mirror of
https://github.com/fjosw/pyerrors.git
synced 2025-11-04 09:35:45 +01:00
734 lines
25 KiB
Python
734 lines
25 KiB
Python
#!/usr/bin/env python
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# coding: utf-8
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import sys
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import os
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import fnmatch
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import re
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import struct
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import autograd.numpy as np # Thinly-wrapped numpy
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from ..pyerrors import Obs
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from ..fits import fit_lin
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def read_sfcf(path, prefix, name, **kwargs):
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"""Read sfcf C format from given folder structure.
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Keyword arguments
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-----------------
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im -- if True, read imaginary instead of real part of the correlation function.
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single -- if True, read a boundary-to-boundary correlation function with a single value
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b2b -- if True, read a time-dependent boundary-to-boundary correlation function
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names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
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"""
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if kwargs.get('im'):
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im = 1
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part = 'imaginary'
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else:
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im = 0
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part = 'real'
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if kwargs.get('single'):
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b2b = 1
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single = 1
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else:
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b2b = 0
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single = 0
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if kwargs.get('b2b'):
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b2b = 1
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read = 0
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T = 0
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start = 0
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ls = []
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for (dirpath, dirnames, filenames) in os.walk(path):
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ls.extend(dirnames)
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break
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if not ls:
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print('Error, directory not found')
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sys.exit()
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for exc in ls:
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if fnmatch.fnmatch(exc, prefix + '*'):
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ls = list(set(ls) - set(exc))
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if len(ls) > 1:
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ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
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replica = len(ls)
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print('Read', part, 'part of', name, 'from', prefix, ',', replica, 'replica')
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if 'names' in kwargs:
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new_names = kwargs.get('names')
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if len(new_names) != replica:
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raise Exception('Names does not have the required length', replica)
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else:
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new_names = ls
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print(replica, 'replica')
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for i, item in enumerate(ls):
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print(item)
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sub_ls = []
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for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
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sub_ls.extend(dirnames)
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break
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for exc in sub_ls:
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if fnmatch.fnmatch(exc, 'cfg*'):
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sub_ls = list(set(sub_ls) - set(exc))
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sub_ls.sort(key=lambda x: int(x[3:]))
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no_cfg = len(sub_ls)
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print(no_cfg, 'configurations')
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if i == 0:
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with open(path + '/' + item + '/' + sub_ls[0] + '/' + name) as fp:
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for k, line in enumerate(fp):
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if read == 1 and not line.strip() and k > start + 1:
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break
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if read == 1 and k >= start:
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T += 1
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if '[correlator]' in line:
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read = 1
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start = k + 7 + b2b
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T -= b2b
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deltas = []
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for j in range(T):
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deltas.append([])
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sublength = len(sub_ls)
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for j in range(T):
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deltas[j].append(np.zeros(sublength))
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for cnfg, subitem in enumerate(sub_ls):
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with open(path + '/' + item + '/' + subitem + '/'+name) as fp:
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for k, line in enumerate(fp):
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if(k >= start and k < start + T):
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floats = list(map(float, line.split()))
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deltas[k-start][i][cnfg] = floats[1 + im - single]
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result = []
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for t in range(T):
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result.append(Obs(deltas[t], new_names))
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return result
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def read_sfcf_c(path, prefix, name, quarks='.*', noffset=0, wf=0, wf2=0, **kwargs):
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"""Read sfcf c format from given folder structure.
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Arguments
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-----------------
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quarks -- Label of the quarks used in the sfcf input file
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noffset -- Offset of the source (only relevant when wavefunctions are used)
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wf -- ID of wave function
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wf2 -- ID of the second wavefunction (only relevant for boundary-to-boundary correlation functions)
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Keyword arguments
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-----------------
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im -- if True, read imaginary instead of real part of the correlation function.
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b2b -- if True, read a time-dependent boundary-to-boundary correlation function
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names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
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"""
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if kwargs.get('im'):
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im = 1
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part = 'imaginary'
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else:
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im = 0
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part = 'real'
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if kwargs.get('b2b'):
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b2b = 1
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else:
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b2b = 0
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read = 0
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T = 0
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start = 0
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ls = []
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for (dirpath, dirnames, filenames) in os.walk(path):
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ls.extend(dirnames)
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break
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if not ls:
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print('Error, directory not found')
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sys.exit()
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# Exclude folders with different names
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for exc in ls:
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if not fnmatch.fnmatch(exc, prefix+'*'):
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ls = list(set(ls) - set([exc]))
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if len(ls) > 1:
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ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
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replica = len(ls)
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if 'names' in kwargs:
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new_names = kwargs.get('names')
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if len(new_names) != replica:
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raise Exception('Names does not have the required length', replica)
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else:
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new_names = ls
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print('Read', part, 'part of', name, 'from', prefix[:-1], ',', replica, 'replica')
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for i, item in enumerate(ls):
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sub_ls = []
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for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
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sub_ls.extend(filenames)
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break
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for exc in sub_ls:
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if not fnmatch.fnmatch(exc, prefix+'*'):
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sub_ls = list(set(sub_ls) - set([exc]))
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sub_ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
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first_cfg = int(re.findall(r'\d+', sub_ls[0])[-1])
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last_cfg = len(sub_ls) + first_cfg - 1
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for cfg in range(1, len(sub_ls)):
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if int(re.findall(r'\d+', sub_ls[cfg])[-1]) != first_cfg + cfg:
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last_cfg = cfg + first_cfg - 1
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break
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no_cfg = last_cfg - first_cfg + 1
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print(item, ':', no_cfg, 'evenly spaced configurations (', first_cfg, '-', last_cfg, ') ,', len(sub_ls) - no_cfg, 'configs omitted\n')
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if i == 0:
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pattern = 'name ' + name + '\nquarks ' + quarks + '\noffset ' + str(noffset) + '\nwf ' + str(wf)
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if b2b:
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pattern += '\nwf_2 ' + str(wf2)
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with open(path+'/'+item+'/'+sub_ls[0], 'r') as file:
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content = file.read()
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match = re.search(pattern, content)
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if match:
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start_read = content.count('\n', 0, match.start()) + 5 + b2b
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end_match = re.search('\n\s*\n', content[match.start():])
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T = content[match.start():].count('\n', 0, end_match.start()) - 4 - b2b
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assert T > 0
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print(T, 'entries, starting to read in line', start_read)
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else:
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raise Exception('Correlator with pattern\n' + pattern + '\nnot found.')
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deltas = []
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for j in range(T):
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deltas.append([])
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sublength = no_cfg
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for j in range(T):
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deltas[j].append(np.zeros(sublength))
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for cfg in range(no_cfg):
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with open(path+'/'+item+'/'+sub_ls[cfg]) as fp:
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for k, line in enumerate(fp):
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if k == start_read - 5 - b2b:
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if line.strip() != 'name ' + name:
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raise Exception('Wrong format', sub_ls[cfg])
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if(k >= start_read and k < start_read + T):
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floats = list(map(float, line.split()))
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deltas[k-start_read][i][cfg] = floats[-2:][im]
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result = []
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for t in range(T):
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result.append(Obs(deltas[t], new_names))
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return result
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def read_qtop(path, prefix, **kwargs):
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"""Read qtop format from given folder structure.
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Keyword arguments
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-----------------
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target -- specifies the topological sector to be reweighted to (default 0)
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full -- if true read the charge instead of the reweighting factor.
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"""
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if 'target' in kwargs:
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target = kwargs.get('target')
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else:
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target = 0
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if kwargs.get('full'):
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full = 1
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else:
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full = 0
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ls = []
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for (dirpath, dirnames, filenames) in os.walk(path):
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ls.extend(filenames)
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break
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if not ls:
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print('Error, directory not found')
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sys.exit()
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# Exclude files with different names
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for exc in ls:
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if not fnmatch.fnmatch(exc, prefix+'*'):
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ls = list(set(ls) - set([exc]))
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if len(ls) > 1:
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ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
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replica = len(ls)
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print('Read Q_top from', prefix[:-1], ',', replica, 'replica')
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deltas = []
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for rep in range(replica):
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tmp = []
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with open(path+'/'+ls[rep]) as fp:
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for k, line in enumerate(fp):
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floats = list(map(float, line.split()))
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if full == 1:
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tmp.append(floats[1])
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else:
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if int(floats[1]) == target:
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tmp.append(1.0)
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else:
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tmp.append(0.0)
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deltas.append(np.array(tmp))
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result = Obs(deltas, [(w.split('.'))[0] for w in ls])
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return result
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def parse_array_openQCD2(d, n, size, wa, quadrupel=False):
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arr = []
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if d == 2:
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tot = 0
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for i in range(n[d-1]-1):
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if quadrupel:
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tmp = wa[tot:n[d-1]]
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tmp2 = []
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for i in range(len(tmp)):
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if i % 2 == 0:
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tmp2.append(tmp[i])
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arr.append(tmp2)
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else:
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arr.append(np.asarray(wa[tot:n[d-1]]))
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return arr
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# mimic the read_array routine of openQCD-2.0.
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# fp is the opened file handle
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# returns the dict array
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# at this point we only parse a 2d array
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# d = 2
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# n = [nfct[irw], 2*nsrc[irw]]
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def read_array_openQCD2(fp):
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t = fp.read(4)
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d = struct.unpack('i', t)[0]
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t = fp.read(4*d)
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n = struct.unpack('%di' % (d), t)
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t = fp.read(4)
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size = struct.unpack('i', t)[0]
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if size == 4:
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types = 'i'
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elif size == 8:
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types = 'd'
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elif size == 16:
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types = 'dd'
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else:
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print('Type not known!')
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m = n[0]
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for i in range(1,d):
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m *= n[i]
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t = fp.read(m*size)
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#print("struct.calc tmp = "+str(struct.calcsize('%d%s' % (m, types))))
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tmp = struct.unpack('%d%s' % (m, types), t)
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arr = parse_array_openQCD2(d, n, size, tmp, quadrupel=True)
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return {'d': d, 'n': n, 'size': size, 'arr': arr}
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def read_rwms(path, prefix, names=None, **kwargs):
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"""Read rwms format from given folder structure. Returns a list of length nrw
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Keyword arguments
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-----------------
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new_format -- if True, the array of the associated numbers of Hasenbusch factors is extracted (v>=openQCD1.6)
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r_start -- list which contains the first config to be read for each replicum
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r_stop -- list which contains the last config to be read for each replicum
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oqcd_ver_string -- openQCD version
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postfix -- postfix of the file to read, e.g. '.ms1' for openQCD-files
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"""
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#oqcd versions implemented in this method
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known_oqcd_versions = ['1.4','1.6','2.0']
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if 'oqcd_ver_string' in kwargs:
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ver_str = kwargs.get('oqcd_ver_string')
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if not (ver_str in known_oqcd_versions):
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raise Exception('Unknown openQCD version defined!')
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else: #Set defaults for openQCD Version to be version 1.4, emulate the old behaviour of this method
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if 'new_format':
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ver_str = '1.6'
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else:
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ver_str = '1.4'
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print("Working with oQCD version:" + ver_str)
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if 'postfix' in kwargs:
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postfix = kwargs.get('postfix')
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else:
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postfix = ''
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ls = []
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for (dirpath, dirnames, filenames) in os.walk(path):
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ls.extend(filenames)
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break
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if not ls:
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print('Error, directory not found')
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sys.exit()
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# Exclude files with different names
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for exc in ls:
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if not fnmatch.fnmatch(exc, prefix + '*'+postfix+'.dat'):
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ls = list(set(ls) - set([exc]))
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if len(ls) > 1:
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ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
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#ls = fnames
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#print(ls)
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replica = len(ls)
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if 'r_start' in kwargs:
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r_start = kwargs.get('r_start')
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if len(r_start) != replica:
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raise Exception('r_start does not match number of replicas')
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# Adjust Configuration numbering to python index
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r_start = [o - 1 if o else None for o in r_start]
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else:
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r_start = [None] * replica
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if 'r_stop' in kwargs:
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r_stop = kwargs.get('r_stop')
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if len(r_stop) != replica:
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raise Exception('r_stop does not match number of replicas')
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else:
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r_stop = [None] * replica
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print('Read reweighting factors from', prefix[:-1], ',', replica, 'replica', end='')
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print_err = 0
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if 'print_err' in kwargs:
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print_err = 1
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print()
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deltas = []
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for rep in range(replica):
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tmp_array = []
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with open(path+ '/' + ls[rep], 'rb') as fp:
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#header
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t = fp.read(4) # number of reweighting factors
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if rep == 0:
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nrw = struct.unpack('i', t)[0]
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if ver_str == '2.0':
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nrw = int(nrw/2)
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for k in range(nrw):
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deltas.append([])
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else:
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if ((nrw != struct.unpack('i', t)[0] and (not ver_str == '2.0')) or (nrw != struct.unpack('i', t)[0]/2 and ver_str == '2.0')):#little weird if-clause due to the /2 operation needed...
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print('Error: different number of reweighting factors for replicum', rep)
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sys.exit()
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for k in range(nrw):
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tmp_array.append([])
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# This block is necessary for openQCD1.6 and openQCD2.0 ms1 files
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nfct = []
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if ver_str in ['1.6','2.0']:
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for i in range(nrw):
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t = fp.read(4)
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nfct.append(struct.unpack('i', t)[0])
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#print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
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else:
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for i in range(nrw):
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nfct.append(1)
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nsrc = []
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for i in range(nrw):
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t = fp.read(4)
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nsrc.append(struct.unpack('i', t)[0])
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if (ver_str == '2.0'):
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if not struct.unpack('i', fp.read(4))[0] == 0:
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print('something is wrong!')
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print('nfct:', nfct, 'nsrc:', nsrc)
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#body
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while 0 < 1:
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t = fp.read(4)
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if len(t) < 4:
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break
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if print_err:
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config_no = struct.unpack('i', t)
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for i in range(nrw):
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if(ver_str == '2.0'):
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tmpd = read_array_openQCD2(fp)
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tmpd = read_array_openQCD2(fp)
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tmp_rw = tmpd['arr']
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tmp_nfct = 1.0
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for j in range(tmpd['n'][0]):
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tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw[j])))
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if print_err:
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print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw[j]))), np.std(np.exp(-np.asarray(tmp_rw[j]))))
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print('Sources:', np.exp(-np.asarray(tmp_rw[j])))
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print('Partial factor:', tmp_nfct)
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elif(ver_str=='1.6' or ver_str=='1.4'):
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tmp_nfct = 1.0
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for j in range(nfct[i]):
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t = fp.read(8 * nsrc[i])
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t = fp.read(8 * nsrc[i])
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tmp_rw = struct.unpack('d' * nsrc[i], t)
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tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw)))
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if print_err:
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print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw))), np.std(np.exp(-np.asarray(tmp_rw))))
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print('Sources:', np.exp(-np.asarray(tmp_rw)))
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print('Partial factor:', tmp_nfct)
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tmp_array[i].append(tmp_nfct)
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for k in range(nrw):
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deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
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print(',', nrw, 'reweighting factors with', nsrc, 'sources')
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result = []
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for t in range(nrw):
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if names == None:
|
|
result.append(Obs(deltas[t], [w.split(".")[0] for w in ls]))
|
|
else:
|
|
print(names)
|
|
result.append(Obs(deltas[t], names))
|
|
return result
|
|
|
|
|
|
def read_pbp(path, prefix, **kwargs):
|
|
"""Read pbp format from given folder structure. Returns a list of length nrw
|
|
|
|
Keyword arguments
|
|
-----------------
|
|
r_start -- list which contains the first config to be read for each replicum
|
|
r_stop -- list which contains the last config to be read for each replicum
|
|
|
|
"""
|
|
|
|
extract_nfct = 1
|
|
|
|
ls = []
|
|
for (dirpath, dirnames, filenames) in os.walk(path):
|
|
ls.extend(filenames)
|
|
break
|
|
|
|
if not ls:
|
|
print('Error, directory not found')
|
|
sys.exit()
|
|
|
|
# Exclude files with different names
|
|
for exc in ls:
|
|
if not fnmatch.fnmatch(exc, prefix + '*.dat'):
|
|
ls = list(set(ls) - set([exc]))
|
|
if len(ls) > 1:
|
|
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
|
replica = len(ls)
|
|
|
|
if 'r_start' in kwargs:
|
|
r_start = kwargs.get('r_start')
|
|
if len(r_start) != replica:
|
|
raise Exception('r_start does not match number of replicas')
|
|
# Adjust Configuration numbering to python index
|
|
r_start = [o - 1 if o else None for o in r_start]
|
|
else:
|
|
r_start = [None] * replica
|
|
|
|
if 'r_stop' in kwargs:
|
|
r_stop = kwargs.get('r_stop')
|
|
if len(r_stop) != replica:
|
|
raise Exception('r_stop does not match number of replicas')
|
|
else:
|
|
r_stop = [None] * replica
|
|
|
|
print('Read <bar{psi}\psi> from', prefix[:-1], ',', replica, 'replica', end='')
|
|
|
|
print_err = 0
|
|
if 'print_err' in kwargs:
|
|
print_err = 1
|
|
print()
|
|
|
|
deltas = []
|
|
|
|
for rep in range(replica):
|
|
tmp_array = []
|
|
with open(path+ '/' + ls[rep], 'rb') as fp:
|
|
|
|
#header
|
|
t = fp.read(4) # number of reweighting factors
|
|
if rep == 0:
|
|
nrw = struct.unpack('i', t)[0]
|
|
for k in range(nrw):
|
|
deltas.append([])
|
|
else:
|
|
if nrw != struct.unpack('i', t)[0]:
|
|
print('Error: different number of reweighting factors for replicum', rep)
|
|
sys.exit()
|
|
|
|
for k in range(nrw):
|
|
tmp_array.append([])
|
|
|
|
# This block is necessary for openQCD1.6 ms1 files
|
|
nfct = []
|
|
if extract_nfct == 1:
|
|
for i in range(nrw):
|
|
t = fp.read(4)
|
|
nfct.append(struct.unpack('i', t)[0])
|
|
print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
|
|
else:
|
|
for i in range(nrw):
|
|
nfct.append(1)
|
|
|
|
nsrc = []
|
|
for i in range(nrw):
|
|
t = fp.read(4)
|
|
nsrc.append(struct.unpack('i', t)[0])
|
|
|
|
#body
|
|
while 0 < 1:
|
|
t = fp.read(4)
|
|
if len(t) < 4:
|
|
break
|
|
if print_err:
|
|
config_no = struct.unpack('i', t)
|
|
for i in range(nrw):
|
|
tmp_nfct = 1.0
|
|
for j in range(nfct[i]):
|
|
t = fp.read(8 * nsrc[i])
|
|
t = fp.read(8 * nsrc[i])
|
|
tmp_rw = struct.unpack('d' * nsrc[i], t)
|
|
tmp_nfct *= np.mean(np.asarray(tmp_rw))
|
|
if print_err:
|
|
print(config_no, i, j, np.mean(np.asarray(tmp_rw)), np.std(np.asarray(tmp_rw)))
|
|
print('Sources:', np.asarray(tmp_rw))
|
|
print('Partial factor:', tmp_nfct)
|
|
tmp_array[i].append(tmp_nfct)
|
|
|
|
for k in range(nrw):
|
|
deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
|
|
|
|
print(',', nrw, '<bar{psi}\psi> with', nsrc, 'sources')
|
|
result = []
|
|
for t in range(nrw):
|
|
result.append(Obs(deltas[t], [(w.split('.'))[0] for w in ls]))
|
|
|
|
return result
|
|
|
|
|
|
def extract_t0(path, prefix, dtr_read, xmin, spatial_extent, fit_range=5, **kwargs):
|
|
"""Extract t0 from given .ms.dat files. Returns t0 as Obs.
|
|
|
|
It is assumed that all boundary effects have sufficiently decayed at x0=xmin.
|
|
The data around the zero crossing of t^2<E> - 0.3 is fitted with a linear function
|
|
from which the exact root is extracted.
|
|
Only works with openQCD v 1.2.
|
|
|
|
Parameters
|
|
----------
|
|
path -- Path to .ms.dat files
|
|
prefix -- Ensemble prefix
|
|
dtr_read -- Determines how many trajectories should be skipped when reading the ms.dat files.
|
|
Corresponds to dtr_cnfg / dtr_ms in the openQCD input file.
|
|
xmin -- First timeslice where the boundary effects have sufficiently decayed.
|
|
spatial_extent -- spatial extent of the lattice, required for normalization.
|
|
fit_range -- Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5)
|
|
|
|
Keyword arguments
|
|
-----------------
|
|
r_start -- list which contains the first config to be read for each replicum.
|
|
r_stop -- list which contains the last config to be read for each replicum.
|
|
plaquette -- If true extract the plaquette estimate of t0 instead.
|
|
"""
|
|
|
|
ls = []
|
|
for (dirpath, dirnames, filenames) in os.walk(path):
|
|
ls.extend(filenames)
|
|
break
|
|
|
|
if not ls:
|
|
print('Error, directory not found')
|
|
sys.exit()
|
|
|
|
# Exclude files with different names
|
|
for exc in ls:
|
|
if not fnmatch.fnmatch(exc, prefix + '*.ms.dat'):
|
|
ls = list(set(ls) - set([exc]))
|
|
if len(ls) > 1:
|
|
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
|
replica = len(ls)
|
|
|
|
if 'r_start' in kwargs:
|
|
r_start = kwargs.get('r_start')
|
|
if len(r_start) != replica:
|
|
raise Exception('r_start does not match number of replicas')
|
|
# Adjust Configuration numbering to python index
|
|
r_start = [o - 1 if o else None for o in r_start]
|
|
else:
|
|
r_start = [None] * replica
|
|
|
|
if 'r_stop' in kwargs:
|
|
r_stop = kwargs.get('r_stop')
|
|
if len(r_stop) != replica:
|
|
raise Exception('r_stop does not match number of replicas')
|
|
else:
|
|
r_stop = [None] * replica
|
|
|
|
print('Extract t0 from', prefix, ',', replica, 'replica')
|
|
|
|
Ysum = []
|
|
|
|
for rep in range(replica):
|
|
|
|
with open(path + '/' + ls[rep], 'rb') as fp:
|
|
# Read header
|
|
t = fp.read(12)
|
|
header = struct.unpack('iii', t)
|
|
if rep == 0:
|
|
dn = header[0]
|
|
nn = header[1]
|
|
tmax = header[2]
|
|
elif dn != header[0] or nn != header[1] or tmax != header[2]:
|
|
raise Exception('Replica parameters do not match.')
|
|
|
|
t = fp.read(8)
|
|
if rep == 0:
|
|
eps = struct.unpack('d', t)[0]
|
|
print('Step size:', eps, ', Maximal t value:', dn * (nn) * eps)
|
|
elif eps != struct.unpack('d', t)[0]:
|
|
raise Exception('Values for eps do not match among replica.')
|
|
|
|
Ysl = []
|
|
|
|
# Read body
|
|
while 0 < 1:
|
|
t = fp.read(4)
|
|
if(len(t) < 4):
|
|
break
|
|
nc = struct.unpack('i', t)[0]
|
|
|
|
t = fp.read(8 * tmax * (nn + 1))
|
|
if kwargs.get('plaquette'):
|
|
if nc % dtr_read == 0:
|
|
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
|
t = fp.read(8 * tmax * (nn + 1))
|
|
if not kwargs.get('plaquette'):
|
|
if nc % dtr_read == 0:
|
|
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
|
t = fp.read(8 * tmax * (nn + 1))
|
|
|
|
Ysum.append([])
|
|
for i, item in enumerate(Ysl):
|
|
Ysum[-1].append([np.mean(item[current + xmin:current + tmax - xmin]) for current in range(0, len(item), tmax)])
|
|
|
|
t2E_dict = {}
|
|
for n in range(nn + 1):
|
|
samples = []
|
|
for nrep, rep in enumerate(Ysum):
|
|
samples.append([])
|
|
for cnfg in rep:
|
|
samples[-1].append(cnfg[n])
|
|
samples[-1] = samples[-1][r_start[nrep]:r_stop[nrep]]
|
|
new_obs = Obs(samples, [(w.split('.'))[0] for w in ls])
|
|
t2E_dict[n * dn * eps] = (n * dn * eps) ** 2 * new_obs / (spatial_extent ** 3) - 0.3
|
|
|
|
zero_crossing = np.argmax(np.array([o.value for o in t2E_dict.values()]) > 0.0)
|
|
|
|
x = list(t2E_dict.keys())[zero_crossing - fit_range: zero_crossing + fit_range]
|
|
y = list(t2E_dict.values())[zero_crossing - fit_range: zero_crossing + fit_range]
|
|
[o.gamma_method() for o in y]
|
|
|
|
fit_result = fit_lin(x, y)
|
|
return -fit_result[0] / fit_result[1]
|