From 469b79451f8d9309b4f96504461a998591e1cffd Mon Sep 17 00:00:00 2001
From: mbi6245 <mbi6245@uw.edu>
Date: Tue, 14 May 2024 12:15:09 -0700
Subject: [PATCH] fix bugs in transforms.py, tests now passing

---
 .github/workflows/build.yml |  1 +
 src/distrx/transforms.py    | 73 +++++++++++++++++++++++++------------
 2 files changed, 50 insertions(+), 24 deletions(-)

diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index bf1a895..74cb5e1 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -17,6 +17,7 @@ jobs:
       run: python -m pip install .[test] --upgrade pip --no-cache-dir
     - name: Test with pytest
       run: pytest # --cov=./ --cov-report=xml
+      # repository > settings > github apps > configure codecov
 
     # - name: Build package distribution
     #   if: startsWith(github.ref, 'refs/tags')
diff --git a/src/distrx/transforms.py b/src/distrx/transforms.py
index ec985a3..96e0384 100644
--- a/src/distrx/transforms.py
+++ b/src/distrx/transforms.py
@@ -9,45 +9,64 @@
 * Add decorators for accepting floats or vectors
 
 """
-from typing import Tuple
+
 import warnings
+from typing import Tuple
 
 import numpy as np
 import numpy.typing as npt
 
 
 class FirstOrder:
-    def __init__(self, transform: str, mu: npt.ArrayLike, sigma: npt.ArrayLike) -> None:
+    def __init__(
+        self, transform: str, mu: npt.ArrayLike, sigma: npt.ArrayLike
+    ) -> None:
         # you may be able to make transform a field, though it might not be necessary
-        # TODO: DSLETE DS.STORE
-        # TODO: USE RUFF LINTER
         # TODO: put each parameter on its separate line if theres a lot (reference pypkg style guide)
-        self.transform = input(transform)
+        self.transform = transform
         self.mu = mu
         self.sigma = sigma
         match self.transform:
             case "log":
-                self.mu_trans, self.sigma_trans = self.log_trans(self.mu, self.sigma)
+                self.mu_trans, self.sigma_trans = self.log_trans(
+                    self.mu, self.sigma
+                )
             case "logit":
-                self.mu_trans, self.sigma_trans = self.logit_trans(self.mu, self.sigma)
+                self.mu_trans, self.sigma_trans = self.logit_trans(
+                    self.mu, self.sigma
+                )
             case "exp":
-                self.mu_trans, self.sigma_trans = self.exp_trans(self.mu, self.sigma)
+                self.mu_trans, self.sigma_trans = self.exp_trans(
+                    self.mu, self.sigma
+                )
             case "expit":
-                self.mu_trans, self.sigma_trans = self.expit_trans(self.mu, self.sigma)
+                self.mu_trans, self.sigma_trans = self.expit_trans(
+                    self.mu, self.sigma
+                )
             case _:
                 raise ValueError(f"Invalid transform '{self.transform}'.")
 
-    def log_trans(self, mu: npt.ArrayLike, sigma: npt.ArrayLike) -> Tuple[np.ndarray, np.ndarray]:
+    def log_trans(
+        self, mu: npt.ArrayLike, sigma: npt.ArrayLike
+    ) -> Tuple[np.ndarray, np.ndarray]:
         return np.log(mu), sigma / mu
 
-    def logit_trans(self, mu: npt.ArrayLike, sigma: npt.ArrayLike) -> Tuple[np.ndarray, np.ndarray]:
+    def logit_trans(
+        self, mu: npt.ArrayLike, sigma: npt.ArrayLike
+    ) -> Tuple[np.ndarray, np.ndarray]:
         return np.log(mu / (1.0 - mu)), sigma / (mu * (1.0 - mu))
 
-    def exp_trans(self, mu: npt.ArrayLike, sigma: npt.ArrayLike) -> Tuple[np.ndarray, np.ndarray]:
-        return np.exp(mu), np.exp(mu)
+    def exp_trans(
+        self, mu: npt.ArrayLike, sigma: npt.ArrayLike
+    ) -> Tuple[np.ndarray, np.ndarray]:
+        return np.exp(mu), sigma * np.exp(mu)
 
-    def expit_trans(self, mu: npt.ArrayLike, sigma: npt.ArrayLike) -> Tuple[np.ndarray, np.ndarray]:
-        return 1.0 / (1.0 + np.exp(-mu)), sigma * np.exp(-mu) / (1.0 + np.exp(-mu)) ** 2
+    def expit_trans(
+        self, mu: npt.ArrayLike, sigma: npt.ArrayLike
+    ) -> Tuple[np.ndarray, np.ndarray]:
+        return 1.0 / (1.0 + np.exp(-mu)), sigma * np.exp(-mu) / (
+            1.0 + np.exp(-mu)
+        ) ** 2
 
     def get_mu_trans(self):
         return self.mu_trans
@@ -56,11 +75,15 @@ def get_sigma_trans(self):
         return self.sigma_trans
 
 
-METHOD_LIST = ['delta']
+METHOD_LIST = ["delta"]
 
 
-def transform_data(mu: npt.ArrayLike, sigma: npt.ArrayLike, transform: str,
-                   method: str = 'delta') -> Tuple[np.ndarray, np.ndarray]:
+def transform_data(
+    mu: npt.ArrayLike,
+    sigma: npt.ArrayLike,
+    transform: str,
+    method: str = "delta",
+) -> Tuple[np.ndarray, np.ndarray]:
     """Transform data from one space to another.
 
     Transform data, in the form of sample statistics and their standard
@@ -89,12 +112,13 @@ def transform_data(mu: npt.ArrayLike, sigma: npt.ArrayLike, transform: str,
     """
     mu, sigma = np.array(mu), np.array(sigma)
     _check_input(method, transform, mu, sigma)
-    if method == 'delta':
+    if method == "delta":
         return delta_method(mu, sigma, transform)
 
 
-def delta_method(mu: npt.ArrayLike, sigma: npt.ArrayLike, transform: str) -> \
-                 Tuple[np.ndarray, np.ndarray]:
+def delta_method(
+    mu: npt.ArrayLike, sigma: npt.ArrayLike, transform: str
+) -> Tuple[np.ndarray, np.ndarray]:
     """Transform data using the delta method.
 
     Transform data, in the form of sample statistics and their standard
@@ -126,13 +150,14 @@ def delta_method(mu: npt.ArrayLike, sigma: npt.ArrayLike, transform: str) -> \
 
     """
     mu, sigma = np.array(mu), np.array(sigma)
-    _check_input('delta', transform, mu, sigma)
+    _check_input("delta", transform, mu, sigma)
     transformer = FirstOrder(transform, mu, sigma)
     return transformer.get_mu_trans(), transformer.get_sigma_trans()
 
 
-def _check_input(method: str, transform: str, mu: npt.ArrayLike,
-                 sigma: npt.ArrayLike) -> None:
+def _check_input(
+    method: str, transform: str, mu: npt.ArrayLike, sigma: npt.ArrayLike
+) -> None:
     """Run checks on input data.
 
     Parameters