std' else: template = '/data1/Daniele/B2217+47/ephemeris/151109_profile_template.std' template = psrchive.Archive_load(template).get_data().flatten() dates,obs_list = cum_profile.plot_lists(template=template,bin_reduc=bins512) observations = np.array(obs_list) date_list = np.array(dates) #Remove bad observation if bins512: idx = np.where(date_list == datetime.date(2011,10,30))[0][0] date_list = np.hstack((date_list[:idx],date_list[idx+1:])) observations = np.vstack((observations[:idx],observations[idx+1:])) #Add earliest LOFAR observations old_date, old_obs = cum_profile.load_early_obs(template=template,bin_reduc=bins512) old_date = np.array(old_date) old_obs = np.array(old_obs) observations = np.vstack((old_obs,observations))