Release 0.34

docs/make_user_guide.py

@@ -306,9 +306,9 @@ def parse_module(module_name):
     start_function_lines = []
 
     # Module level classes and functions
-    numRows = len(lines)
+    num_rows = len(lines)
 
-    for row_num in range(0, numRows):
+    for row_num in range(0, num_rows):
 
         line = lines[row_num]
 
@@ -324,9 +324,9 @@ def parse_module(module_name):
             num_functions += 1
             start_function_lines.append(row_num)
 
-    start_enum_lines.append(numRows)
-    start_class_lines.append(numRows)
-    start_function_lines.append(numRows)
+    start_enum_lines.append(num_rows)
+    start_class_lines.append(num_rows)
+    start_function_lines.append(num_rows)
 
     # print("start_class_lines", start_class_lines)
 
@@ -870,7 +870,7 @@ def parse_type(p_type):
     os.remove(file_name + ".toc")
     os.remove(file_name + ".aux")
 #    os.remove(file_name + ".fls")
-    os.remove(file_name + ".fdb_latexmk")
+#    os.remove(file_name + ".fdb_latexmk")
     os.remove(file_name + ".log")
     os.remove(new_head_file)
     os.remove(new_head_file + ".bak")

financepy/__init__.py

@@ -1,7 +1,7 @@
 cr = "\n"
 
 s = "####################################################################" + cr
-s += "#  FINANCEPY BETA Version " + str('0.33') + " - This build:  03 Dec 2023 at 17:52 #" + cr
+s += "#  FINANCEPY BETA Version " + str('0.34') + " - This build:  09 Dec 2023 at 18:51 #" + cr
 s += "#     This software is distributed FREE AND WITHOUT ANY WARRANTY   #" + cr
 s += "#  Report bugs as issues at https://github.com/domokane/FinancePy  #" + cr
 s += "####################################################################"

financepy/market/curves/discount_curve_ns.py

@@ -27,14 +27,14 @@ class DiscountCurveNS(DiscountCurve):
 
     def __init__(self,
                  value_dt: Date,
-                 beta0: float,
-                 beta1: float,
-                 beta2: float,
+                 beta_0: float,
+                 beta_1: float,
+                 beta_2: float,
                  tau: float,
                  freq_type: FrequencyTypes = FrequencyTypes.CONTINUOUS,
                  dc_type: DayCountTypes = DayCountTypes.ACT_ACT_ISDA):
         """ Creation of a FinDiscountCurveNS object. Parameters are provided
-        individually for beta0, beta1, beta2 and tau. The zero rates produced
+        individually for beta_0, beta_1, beta_2 and tau. The zero rates produced
         by this parametrisation have an implicit compounding convention that
         defaults to continuous but which can be overridden. """
 
@@ -44,9 +44,9 @@ def __init__(self,
             raise FinError("Tau must be positive")
 
         self._value_dt = value_dt
-        self._beta0 = beta0
-        self._beta1 = beta1
-        self._beta2 = beta2
+        self._beta_0 = beta_0
+        self._beta_1 = beta_1
+        self._beta_2 = beta_2
         self._tau = tau
         self._freq_type = freq_type
         self._dc_type = dc_type
@@ -105,9 +105,9 @@ def _zero_rate(self,
 
         theta = t / self._tau
         e = np.exp(-theta)
-        zero_rate = self._beta0
-        zero_rate += self._beta1 * (1.0 - e) / theta
-        zero_rate += self._beta2 * ((1.0 - e) / theta - e)
+        zero_rate = self._beta_0
+        zero_rate += self._beta_1 * (1.0 - e) / theta
+        zero_rate += self._beta_2 * ((1.0 - e) / theta - e)
         return zero_rate
 
     ###########################################################################
@@ -144,9 +144,9 @@ def __repr__(self):
 
         s = label_to_string("OBJECT TYPE", type(self).__name__)
         s += label_to_string("PARAMETER", "VALUE")
-        s += label_to_string("BETA0", self._beta0)
-        s += label_to_string("BETA1", self._beta1)
-        s += label_to_string("BETA2", self._beta2)
+        s += label_to_string("beta_0", self._beta_0)
+        s += label_to_string("beta_1", self._beta_1)
+        s += label_to_string("beta_2", self._beta_2)
         s += label_to_string("TAU", self._tau)
         s += label_to_string("FREQUENCY", (self._freq_type))
         s += label_to_string("DAY_COUNT", (self._dc_type))

financepy/market/curves/interpolator.py

@@ -197,9 +197,9 @@ def _vinterpolate(xValues,
 class Interpolator():
 
     def __init__(self,
-                 interpolatorType: InterpTypes):
+                 interpolator_type: InterpTypes):
 
-        self._interp_type = interpolatorType
+        self._interp_type = interpolator_type
         self._interp_fn = None
         self._times = None
         self._dfs = None

financepy/market/volatility/equity_vol_surface.py

@@ -251,16 +251,16 @@ def __init__(self,
         self._discount_curve = discount_curve
         self._dividend_curve = dividend_curve
 
-        nExpiryDates = len(expiry_dts)
-        nStrikes = len(strikes)
+        num_expiry_dates = len(expiry_dts)
+        num_strikes = len(strikes)
         n = len(volatility_grid)
         m = len(volatility_grid[0])
 
-        if n != nExpiryDates:
-            raise FinError("1st dimension of vol grid is not nExpiryDates")
+        if n != num_expiry_dates:
+            raise FinError("1st dim of vol grid is not num_expiry_dates")
 
-        if m != nStrikes:
-            raise FinError("2nd dimension of the vol matrix is not nStrikes")
+        if m != num_strikes:
+            raise FinError("2nd dim of the vol matrix is not num_strikes")
 
         self._strikes = strikes
         self._num_strikes = len(strikes)
@@ -681,7 +681,7 @@ def check_calibration(self, verbose: bool, tol: float = 1e-6):
                 strike = self._strikes[j]
 
                 fitted_vol = self.vol_from_strike_dt(strike,
-                                                       expiry_dt)
+                                                     expiry_dt)
 
                 mkt_vol = self._volatility_grid[i][j]
 
@@ -695,7 +695,7 @@ def check_calibration(self, verbose: bool, tol: float = 1e-6):
 
 ###############################################################################
 
-    def implied_dbns(self, lowS, highS, numIntervals):
+    def implied_dbns(self, lowS, highS, num_intervals):
         """ Calculate the pdf for each tenor horizon. Returns a list of
         FinDistribution objects, one for each tenor horizon. """
 
@@ -706,7 +706,7 @@ def implied_dbns(self, lowS, highS, numIntervals):
             f = self._F_0T[iTenor]
             t = self._t_exp[iTenor]
 
-            dS = (highS - lowS) / numIntervals
+            dS = (highS - lowS) / num_intervals
 
             disDF = self._discount_curve._df(t)
             div_df = self._dividend_curve._df(t)
@@ -717,7 +717,7 @@ def implied_dbns(self, lowS, highS, numIntervals):
             Ks = []
             vols = []
 
-            for iK in range(0, numIntervals):
+            for iK in range(0, num_intervals):
 
                 k = lowS + iK*dS
 
@@ -755,11 +755,11 @@ def plot_vol_curves(self):
             ks = []
             fitted_vols = []
 
-            numIntervals = 30
+            num_intervals = 30
             K = lowK
-            dK = (highK - lowK)/numIntervals
+            dK = (highK - lowK)/num_intervals
 
-            for i in range(0, numIntervals):
+            for i in range(0, num_intervals):
 
                 ks.append(K)
                 fitted_vol = self.vol_from_strike_dt(K, expiry_dt) * 100.