Delete HelperFunctions.py

HelperFunctions.py

-from itertools import chain
-from iminuit import Minuit
-from numba import njit
-from iminuit.util import describe
-from scipy.interpolate import interp1d
-import numpy as np
-from scipy.stats import skew as sc_skew
-import matplotlib.pyplot as plt
-
-
-#HELPER FUNCTIONS
-
-
-class FakeFuncCode:
-    def __init__(self, f, prmt=None, dock=0, append=None):
-        #f can either be tuple or function object
-        self.co_varnames = describe(f)
-        self.co_argcount = len(self.co_varnames)
-        self.co_argcount -= dock
-        self.co_varnames = self.co_varnames[dock:]
-
-        if prmt is not None:  #rename parameters from the front
-            for i, p in enumerate(prmt):
-                self.co_varnames[i] = p
-
-        if isinstance(append, str): append = [append]
-
-        if append is not None:
-            old_count = self.co_argcount
-            self.co_argcount += len(append)
-            self.co_varnames = tuple(
-                list(self.co_varnames[:old_count]) +
-                append +
-                list(self.co_varnames[old_count:]))
-
-
-
-            
-def LatexFormat(value, scirange=[0.01,1000]):
-    if(np.abs(value)>scirange[0] and np.abs(value)<scirange[1]):
-        float_str = r"${:3.3f}$".format(value)
-    else:
-        try:
-            float_str = "{:3.3E}".format(value)
-            base, exponent = float_str.split("E")
-            float_str = r"${0} \times 10^{{{1}}}$".format(base, int(exponent))
-        except:
-            float_str=str(value)
-    return float_str
-
-            
-@njit
-def SelectRangeNumba(array, low_lim, hi_lim):
-    index = (array >=  low_lim) & (array <= hi_lim)
-    return array[index]
-
- 
-def EmpiricalPPF(data):
-    x = np.sort(data)
-    n = x.size
-    y = np.arange(1, n+1) / n
-    ppf = interp1d(y, x, fill_value="extrapolate")
-    return ppf
-
-
-def EmpiricalCDF(data):
-    x = np.sort(data)
-    n = x.size
-    y = np.arange(1, n+1) / n
-    ppf = interp1d(x, y, fill_value="extrapolate")
-    return ppf
-
-
-def Logify(y):
-    log_y = np.log(y)
-    min_log_y = np.min(log_y[y>0])
-
-    return np.where(y>0, log_y, min_log_y)
-
-
-def Linear(x, m, c):
-    return m*x + c
-
-def GetStats(data):
-    return np.mean(data), np.std(data), sc_skew(data)
-
-
-
-def GP_lbda(mu, sigma, gamma):
-    lbda = 0.5*(((mu*gamma)/(sigma))- 1)
-    return lbda
-
-def GP_gain(mu, sigma, gamma):
-    lbda = GP_lbda(mu, sigma, gamma)
-    gain = (sigma**2/mu)*((1 - lbda)**2)
-    return gain
-
-def GP_muGP(mu, sigma, gamma):
-    lbda = GP_lbda(mu, sigma, gamma)
-    mu_gp = (1/(1-lbda))*(mu**2/sigma**2)
-    return mu_gp
-
-
-
-def FormatExponent(ax, axis='y'):
-
-    # Change the ticklabel format to scientific format
-    ax.ticklabel_format(axis=axis, style='sci', scilimits=(-2, 2))
-
-    # Get the appropriate axis
-    if axis == 'y':
-        ax_axis = ax.yaxis
-        x_pos = 0.0
-        y_pos = 1.0
-        horizontalalignment='left'
-        verticalalignment='bottom'
-    else:
-        ax_axis = ax.xaxis
-        x_pos = 1.0
-        y_pos = -0.05
-        horizontalalignment='right'
-        verticalalignment='top'
-
-    # Run plt.tight_layout() because otherwise the offset text doesn't update
-    plt.tight_layout()
-    ##### THIS IS A BUG 
-    ##### Well, at least it's sub-optimal because you might not
-    ##### want to use tight_layout(). If anyone has a better way of 
-    ##### ensuring the offset text is updated appropriately
-    ##### please comment!
-
-    # Get the offset value
-    offset = ax_axis.get_offset_text().get_text()
-
-    if len(offset) > 0:
-        # Get that exponent value and change it into latex format
-        minus_sign = u'\u2212'
-        expo = np.float(offset.replace(minus_sign, '-').split('e')[-1])
-        offset_text = r'x$\mathregular{10^{%d}}$' %expo
-
-        # Turn off the offset text that's calculated automatically
-        ax_axis.offsetText.set_visible(False)
-
-        # Add in a text box at the top of the y axis
-        ax.text(x_pos, y_pos, offset_text, transform=ax.transAxes,
-               horizontalalignment=horizontalalignment,
-               verticalalignment=verticalalignment)
-    return ax
-
-
-
-    
-
-