ran RTL update Oct 23

pytest/test_risktools.py

@@ -347,7 +347,7 @@ def test_swap_irs():
     # a = 85085.84
     # b = round(1.015174, 4)
 
-    # ac = _load_json("swapIRS.json")
+    # ac = _load_json("./data/swapIRS.json")
     # ac.dates = pd.to_datetime(ac.dates)
 
     # usSwapCurves = rt.data.open_data("usSwapCurves")
@@ -443,46 +443,17 @@ def test_stl_decomposition():
 
 
 def test_get_eia_df():
-    pass
-    # ac = _load_json("eia2tidy1.json")
-    # ac = ac[["date", "value"]].set_index("date").sort_index().value
-    # ts = rt.get_eia_df("PET.MCRFPTX2.M", key=up["eia"])
-    # ts = ts[["date", "value"]].set_index("date").sort_index().value
-    # ts = ts[ac.index.min() : ac.index.max()]
-
-    # # assert ac.equals(ts), "get_eia_df Test 1 failed"
-    # pd.testing.assert_series_equal(ac, ts)
-
-    # ac = _load_json("eia2tidy2.json")
-    # ac = ac.set_index(["series", "date"]).sort_index().value
-    # ts = rt.get_eia_df(
-    #     ["PET.W_EPC0_SAX_YCUOK_MBBL.W", "NG.NW2_EPG0_SWO_R48_BCF.W"], key=up["eia"]
-    # )
-    # ts.date = pd.to_datetime(ts.date)
-    # ts.table_name = ts.table_name.map(
-    #     {
-    #         "Cushing, OK Ending Stocks excluding SPR of Crude Oil, Weekly": "CrudeCushing",
-    #         "Weekly Lower 48 States Natural Gas Working Underground Storage, Weekly": "NGLower48",
-    #     }
-    # )
+    ts = rt.get_eia_df("PET.MCRFPTX2.M", key=up["eia"])
 
-    # ts = (
-    #     ts.rename({"table_name": "series"}, axis=1)
-    #     .set_index(["series", "date"])
-    #     .sort_index()
-    #     .value
-    # )
+    assert ts.shape[0] > 0, "get_eia_df Test 1 failed"
 
-    # cmin = ac["CrudeCushing"].index.min()
-    # cmax = ac["CrudeCushing"].index.max()
+    ts = rt.get_eia_df(
+        ["PET.W_EPC0_SAX_YCUOK_MBBL.W", "NG.NW2_EPG0_SWO_R48_BCF.W"], key=up["eia"]
+    )
 
-    # nmin = ac["NGLower48"].index.min()
-    # nmax = ac["NGLower48"].index.max()
+    assert ts.shape[0] > 0, "get_eia_df Test 2 failed"
 
-    # ts = ts.loc[("CrudeCushing", slice(cmin, cmax))].append(
-    #     ts.loc[("NGLower48", slice(nmin, nmax))]
-    # )
-    # pd.testing.assert_series_equal(ac, ts)
+    assert ts.shape[1] == 4, "get_eia_df Test 3 failed"
 
 
 def test_chart_spreads():

src/risktools/_main_functions.py

@@ -63,7 +63,6 @@ def ir_df_us(quandl_key=None, ir_sens=0.01, date=None):
         sdt = edt - _pd.DateOffset(days=30)
 
     fedsfund = _quandl.get("FED/RIFSPFF_N_D", start_date=sdt, end_date=edt).dropna()
-    # print(fedsfund)
     fedsfund["FedsFunds0"] = _np.log((1 + fedsfund.Value / 360) ** 365)
     fedsfund.drop("Value", axis=1, inplace=True)
 
@@ -634,7 +633,6 @@ def npv(
         )
 
     if break_even == True:
-        print("test")
         disc_factors["yield"] = be_yield
         disc_factors["discountfactor"] = _np.exp(
             -disc_factors["yield"] * disc_factors.maturity

src/risktools/_sims.py

@@ -685,7 +685,7 @@ def _fitOU_MLE(spread):
         - 2 * mu * (1 - a) * (Sy - a * Sx)
         + (n - 1) * mu**2 * (1 - a) ** 2
     ) / (n - 1)
-    print((sigmah2) * 2 * theta / (1 - a**2))
+    # print((sigmah2) * 2 * theta / (1 - a**2))
     sigma = _np.sqrt((sigmah2) * 2 * theta / (1 - a**2))
     theta = {"theta": theta, "mu": mu, "annualized_sigma": sigma}
 

src/risktools/_swap.py

@@ -142,7 +142,7 @@ def swap_irs(
             / 365,  # calc days to maturity from trade_date
         }
     )
-    print(df)
+
     disc = _interpolate.splrep(disc_curve["times"], disc_curve["discounts"])
     df["disc"] = _interpolate.splev(df.times, disc)
 

src/risktools/data/__init__.py

@@ -155,6 +155,7 @@ def _norm_df(fn):
             cf = _pd.DataFrame()
             for sec_key in tmp[key].keys():
                 tf = _pd.DataFrame.from_records(tmp[key][sec_key])
+                tf.columns = tf.columns.str.replace("\.+", "_", regex=True)
                 cols = list(tf.columns)
                 tf['assay'] = sec_key
                 tf = tf[['assay', *cols]]
@@ -176,6 +177,7 @@ def _load_data(fn):
     try:
         df = _pd.DataFrame.from_records(dd)
         df = _try_dates(df)
+        df.columns = df.columns.str.replace("\.+", "_", regex=True)
         return df
     except:
         pass
@@ -184,11 +186,13 @@ def _load_data(fn):
 
         try:
             dd[key] = _pd.DataFrame.from_records(dd[key])
+            dd[key].columns = dd[key].columns.str.replace("\.+", "_", regex=True)
         except:
             pass
 
         try:
             dd[key] = _pd.DataFrame(dd[key])
+            dd[key].columns = dd[key].columns.str.replace("\.+", "_", regex=True)
         except:
             pass
 
@@ -199,7 +203,7 @@ def _load_data(fn):
         #     dd[key] = _np.array(dd[key])
         # except:
         #     pass
-
+    # dd.columns = dd.columns.str.replace("\.+", "_", regex=True)
     return dd
 
 
@@ -225,7 +229,7 @@ def _read_curves(fn):
             dd[key] = _np.array(dd[key])
 
         if isinstance(dd[key], dict) == True:
-            print(dd[key])
+            # print(dd[key])
             for k in dd[key].keys():
                 dd[key][k] = _np.array(dd[key][k])
 

src/risktools/data/test.ipynb

@@ -190,7 +190,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   },
   "orig_nbformat": 4,
   "vscode": {

src/risktools/data/tsQuotes.json

@@ -1 +1 @@
-{"d1w":[0.053],"d1m":[0.0531],"d3m":[0.0538],"s2y":[0.0482],"s3y":[0.0449],"s5y":[0.0417],"s7y":[0.0405],"s10y":[0.0398],"s15y":[0.0397],"s30y":[0.037],"fut1":[94.7625],"fut2":[94.68],"fut3":[94.6375],"fut4":[94.6],"fut5":[94.575],"fut6":[94.58],"fut7":[94.62],"fut8":[94.66]}
+{"d1w":[0.053],"d1m":[0.0534],"d3m":[0.0541],"s2y":[0.0496],"s3y":[0.0473],"s5y":[0.0459],"s7y":[0.0457],"s10y":[0.0457],"s15y":[0.0461],"s30y":[0.0437],"fut1":[94.6625],"fut2":[94.6525],"fut3":[94.625],"fut4":[94.6],"fut5":[94.575],"fut6":[94.575],"fut7":[94.6],"fut8":[94.665]}