Run autopep8 linter to make code PEP8 compliant

thelyo · Nov 5, 2021 · 293eee3 · 293eee3
1 parent be79a79
commit 293eee3
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Showing 182 changed files with 3,424 additions and 3,162 deletions.
diff --git a/docs/makeUserGuide.py b/docs/makeUserGuide.py
@@ -568,9 +568,11 @@ def parseFunction(lines, startLine, endLine, className=""):
 
             missingSpaces = len(className) - len("__init__")
             if (missingSpaces >= 0):
-                functionSignature = functionSignature.replace("\n ", "\n " + " " * (missingSpaces))
+                functionSignature = functionSignature.replace(
+                    "\n ", "\n " + " " * (missingSpaces))
             else:
-                functionSignature = functionSignature.replace("\n" + " " * (-missingSpaces), "\n")
+                functionSignature = functionSignature.replace(
+                    "\n" + " " * (-missingSpaces), "\n")
 
         # Remove 'self' and any whitespace following it
         functionSignature = functionSignature.replace("self", "")
@@ -628,7 +630,6 @@ def parseFunction(lines, startLine, endLine, className=""):
             # This is because we remove trailing whitespace
             functionComment += line + " "
 
-
     if functionComment == "":
         functionComment = "PLEASE ADD A FUNCTION DESCRIPTION"
 
@@ -710,7 +711,8 @@ def extractParams(functionSignature):
     functionSignature = functionSignature.replace("%", "\%")
 
     # Remove information that isn't to do with the parameters
-    stripedSignature = functionSignature.split("(", 1)[1].replace("):", "").strip()
+    stripedSignature = functionSignature.split(
+        "(", 1)[1].replace("):", "").strip()
     if stripedSignature == "":
         # The function has no parameters
         return ""

diff --git a/financepy/__init__.py b/financepy/__init__.py
@@ -1,7 +1,7 @@
 cr = "\n"
 
 s = "####################################################################" + cr
-s += "# FINANCEPY BETA Version " + str('0.204') + " - This build:  02 Nov 2021 at 10:17 #" + cr
+s += "# FINANCEPY BETA Version " + str('0.204') + " - This build:  05 Nov 2021 at 09:38 #" + cr
 s += "#      This software is distributed FREE & WITHOUT ANY WARRANTY    #" + cr
 s += "#  Report bugs as issues at https://github.com/domokane/FinancePy  #" + cr
 s += "####################################################################"

diff --git a/financepy/market/__init__.py b/financepy/market/__init__.py
@@ -1 +0,0 @@
-

diff --git a/financepy/market/curves/discount_curve.py b/financepy/market/curves/discount_curve.py
@@ -85,11 +85,11 @@ def __init__(self,
     ###############################################################################
 
     def _zero_to_df(self,
-                  valuation_date: Date,
-                  rates: (float, np.ndarray),
-                  times: (float, np.ndarray),
-                  freq_type: FrequencyTypes,
-                  day_count_type: DayCountTypes):
+                    valuation_date: Date,
+                    rates: (float, np.ndarray),
+                    times: (float, np.ndarray),
+                    freq_type: FrequencyTypes,
+                    day_count_type: DayCountTypes):
         """ Convert a zero with a specified compounding frequency and day count
         convention to a discount factor for a single maturity date or a list of
         dates. The day count is used to calculate the elapsed year fraction."""
@@ -118,10 +118,10 @@ def _zero_to_df(self,
     ###############################################################################
 
     def _df_to_zero(self,
-                  dfs: (float, np.ndarray),
-                  maturityDts: (Date, list),
-                  freq_type: FrequencyTypes,
-                  day_count_type: DayCountTypes):
+                    dfs: (float, np.ndarray),
+                    maturityDts: (Date, list),
+                    freq_type: FrequencyTypes,
+                    day_count_type: DayCountTypes):
         """ Given a dates this first generates the discount factors. It then
         converts the discount factors to a zero rate with a chosen compounding
         frequency which may be continuous, simple, or compounded at a specific
@@ -146,7 +146,8 @@ def _df_to_zero(self,
         num_dates = len(dateList)
         zero_rates = []
 
-        times = times_from_dates(dateList, self._valuation_date, day_count_type)
+        times = times_from_dates(
+            dateList, self._valuation_date, day_count_type)
 
         for i in range(0, num_dates):
 
@@ -168,9 +169,9 @@ def _df_to_zero(self,
     ###############################################################################
 
     def zero_rate(self,
-                 dts: (list, Date),
-                 freq_type: FrequencyTypes = FrequencyTypes.CONTINUOUS,
-                 day_count_type: DayCountTypes = DayCountTypes.ACT_360):
+                  dts: (list, Date),
+                  freq_type: FrequencyTypes = FrequencyTypes.CONTINUOUS,
+                  day_count_type: DayCountTypes = DayCountTypes.ACT_360):
         """ Calculation of zero rates with specified frequency. This
         function can return a vector of zero rates given a vector of
         dates so must use Numpy functions. Default frequency is a
@@ -195,22 +196,23 @@ def zero_rate(self,
     ###############################################################################
 
     def cc_rate(self,
-               dts: (list, Date),
-               day_count_type: DayCountTypes = DayCountTypes.SIMPLE):
+                dts: (list, Date),
+                day_count_type: DayCountTypes = DayCountTypes.SIMPLE):
         """ Calculation of zero rates with continuous compounding. This
         function can return a vector of cc rates given a vector of
         dates so must use Numpy functions. """
 
-        cc_rates = self.zero_rate(dts, FrequencyTypes.CONTINUOUS, day_count_type)
+        cc_rates = self.zero_rate(
+            dts, FrequencyTypes.CONTINUOUS, day_count_type)
         return cc_rates
 
     ###############################################################################
 
     def swap_rate(self,
-                 effective_date: Date,
-                 maturity_date: (list, Date),
-                 freq_type=FrequencyTypes.ANNUAL,
-                 day_count_type: DayCountTypes = DayCountTypes.THIRTY_E_360):
+                  effective_date: Date,
+                  maturity_date: (list, Date),
+                  freq_type=FrequencyTypes.ANNUAL,
+                  day_count_type: DayCountTypes = DayCountTypes.THIRTY_E_360):
         """ Calculate the swap rate to maturity date. This is the rate paid by
         a swap that has a price of par today. This is the same as a Libor swap
         rate except that we do not do any business day adjustments. """
@@ -282,7 +284,7 @@ def swap_rate(self,
 
     def df(self,
            dt: (list, Date),
-           day_count = DayCountTypes.ACT_ACT_ISDA):
+           day_count=DayCountTypes.ACT_ACT_ISDA):
         """ Function to calculate a discount factor from a date or a
         vector of dates. The day count determines how dates get converted to 
         years. I allow this to default to ACT_ACT_ISDA unless specified. """
@@ -320,7 +322,7 @@ def _df(self,
     ###############################################################################
 
     def survival_prob(self,
-                 dt: Date):
+                      dt: Date):
         """ This returns a survival probability to a specified date based on
         the assumption that the continuously compounded rate is a default
         hazard rate in which case the survival probability is directly
@@ -450,7 +452,7 @@ def __repr__(self):
         s += label_to_string("DATES", "DISCOUNT FACTORS")
         for i in range(0, num_points):
             s += label_to_string("%12s" % self._df_dates[i],
-                               "%12.8f" % self._dfs[i])
+                                 "%12.8f" % self._dfs[i])
 
         return s
 

diff --git a/financepy/market/curves/discount_curve_flat.py b/financepy/market/curves/discount_curve_flat.py
@@ -58,7 +58,8 @@ def __init__(self,
 
         # Set up a grid of times and discount factors for functions
         self._dfs = self.df(dates)
-        self._times = times_from_dates(dates, self._valuation_date, day_count_type)
+        self._times = times_from_dates(
+            dates, self._valuation_date, day_count_type)
 
 ###############################################################################
 
@@ -90,10 +91,10 @@ def df(self,
                                     self._day_count_type)
 
         dfs = self._zero_to_df(self._valuation_date,
-                             self._flat_rate,
-                             dc_times,
-                             self._freq_type,
-                             self._day_count_type)
+                               self._flat_rate,
+                               dc_times,
+                               self._freq_type,
+                               self._day_count_type)
 
         if isinstance(dates, Date):
             return dfs[0]

diff --git a/financepy/market/curves/discount_curve_ns.py b/financepy/market/curves/discount_curve_ns.py
@@ -81,16 +81,16 @@ def zero_rate(self,
 
         # Now get the discount factors using curve conventions
         dfs = self._zero_to_df(self._valuation_date,
-                             zero_rates,
-                             dc_times,
-                             self._freq_type,
-                             self._day_count_type)
+                               zero_rates,
+                               dc_times,
+                               self._freq_type,
+                               self._day_count_type)
 
         # Convert these to zero rates in the required frequency and day count
         zero_rates = self._df_to_zero(dfs,
-                                    dates,
-                                    freq_type,
-                                    day_count_type)
+                                      dates,
+                                      freq_type,
+                                      day_count_type)
 
         return zero_rates
 
@@ -128,10 +128,10 @@ def df(self,
         zero_rates = self._zero_rate(dc_times)
 
         df = self._zero_to_df(self._valuation_date,
-                            zero_rates,
-                            dc_times,
-                            self._freq_type,
-                            self._day_count_type)
+                              zero_rates,
+                              dc_times,
+                              self._freq_type,
+                              self._day_count_type)
 
         return df
 

diff --git a/financepy/market/curves/discount_curve_nss.py b/financepy/market/curves/discount_curve_nss.py
@@ -88,16 +88,16 @@ def zero_rate(self,
 
         # Now get the discount factors using curve conventions
         dfs = self._zero_to_df(self._valuation_date,
-                             zero_rates,
-                             dc_times,
-                             self._freq_type,
-                             self._day_count_type)
+                               zero_rates,
+                               dc_times,
+                               self._freq_type,
+                               self._day_count_type)
 
         # Convert these to zero rates in the required frequency and day count
         zero_rates = self._df_to_zero(dfs,
-                                    dates,
-                                    freq_type,
-                                    day_count_type)
+                                      dates,
+                                      freq_type,
+                                      day_count_type)
 
         if isinstance(dates, Date):
             return zero_rates[0]
@@ -142,10 +142,10 @@ def df(self,
         zero_rates = self._zero_rate(dc_times)
 
         df = self._zero_to_df(self._valuation_date,
-                            zero_rates,
-                            dc_times,
-                            self._freq_type,
-                            self._day_count_type)
+                              zero_rates,
+                              dc_times,
+                              self._freq_type,
+                              self._day_count_type)
 
         if isinstance(dates, Date):
             return df[0]

diff --git a/financepy/market/curves/discount_curve_poly.py b/financepy/market/curves/discount_curve_poly.py
@@ -63,17 +63,18 @@ def zero_rate(self,
             raise FinError("Invalid Day Count type.")
 
         # Get day count times to use with curve day count convention
-        dc_times = times_from_dates(dts, self._valuation_date, self._day_count_type)
+        dc_times = times_from_dates(
+            dts, self._valuation_date, self._day_count_type)
 
         # We now get the discount factors using these times
         zero_rates = self._zero_rate(dc_times)
 
         # Now get the discount factors using curve conventions
         dfs = self._zero_to_df(self._valuation_date,
-                             zero_rates,
-                             dc_times,
-                             self._freq_type,
-                             self._day_count_type)
+                               zero_rates,
+                               dc_times,
+                               self._freq_type,
+                               self._day_count_type)
 
         # Convert these to zero rates in the required frequency and day count
         zero_rates = self._df_to_zero(dfs, dts, freq_type, day_count_type)
@@ -115,10 +116,10 @@ def df(self,
 
         # Now get the discount factors using curve conventions
         dfs = self._zero_to_df(self._valuation_date,
-                             zero_rates,
-                             dc_times,
-                             self._freq_type,
-                             self._day_count_type)
+                               zero_rates,
+                               dc_times,
+                               self._freq_type,
+                               self._day_count_type)
 
         return dfs
 

diff --git a/financepy/market/curves/discount_curve_pwf.py b/financepy/market/curves/discount_curve_pwf.py
@@ -136,10 +136,10 @@ def df(self,
         zero_rates = self._zero_rate(dc_times)
 
         df = self._zero_to_df(self._valuation_date,
-                            zero_rates,
-                            dc_times,
-                            self._freq_type,
-                            self._day_count_type)
+                              zero_rates,
+                              dc_times,
+                              self._freq_type,
+                              self._day_count_type)
 
         return df
 

diff --git a/financepy/market/curves/discount_curve_pwl.py b/financepy/market/curves/discount_curve_pwl.py
@@ -117,10 +117,10 @@ def df(self,
         zero_rates = self._zero_rate(dc_times)
 
         df = self._zero_to_df(self._valuation_date,
-                            zero_rates,
-                            dc_times,
-                            self._freq_type,
-                            self._day_count_type)
+                              zero_rates,
+                              dc_times,
+                              self._freq_type,
+                              self._day_count_type)
 
         return df
 

diff --git a/financepy/market/curves/discount_curve_zeros.py b/financepy/market/curves/discount_curve_zeros.py
@@ -70,16 +70,17 @@ def __init__(self,
         self._zero_rates = np.array(zero_rates)
         self._zero_dates = zero_dates
 
-        self._times = times_from_dates(zero_dates, valuation_date, day_count_type)
+        self._times = times_from_dates(
+            zero_dates, valuation_date, day_count_type)
 
         if test_monotonicity(self._times) is False:
             raise FinError("Times or dates are not sorted in increasing order")
 
         dfs = self._zero_to_df(self._valuation_date,
-                             self._zero_rates,
-                             self._times,
-                             self._freq_type,
-                             self._day_count_type)
+                               self._zero_rates,
+                               self._times,
+                               self._freq_type,
+                               self._day_count_type)
 
         self._dfs = np.array(dfs)
         self._interpolator = Interpolator(self._interp_type)
@@ -118,7 +119,7 @@ def __repr__(self):
         num_points = len(self._times)
         for i in range(0, num_points):
             s += label_to_string("%12s" % self._zero_dates[i],
-                               "%10.7f" % self._zero_rates[i])
+                                 "%10.7f" % self._zero_rates[i])
 
         return s
 
@@ -129,4 +130,3 @@ def _print(self):
         print(self)
 
 ###############################################################################
-
diff --git a/financepy/market/prices/__init__.py b/financepy/market/prices/__init__.py
@@ -1,2 +1 @@
 # -*- coding: utf-8 -*-
-
diff --git a/financepy/market/volatility/__init__.py b/financepy/market/volatility/__init__.py
@@ -3,5 +3,3 @@
 from .fx_vol_surface import *
 from .fx_vol_surface_plus import *
 from .ibor_cap_vol_curve import *
-
-
Original file line number	Diff line number	Diff line change
Expand Up		@@ -3,5 +3,3 @@
		from .fx_vol_surface import *
		from .fx_vol_surface_plus import *
		from .ibor_cap_vol_curve import *