Fix tests, bump python version to 3.11 (#29)

* fix tests 

* bump python version to 3.11

* fix ci

* add tests for bayesian blocks

.github/workflows/ci.yml

@@ -1,41 +1,77 @@
 name: CI
-on: [push, pull_request]
+
+on:
+  push:
+    branches:
+      - main
+    tags:
+      - '**'
+  pull_request:
+
 jobs:
+
   tests:
+    name: test coverage
+
+    strategy:
+      matrix:
+        include:
+          - python-version: "3.11"
+            os: ubuntu-latest
+
+    runs-on: ${{ matrix.os }}
+
     defaults:
       run:
         shell: bash -l {0}
-    name: test coverage
-    runs-on: ubuntu-latest
+
     steps:
-      - name: checkout repo
-        uses: actions/checkout@v2
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.pull_request.head.sha }}
       - name: create and activate env
-        uses: conda-incubator/setup-miniconda@v2
+        uses: conda-incubator/setup-miniconda@v3
         with:
           activate-environment: mutis
           environment-file: environment.yml
+          auto-update-conda: true
+          python-version: ${{ matrix.python-version }}
       - name: install mutis
         run: |
           pip install -e .
       - name: test coverage
         run: |
           make test-cov
           codecov -X gcov
+
   docs:
+    name: docs building
+
+    strategy:
+      matrix:
+        include:
+          - python-version: "3.11"
+            os: ubuntu-latest
+
+    runs-on: ${{ matrix.os }}
+
     defaults:
       run:
         shell: bash -l {0}
-    name: docs building
-    runs-on: ubuntu-latest
+
     steps:
-      - name: checkout repo
-        uses: actions/checkout@v2
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ github.event.pull_request.head.sha }}
       - name: create and activate env
-        uses: conda-incubator/setup-miniconda@v2
+        uses: conda-incubator/setup-miniconda@v3
         with:
           activate-environment: mutis
           environment-file: environment.yml
+          auto-update-conda: true
+          python-version: ${{ matrix.python-version }}
       - name: install mutis
         run: |
           pip install -e .

docs/recipes/stochastics_tests.ipynb

@@ -313,9 +313,7 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "fit[0]*sigma_est**2/2"
-   ]
+   "source": []
   },
   {
    "cell_type": "markdown",

mutis/flares/bayblocks.py

@@ -213,7 +213,7 @@ def get_flare_list(self):
                           np.where((np.abs(np.diff(np.asarray(self.inflare, dtype=int))) == 1))[0]+1)
 
         # (groups contains the groups of indices of self.inflare/self.values 
-        # that corresond to flares or no flares)
+        # that correspond to flares or no flares)
 
         #print(self.inflare)
         #print([list(grp) for grp in groups])

mutis/lib/correlation.py

@@ -267,8 +267,8 @@ def nindcf(t1, s1, t2, s2):
     """Computes the normalised correlation of two discrete signals (interpolating them)."""
 
     dt = np.max([(t1.max() - t1.min()) / t1.size, (t2.max() - t2.min()) / t2.size])
-    n1 = np.int(np.ptp(t1) / dt * 10.0)
-    n2 = np.int(np.ptp(t1) / dt * 10.0)
+    n1 = int(np.ptp(t1) / dt * 10.0)
+    n2 = int(np.ptp(t1) / dt * 10.0)
     s1i = np.interp(np.linspace(t1.min(), t1.max(), n1), t1, s1)
     s2i = np.interp(np.linspace(t2.min(), t2.max(), n2), t2, s2)
     return ndcf(s1i, s2i)

mutis/signal.py

@@ -47,7 +47,6 @@ class Signal:
         (For OU method) Parameter mu of the OU process.
     OU_sigma : :class:`float`
         (For OU method) Parameter sigma of the OU process.
-        
     """
 
     def __init__(self, times, values, dvalues=None, fgen=None):
@@ -123,7 +122,7 @@ def OU_fit(self, bins=None, rang=None, a=1e-5, b=100):
 
         # plot histogram
         if bins is None:
-            bins = np.int(y.size ** 0.5 / 1.5)  # bins='auto'
+            bins = int(y.size ** 0.5 / 1.5)  # bins='auto'
         if rang is None:
             rang = (np.percentile(y, 0), np.percentile(y, 99))
 
@@ -138,7 +137,7 @@ def OU_fit(self, bins=None, rang=None, a=1e-5, b=100):
         anchored_text = AnchoredText(
             f"mean    {np.mean(y):.2g} \n "
             f"median  {np.median(y):.2g} \n "
-            f"mode    {scipy_stats.mode(y)[0][0]:.2g} \n "
+            f"mode    {scipy_stats.mode(y)[0]:.2g} \n "
             f"std     {np.std(y):.2g} \n "
             f"var     {np.var(y):.2g}",
             loc="upper right",
@@ -242,12 +241,12 @@ def check_gen(self, fgen=None, fgen_params=None, fpsd="lombscargle", **axes):
         axes["ax1"].set_title("light curves")
 
         # plot their histogram
-        bins = "auto"  # bins = np.int(y.size**0.5/1.5) #
+        bins = "auto"  # bins = int(y.size**0.5/1.5) #
         rang = (np.percentile(y, 0), np.percentile(y, 99))
         axes["ax2"].hist(y, density=True, color="b", alpha=0.4, bins=bins, range=rang)
 
         # ax2p = ax2.twinx()
-        bins = "auto"  # bins = np.int(y.size**0.5/1.5) #
+        bins = "auto"  # bins = int(y.size**0.5/1.5) #
         rang = (np.percentile(y2, 0), np.percentile(y2, 99))
         axes["ax2"].hist(y2, density=True, color="r", alpha=0.4, bins=bins, range=rang)
 

mutis/tests/test_bayblocks.py

@@ -0,0 +1,16 @@
+import unittest
+import numpy as np
+from mutis.flares.bayblocks import BayesianBlocks
+from mutis import Signal
+
+def test_bayblocks():
+    # test the bayblock algorithm with a signal that corresponds to 3 gaussian pulses in a row
+    t = np.linspace(0, 6, 50)
+    y = np.exp(-(t-1)**2/0.1) + np.exp(-(t-3)**2/0.1) + np.exp(-(t-5)**2/0.1)
+    dy = 0.1 * np.abs(y) 
+    signal = Signal(t, y, dy)
+    bayblocks = BayesianBlocks(signal, p=1e-1)
+    bayblocks.get_flares()
+    bayblocks.signal.plot()
+    bayblocks.plot()
+    assert len(bayblocks.get_flare_list()) == 3

setup.py

@@ -18,5 +18,5 @@
         "License :: OSI Approved :: BSD License",
         "Operating System :: OS Independent",
     ],
-    python_requires='>=3.7',
+    python_requires='>=3.11',
 )