From 9e0792ee08e4f7ef7a770410f93b77ac41643aa6 Mon Sep 17 00:00:00 2001 From: Marcel Milcent Date: Sun, 23 May 2021 17:24:07 -0300 Subject: [PATCH 1/2] Bumped version --- Demo.ipynb | 4 ++-- README-pypi.md | 2 +- README.md | 2 +- __init__.py | 2 +- benford/__init__.py | 2 +- setup.py | 4 ++-- 6 files changed, 8 insertions(+), 8 deletions(-) diff --git a/Demo.ipynb b/Demo.ipynb index e5a7654..e482783 100644 --- a/Demo.ipynb +++ b/Demo.ipynb @@ -11,7 +11,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Current version: 0.3.3" + "### Current version: 0.4.2" ] }, { @@ -36,7 +36,7 @@ "metadata": {}, "source": [ "### Or you can cd into the site-packages subfolder of your python distribution (or environment) and clone from there:\n", - "##### `$ git clone http://github.com/milcent/Benford_py.git`" + "##### `$ git clone http://github.com/milcent/benford_py.git`" ] }, { diff --git a/README-pypi.md b/README-pypi.md index 66a5ca0..c6b344f 100644 --- a/README-pypi.md +++ b/README-pypi.md @@ -20,7 +20,7 @@ If you find *Benford_py* useful in your research, please consider adding the fol -------------------------------------------------------------------------------- -`current version = 0.4.1` +`current version = 0.4.2` ### See [release notes](https://github.com/milcent/benford_py/releases/) for features in this and in older versions diff --git a/README.md b/README.md index 6b3cf16..35c3cf4 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ If you find *Benford_py* useful in your research, please consider adding the fol -------------------------------------------------------------------------------- -`current version = 0.4.1` +`current version = 0.4.2` ### See [release notes](https://github.com/milcent/benford_py/releases/) for features in this and in older versions diff --git a/__init__.py b/__init__.py index 907d273..ab28a02 100644 --- a/__init__.py +++ b/__init__.py @@ -1,2 +1,2 @@ '''Benfords law module''' -__version__ = "0.4.1" +__version__ = "0.4.2" diff --git a/benford/__init__.py b/benford/__init__.py index f621e4b..b47dd4d 100644 --- a/benford/__init__.py +++ b/benford/__init__.py @@ -24,4 +24,4 @@ from .benford import * -__version__ = '0.4.1' +__version__ = '0.4.2' diff --git a/setup.py b/setup.py index 95f61c3..61fe828 100644 --- a/setup.py +++ b/setup.py @@ -7,12 +7,12 @@ long_description = f.read() setup(name='benford_py', - version='0.4.1', + version='0.4.2', description='A library for testing data sets with Bendford\'s Law', long_description=long_description, long_description_content_type='text/markdown', url='https://github.com/milcent/benford_py', - download_url='https://github.com/milcent/benford_py/archive/v0.4.1.tar.gz', + download_url='https://github.com/milcent/benford_py/archive/v0.4.2.tar.gz', author='Marcel Milcent', author_email='marcelmilcent@gmail.com', license='BSD 3-Clause', From 051d6f057dd3361335355f13e1eab66a7613f637 Mon Sep 17 00:00:00 2001 From: Marcel Milcent Date: Sun, 23 May 2021 17:24:22 -0300 Subject: [PATCH 2/2] new version docs --- docs/build/doctrees/environment.pickle | Bin 155304 -> 155445 bytes docs/build/html/_modules/benford/benford.html | 73 +++++++++--------- docs/build/html/_modules/benford/stats.html | 23 +++--- docs/build/html/_modules/benford/viz.html | 56 +++++++------- 4 files changed, 78 insertions(+), 74 deletions(-) diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle index 57aa6a95a00a1e0ea746199ac82ecdf59a183549..3cd02deaa2970d86883805d44e765b0eeb129b08 100644 GIT binary patch delta 10057 zcmcgyd3amZmFGRnlDBw?<27DnE4IAFaTdqKSsm|@pS+Sdb`(XnWLvT<*;-<bd{>hRDVnu#pXNU9Ram)TE%zquTCkiu2R~V0?Rp(8l1^IEI`qv+ujUASTGQT|kiS6C~aNlkLy=i*{gQQO+{k73>&%UfWfI_?RN7 zx3<{_gfm6CMZ}4zBzai%xM^_IG;Hxn1MyMvKybZiT^qIh8nx`5inBW%!yc;#b4O$O z2^sbrA=88q7p38;jVXo4ImiHCg*%F~t3u*0vAv2qQ?Yid+heqPEMq?Kh2;reDXv}~ zq9p6MEJGHT#W84!)Ipmhx3EsTJddc_-XnyjvD_aWa^y5dVH%-eRW>}YO)DbtPQ?ao 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b/docs/build/html/_modules/benford/benford.html @@ -154,8 +154,8 @@

Source code for benford.benford

 import warnings
 from pandas import Series, DataFrame
 from numpy import arange, log10, ones, abs, cos, sin, pi, mean
-from .constants import confs, digs_dict, sec_order_dict, rev_digs, names, \
-    mad_dict, crit_chi2, KS_crit
+from .constants import CONFS, DIGS, SEC_ORDER_DIGS, REV_DIGS, TEST_NAMES, \
+    MAD_CONFORM, CRIT_CHI2, CRIT_KS
 from .checks import _check_digs_, _check_confidence_, _check_test_, \
     _check_num_array_, _check_high_Z_
 from .utils import _set_N_, input_data, prepare, \
@@ -222,9 +222,9 @@ 
Source code for benford.benford
                 self['ZN'] = (ab * (10 ** decimals)).astype(int)
         # First digits
         for col in ['F1D', 'F2D', 'F3D']:
-            temp = self.ZN.loc[self.ZN >= 10 ** (rev_digs[col] - 1)]
+            temp = self.ZN.loc[self.ZN >= 10 ** (REV_DIGS[col] - 1)]
             self[col] = (temp // 10 ** ((log10(temp).astype(int)) -
-                                        (rev_digs[col] - 1)))
+                                        (REV_DIGS[col] - 1)))
             # fill NANs with -1, which is a non-usable value for digits,
             # to be discarded later.
             self[col] = self[col].fillna(-1).astype(int)
@@ -269,9 +269,9 @@ 
Source code for benford.benford
         # create a separated Expected distributions object
         super(Test, self).__init__(_get_expected_digits_(digs))
         # create column with occurrences of the digits in the base
-        self['Counts'] = base[digs_dict[digs]].value_counts()
+        self['Counts'] = base[DIGS[digs]].value_counts()
         # create column with relative frequencies
-        self['Found'] = base[digs_dict[digs]].value_counts(normalize=True)
+        self['Found'] = base[DIGS[digs]].value_counts(normalize=True)
         self.fillna(0, inplace=True)
         # create column with absolute differences
         self['Dif'] = self.Found - self.Expected
@@ -294,9 +294,9 @@ 
Source code for benford.benford
         self.sec_order = sec_order
 
         if sec_order:
-            self.name = names[sec_order_dict[digs]]
+            self.name = TEST_NAMES[SEC_ORDER_DIGS[digs]]
         else:
-            self.name = names[digs_dict[digs]]
+            self.name = TEST_NAMES[DIGS[digs]]
 
 
[docs]    def update_confidence(self, new_conf, check=True):
         """Sets a new confidence level for the Benford object, so as to be used to
@@ -317,11 +317,12 @@ 
Source code for benford.benford
     def critical_values(self):
         """dict: a dictionary with the critical values for the test at hand,
             according to the current confidence level."""
-        return {'Z': confs[self.confidence],
-                'KS': KS_crit[self.confidence] / (self.N ** 0.5),
-                'chi2': crit_chi2[self.ddf][self.confidence],
-                'MAD': mad_dict[self.digs]
-                }
+        crit_ks = CRIT_KS[self.confidence] / (self.N ** 0.5) if self.confidence\
+            else None
+        return {'Z': CONFS[self.confidence],
+                'KS': crit_ks,
+                'chi2': CRIT_CHI2[self.ddf][self.confidence],
+                'MAD': MAD_CONFORM[self.digs]}
 
 
[docs]    def show_plot(self, save_plot=None, save_plot_kwargs=None):
         """Draws the test plot.
@@ -338,7 +339,7 @@ 
Source code for benford.benford
         """
         x, figsize, text_x = _get_plot_args(self.digs)
         plot_digs(self, x=x, y_Exp=self.Expected, y_Found=self.Found,
-                    N=self.N, figsize=figsize, conf_Z=confs[self.confidence],
+                    N=self.N, figsize=figsize, conf_Z=CONFS[self.confidence],
                     text_x=text_x, save_plot=save_plot, save_plot_kwargs=save_plot_kwargs
                     )

 
@@ -395,9 +396,9 @@ 
Source code for benford.benford
         #: Confidence level to consider when setting some critical values
         self.confidence = None
         # (int): numerical representation of the test at hand
-        self.digs = rev_digs[test]
+        self.digs = REV_DIGS[test]
         # (str): the name of the Summation test.
-        self.name = names[f'{test}_Summ']
+        self.name = TEST_NAMES[f'{test}_Summ']
 
 
[docs]    def show_plot(self, save_plot=None, save_plot_kwargs=None):
         """Draws the Summation test plot
@@ -591,7 +592,7 @@ 
Source code for benford.benford
         self.tests = []
 
         # Create a DatFrame for each Test
-        for key, val in digs_dict.items():
+        for key, val in DIGS.items():
             test = Test(self.base.loc[self.base[val] != -1],
                         digs=key, confidence=self.confidence,
                         limit_N=self.limit_N)
@@ -599,9 +600,9 @@ 
Source code for benford.benford
             self.tests.append(val)
         # dict with the numbers of discarded entries for each test column
         self._discarded = {key: val for (key, val) in
-                           zip(digs_dict.values(),
+                           zip(DIGS.values(),
                                [len(self.base[col].loc[self.base[col] == -1])
-                                for col in digs_dict.values()])}
+                                for col in DIGS.values()])}
 
         if self.verbose:
             print('\n', ' Benford Object Instantiated '.center(50, '#'), '\n')
@@ -684,18 +685,18 @@ 
Source code for benford.benford
         #: Base instance of the differences between the ordered sample
         self.base_sec = Base(subtract_sorted(self.chosen),
                              decimals=self.decimals, sign=self.sign)
-        for key, val in digs_dict.items():
+        for key, val in DIGS.items():
             test = Test(self.base_sec.loc[self.base_sec[val] != -1],
                         digs=key, confidence=self.confidence,
                         limit_N=self.limit_N, sec_order=True)
-            setattr(self, sec_order_dict[key], test)
+            setattr(self, SEC_ORDER_DIGS[key], test)
             self.tests.append(f'{val}_sec')
             # No need to populate crit_vals dict, since they are the
             # same and do not depend on N
             self._discarded_sec = {key: val for (key, val) in zip(
-                                   sec_order_dict.values(),
+                                   SEC_ORDER_DIGS.values(),
                                    [sum(self.base_sec[col] == -1) for col in
-                                    digs_dict.values()])}
+                                    DIGS.values()])}
         if self.verbose:
             print(f'\nSecond order tests run in {len(self.base_sec)} '
                   'registries.\n\nNumber of discarded entries for second order'
@@ -878,10 +879,10 @@ 
Source code for benford.benford
         # Check on the possible values for confidence levels
         confidence = _check_confidence_(confidence)
         # Check on possible digits
-        _check_test_(digs)
+        _check_digs_(digs)
 
         temp = self.loc[self.ZN >= 10 ** (digs - 1)]
-        temp[digs_dict[digs]] = (temp.ZN // 10 ** ((log10(temp.ZN).astype(
+        temp[DIGS[digs]] = (temp.ZN // 10 ** ((log10(temp.ZN).astype(
                                                    int)) - (digs - 1))).astype(
                                                        int)
         n, m = 10 ** (digs - 1), 10 ** (digs)
@@ -890,10 +891,10 @@ 
Source code for benford.benford
         if simple:
             self.verbose = False
             show_plot = False
-            df = prepare(temp[digs_dict[digs]], digs, limit_N=limit_N,
+            df = prepare(temp[DIGS[digs]], digs, limit_N=limit_N,
                          simple=True)
         else:
-            N, df = prepare(temp[digs_dict[digs]], digs, limit_N=limit_N,
+            N, df = prepare(temp[DIGS[digs]], digs, limit_N=limit_N,
                             simple=False)
 
         if self.verbose:
@@ -901,7 +902,7 @@ 
Source code for benford.benford
                   f"Discarded {len(self) - len(temp)} records < {10 ** (digs - 1)}"
                   " after preparation.")
             if confidence is not None:
-                _inform_(df, high_Z=high_Z, conf=confs[confidence])
+                _inform_(df, high_Z=high_Z, conf=CONFS[confidence])
 
         # Mean absolute difference
         if MAD:
@@ -939,7 +940,7 @@ 
Source code for benford.benford
         if show_plot:
             plot_digs(df, x=x, y_Exp=df.Expected, y_Found=df.Found, N=N,
                        figsize=(2 * (digs ** 2 + 5), 1.5 * (digs ** 2 + 5)),
-                       conf_Z=confs[confidence], save_plot=save_plot,
+                       conf_Z=CONFS[confidence], save_plot=save_plot,
                        save_plot_kwargs=save_plot_kwargs)
         if ret_df:
             return df

@@ -999,7 +1000,7 @@ 
Source code for benford.benford
         """
         confidence = _check_confidence_(confidence)
 
-        conf = confs[confidence]
+        conf = CONFS[confidence]
 
         temp = self.loc[self.ZN >= 10, :]
         temp['SD'] = (temp.ZN // 10 ** ((log10(temp.ZN)).astype(
@@ -1110,7 +1111,7 @@ 
Source code for benford.benford
                 the differences
         """
         confidence = _check_confidence_(confidence)
-        conf = confs[confidence]
+        conf = CONFS[confidence]
 
         temp = self.loc[self.ZN >= 1000]
         temp['L2D'] = temp.ZN % 100
@@ -1196,7 +1197,7 @@ 
Source code for benford.benford
         if digs == 1:
             top = 9
         # Call the dict for F1D, F2D, F3D
-        d = digs_dict[digs]
+        d = DIGS[digs]
         if d not in self.columns:
             self[d] = self.ZN.astype(str).str[:digs].astype(int)
         # Call the expected proportion according to digs
@@ -1396,7 +1397,7 @@ 
Source code for benford.benford
 
         Exp, ind = prep_to_roll(data, self.test)
 
-        self.roll_series = data[digs_dict[test]].rolling(
+        self.roll_series = data[DIGS[test]].rolling(
                                 window=window).apply(mad_to_roll, 
                                     args=(Exp, ind), raw=False)
         self.roll_series.dropna(inplace=True)
@@ -1448,7 +1449,7 @@ 
Source code for benford.benford
 
         Exp, ind = prep_to_roll(data, test)
 
-        self.roll_series = data[digs_dict[test]].rolling(
+        self.roll_series = data[DIGS[test]].rolling(
                                 window=window).apply(mse_to_roll, 
                                     args=(Exp, ind), raw=False)
         self.roll_series.dropna(inplace=True)
@@ -1937,12 +1938,12 @@ 
Source code for benford.benford
 
     start = Source(data, sign=sign, decimals=decimals, verbose=verbose)
     temp = start.loc[start.ZN >= 10 ** (test - 1)]
-    temp[digs_dict[test]] = (temp.ZN // 10 ** ((log10(temp.ZN).astype(
+    temp[DIGS[test]] = (temp.ZN // 10 ** ((log10(temp.ZN).astype(
                                                 int)) - (test - 1))).astype(
                                                     int)
     li = 1. / (9 * (10 ** (test - 1)))
 
-    df = temp.groupby(digs_dict[test]).sum()
+    df = temp.groupby(DIGS[test]).sum()
     return mean(abs(df.ZN / df.ZN.sum() - li))

 
 
diff --git a/docs/build/html/_modules/benford/stats.html b/docs/build/html/_modules/benford/stats.html
index f75f844..a83bd66 100644
--- a/docs/build/html/_modules/benford/stats.html
+++ b/docs/build/html/_modules/benford/stats.html
@@ -151,8 +151,8 @@
            

             
   
Source code for benford.stats
-from numpy import sqrt, log, where
-from .constants import crit_chi2, KS_crit, mad_dict, digs_dict
+from numpy import errstate, log, sqrt, where
+from .constants import CRIT_CHI2, CRIT_KS, MAD_CONFORM, DIGS
 
 
 
[docs]def Z_score(frame, N):
@@ -194,7 +194,7 @@ 
Source code for benford.stats
         exp_counts = frame.Counts.sum() * frame.Expected
         dif_counts = frame.Counts - exp_counts
         found_chi = (dif_counts ** 2 / exp_counts).sum()
-        crit_chi = crit_chi2[ddf][confidence]
+        crit_chi = CRIT_CHI2[ddf][confidence]
         if verbose:
             print(f"\nThe Chi-square statistic is {found_chi:.4f}.\n"
                   f"Critical Chi-square for this series: {crit_chi}.")
@@ -241,7 +241,7 @@ 
Source code for benford.stats
         # finding the supremum - the largest cumul dist difference
         suprem = ((ks_frame.Found - ks_frame.Expected).abs()).max()
         # calculating the crittical value according to confidence
-        crit_KS = KS_crit[confidence] / sqrt(N)
+        crit_KS = CRIT_KS[confidence] / sqrt(N)
 
         if verbose:
             print(f"\nThe Kolmogorov-Smirnov statistic is {suprem:.4f}.\n"
@@ -285,11 +285,11 @@ 
Source code for benford.stats
         print(f"\nThe Mean Absolute Deviation is {mad}")
 
         if test != -2:
-            print(f"For the {mad_dict[digs_dict[test]]}:\n\
-            - 0.0000 to {mad_dict[test][0]}: Close Conformity\n\
-            - {mad_dict[test][0]} to {mad_dict[test][1]}: Acceptable Conformity\n\
-            - {mad_dict[test][1]} to {mad_dict[test][2]}: Marginally Acceptable Conformity\n\
-            - Above {mad_dict[test][2]}: Nonconformity")
+            print(f"For the {MAD_CONFORM[DIGS[test]]}:\n\
+            - 0.0000 to {MAD_CONFORM[test][0]}: Close Conformity\n\
+            - {MAD_CONFORM[test][0]} to {MAD_CONFORM[test][1]}: Acceptable Conformity\n\
+            - {MAD_CONFORM[test][1]} to {MAD_CONFORM[test][2]}: Marginally Acceptable Conformity\n\
+            - Above {MAD_CONFORM[test][2]}: Nonconformity")
         else:
             pass
     return mad

@@ -358,7 +358,10 @@ 
Source code for benford.stats
     Returns:
         kulb_leib_diverg (float)        
     """
-    return (log((dist_1 / dist_2), where=(dist_1 != 0)) * dist_1).sum()
+    # ignore divide by zero warning in np.where
+    with errstate(divide='ignore'):
+        kl_d = (log((dist_1 / dist_2), where=(dist_1 != 0)) * dist_1).sum()
+    return kl_d
 

 
            

diff --git a/docs/build/html/_modules/benford/viz.html b/docs/build/html/_modules/benford/viz.html
index 1548a0e..8558559 100644
--- a/docs/build/html/_modules/benford/viz.html
+++ b/docs/build/html/_modules/benford/viz.html
@@ -154,7 +154,7 @@ 
Source code for benford.viz
 from numpy import array, arange, maximum, sqrt, ones
 import matplotlib.pyplot as plt
 from matplotlib.text import Annotation
-from .constants import colors, mad_dict
+from .constants import COLORS, MAD_CONFORM
 
 
 
[docs]def plot_expected(df, digs, save_plot=None, save_plot_kwargs=None):
@@ -183,9 +183,9 @@ 
Source code for benford.viz
     plt.title('Expected Benford Distributions', size='xx-large')
     plt.xlabel(df.index.name, size='x-large')
     plt.ylabel('Distribution (%)', size='x-large')
-    ax.set_facecolor(colors['b'])
+    ax.set_facecolor(COLORS['b'])
     ax.set_ylim(0, y_max)
-    ax.bar(df.index, df.Expected * 100, color=colors['t'], align='center')
+    ax.bar(df.index, df.Expected * 100, color=COLORS['t'], align='center')
     ax.set_xticks(df.index)
     ax.set_xticklabels(df.index)
 
@@ -254,22 +254,22 @@ 
Source code for benford.viz
         lower_zeros = array([0]*len(upper))
         lower = maximum(y_Exp - sig - (1 / (2 * N)), lower_zeros)
         u = (y_Found < lower) | (y_Found > upper)
-        c = array([colors['m']] * len(u))
-        c[u] = colors['af']
+        c = array([COLORS['m']] * len(u))
+        c[u] = COLORS['af']
         lower *= 100.
         upper *= 100.
-        ax.plot(x, upper, color=colors['s'], zorder=5)
-        ax.plot(x, lower, color=colors['s'], zorder=5)
-        ax.fill_between(x, upper, lower, color=colors['s'],
-                        alpha=.3, label='Conf')
+        ax.plot(x, upper, color=COLORS['s'], zorder=5)
+        ax.plot(x, lower, color=COLORS['s'], zorder=5)
+        ax.fill_between(x, upper, lower, color=COLORS['s'],
+                        alpha=.3, label='Conf')
     else:
-        c = colors['m']
+        c = COLORS['m']
     ax.bar(x, y_Found * 100., color=c, label='Found', zorder=3, align='center')
-    ax.plot(x, y_Exp * 100., color=colors['s'], linewidth=2.5,
+    ax.plot(x, y_Exp * 100., color=COLORS['s'], linewidth=2.5,
             label='Benford', zorder=4)
     ax.set_xticks(x)
     ax.set_xticklabels(x, rotation=rotation)
-    ax.set_facecolor(colors['b'])
+    ax.set_facecolor(COLORS['b'])
     if text_x:
         ind = array(df.index).astype(str)
         ind[:10] = array(['00', '01', '02', '03', '04', '05',
@@ -308,13 +308,13 @@ 
Source code for benford.viz
     plt.title('Expected vs. Found Sums')
     plt.xlabel('Digits')
     plt.ylabel('Sums')
-    ax.bar(x, df.Percent, color=colors['m'],
+    ax.bar(x, df.Percent, color=COLORS['m'],
            label='Found Sums', zorder=3, align='center')
     ax.set_xlim(x[0] - 1, x[-1] + 1)
-    ax.axhline(li, color=colors['s'], linewidth=2, label='Expected', zorder=4)
+    ax.axhline(li, color=COLORS['s'], linewidth=2, label='Expected', zorder=4)
     ax.set_xticks(x)
     ax.set_xticklabels(x, rotation=rotation)
-    ax.set_facecolor(colors['b'])
+    ax.set_facecolor(COLORS['b'])
     if text_x:
         ind = array(x).astype(str)
         ind[:10] = array(['00', '01', '02', '03', '04', '05',
@@ -351,12 +351,12 @@ 
Source code for benford.viz
     fig = plt.figure(figsize=figsize)
     ax = fig.add_subplot(111)
     ax.plot(x, col.sort_values(), linestyle='--',
-            color=colors['s'], linewidth=3, label='Mantissas')
-    ax.plot(x, n.cumsum(), color=colors['m'],
+            color=COLORS['s'], linewidth=3, label='Mantissas')
+    ax.plot(x, n.cumsum(), color=COLORS['m'],
             linewidth=2, label='Expected')
     plt.ylim((0, 1.))
     plt.xlim((1, ld + 1))
-    ax.set_facecolor(colors['b'])
+    ax.set_facecolor(COLORS['b'])
     ax.set_title("Ordered Mantissas")
     plt.legend(loc='upper left')
 
@@ -388,11 +388,11 @@ 
Source code for benford.viz
     """
     fig = plt.figure(figsize=(figsize, figsize))
     ax = plt.subplot()
-    ax.set_facecolor(colors['b'])
+    ax.set_facecolor(COLORS['b'])
     ax.scatter(df.mant_x, df.mant_y, label="ARC TEST",
-               color=colors['m'])
+               color=COLORS['m'])
     ax.scatter(gravity_center[0], gravity_center[1],
-               color=colors['s'])
+               color=COLORS['s'])
     text_annotation = Annotation(
         "  Gravity Center: "
         f"x({round(gravity_center[0], 3)}),"
@@ -428,8 +428,8 @@ 
Source code for benford.viz
             https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html
     """
     fig, ax = plt.subplots(figsize=figsize)
-    ax.set_facecolor(colors['b'])
-    ax.plot(roll_series, color=colors['m'])
+    ax.set_facecolor(COLORS['b'])
+    ax.plot(roll_series, color=COLORS['m'])
 
     if save_plot:
         if not save_plot_kwargs:
@@ -452,13 +452,13 @@ 
Source code for benford.viz
             https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html
     """
     fig, ax = plt.subplots(figsize=figsize)
-    ax.set_facecolor(colors['b'])
-    ax.plot(roll_mad.roll_series, color=colors['m'])
+    ax.set_facecolor(COLORS['b'])
+    ax.plot(roll_mad.roll_series, color=COLORS['m'])
 
     if roll_mad.test != -2:
-        plt.axhline(y=mad_dict[roll_mad.test][0], color=colors['af'], linewidth=3)
-        plt.axhline(y=mad_dict[roll_mad.test][1], color=colors['h2'], linewidth=3)
-        plt.axhline(y=mad_dict[roll_mad.test][2], color=colors['s'], linewidth=3)
+        plt.axhline(y=MAD_CONFORM[roll_mad.test][0], color=COLORS['af'], linewidth=3)
+        plt.axhline(y=MAD_CONFORM[roll_mad.test][1], color=COLORS['h2'], linewidth=3)
+        plt.axhline(y=MAD_CONFORM[roll_mad.test][2], color=COLORS['s'], linewidth=3)
 
     if save_plot:
         if not save_plot_kwargs: