ADD: Renaming repos (#5)

* renaming repos

* hide codecov for now

* hide codecov for now

.coveragerc

@@ -3,13 +3,13 @@ branch = True
 omit =
     */tests*
     */__init__.py
-    q2_time/_version.py
+    q2_ritme/_version.py
     versioneer.py
 
 [report]
 fail_under = 90
 omit =
     */tests*
     */__init__.py
-    q2_time/_version.py
+    q2_ritme/_version.py
     versioneer.py

.gitattributes

@@ -1 +1 @@
-q2_time/_version.py export-subst
+q2_ritme/_version.py export-subst

.github/workflows/ci.yml

@@ -55,22 +55,23 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         make create-env
-        conda activate time && make dev && make test-cov
+        conda activate ritme && make dev && make test-cov
 
     - name: Hack - template coverage output path
       run: echo "COV=coverage xml -o $GITHUB_WORKSPACE/coverage.xml" >> $GITHUB_ENV
 
     # # TODO: include this once this is a Q2 plugin and remove above run tests
     # - uses: qiime2/action-library-packaging@alpha1
     #   with:
-    #     package-name: q2-time
+    #     package-name: q2-ritme
     #     additional-tests: ${{ env.COV }}
     #     build-target: dev
     #     library-token: ${{ secrets.LIBRARY_TOKEN }}
 
-    - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v3
-      with:
-        # TODO: remove token when repos is public
-        token: ${{ secrets.CODECOV_TOKEN }}
-        fail_ci_if_error: true
+    # # TODO: add back codecov once repos renaming is detected correctly
+    # - name: Upload coverage to Codecov
+    #   uses: codecov/codecov-action@v3
+    #   with:
+    #     # TODO: remove token when repos is public
+    #     token: ${{ secrets.CODECOV_TOKEN }}
+    #     fail_ci_if_error: true

MANIFEST.in

@@ -1,2 +1,2 @@
 include versioneer.py
-include q2_time/_version.py
+include q2_ritme/_version.py

Makefile

@@ -13,13 +13,13 @@ test: all
 
 # todo: adjust coverage threshold once final
 test-cov: all
-	py.test --cov=q2_time --cov-report xml:coverage.xml --cov-fail-under=80
+	py.test --cov=q2_ritme --cov-report xml:coverage.xml --cov-fail-under=80
 
 install: all
 	$(PYTHON) setup.py install
 
 create-env: install-req
-	mamba create -y -n time -c qiime2 -c conda-forge -c bioconda -c defaults $(shell python get_requirements.py ci/recipe/meta.yaml conda)
+	mamba create -y -n ritme -c qiime2 -c conda-forge -c bioconda -c defaults $(shell python get_requirements.py ci/recipe/meta.yaml conda)
 
 install-req:
 	@command -v mamba >/dev/null 2>&1 || { echo "Installing mamba..."; conda install -y mamba -n base -c conda-forge; }

README.md

@@ -1,15 +1,15 @@
-# q2-time
-![CI](https://github.com/adamovanja/q2-time/actions/workflows/ci.yml/badge.svg)
-[![codecov](https://codecov.io/gh/adamovanja/q2-time/branch/main/graph/badge.svg?token=VQ4D7FXMCB)](https://codecov.io/gh/adamovanja/q2-time)
+# q2-ritme
+![CI](https://github.com/adamovanja/q2-ritme/actions/workflows/ci.yml/badge.svg)
+[![codecov](https://codecov.io/gh/adamovanja/q2-ritme/branch/main/graph/badge.svg?token=VQ4D7FXMCB)](https://codecov.io/gh/adamovanja/q2-ritme)
 
 Longitudinal modeling approaches accounting for high-dimensional, sparse and compositional nature of microbial time-series.
 
 ## Setup
-<!-- TODO: replace plugin name "q2-time" with something better-->
+<!-- TODO: replace plugin name "q2-ritme" with something better-->
 To install the required dependencies for this package run:
 ```shell
 make create-env
-conda activate time
+conda activate ritme
 make dev
 ```
 

ci/recipe/meta.yaml

@@ -2,7 +2,7 @@
 {% set version = data.get('version') or 'placehold' %}
 
 package:
-  name: q2-time
+  name: q2-ritme
   version: {{ version }}
 
 source:
@@ -44,12 +44,12 @@ test:
     - coverage
     - pytest-cov
   imports:
-    - q2_time
-    - qiime2.plugins.time
+    - q2_ritme
+    - qiime2.plugins.ritme
   commands:
-    - pytest --cov q2_time --pyargs q2_time
+    - pytest --cov q2_ritme --pyargs q2_ritme
 
 about:
-  home: https://github.com/adamovanja/q2-time
+  home: https://github.com/adamovanja/q2-ritme
   license: BSD-3-Clause
   license_family: BSD

experiments/ma5_tune.ipynb

@@ -28,11 +28,11 @@
     "import pandas as pd\n",
     "from IPython.display import display\n",
     "\n",
-    "from q2_time.process_data import load_n_split_data\n",
-    "from q2_time.tune_models import run_all_trials\n",
-    "from q2_time.evaluate_models import get_best_model, get_best_data_processing\n",
-    "from q2_time.feature_space.transform_features import transform_features\n",
-    "from q2_time.config import (\n",
+    "from q2_ritme.process_data import load_n_split_data\n",
+    "from q2_ritme.tune_models import run_all_trials\n",
+    "from q2_ritme.evaluate_models import get_best_model, get_best_data_processing\n",
+    "from q2_ritme.feature_space.transform_features import transform_features\n",
+    "from q2_ritme.config import (\n",
     "    HOST_ID,\n",
     "    TARGET,\n",
     "    TRAIN_SIZE,\n",

experiments/try_tune.ipynb

@@ -27,11 +27,11 @@
     "import pandas as pd\n",
     "from IPython.display import display\n",
     "\n",
-    "from q2_time.process_data import load_n_split_data\n",
-    "from q2_time.tune_models import run_all_trials\n",
-    "from q2_time.evaluate_models import get_best_model, get_best_data_processing\n",
-    "from q2_time.feature_space.transform_features import transform_features\n",
-    "from q2_time.config import (\n",
+    "from q2_ritme.process_data import load_n_split_data\n",
+    "from q2_ritme.tune_models import run_all_trials\n",
+    "from q2_ritme.evaluate_models import get_best_model, get_best_data_processing\n",
+    "from q2_ritme.feature_space.transform_features import transform_features\n",
+    "from q2_ritme.config import (\n",
     "    HOST_ID,\n",
     "    TARGET,\n",
     "    SEED_DATA,\n",

q2_time/_version.py → q2_ritme/_version.py

@@ -44,8 +44,8 @@ def get_config():
     cfg.VCS = "git"
     cfg.style = "pep440"
     cfg.tag_prefix = ""
-    cfg.parentdir_prefix = "q2-time-"
-    cfg.versionfile_source = "q2_time/_version.py"
+    cfg.parentdir_prefix = "q2-ritme-"
+    cfg.versionfile_source = "q2_ritme/_version.py"
     cfg.verbose = False
     return cfg
 

q2_time/feature_space/_process_train.py → q2_ritme/feature_space/_process_train.py

@@ -1,5 +1,5 @@
-from q2_time.feature_space.transform_features import transform_features
-from q2_time.process_data import split_data_by_host
+from q2_ritme.feature_space.transform_features import transform_features
+from q2_ritme.process_data import split_data_by_host
 
 
 def process_train(config, train_val, target, host_id, seed_data):

q2_time/model_space/_static_trainables.py → q2_ritme/model_space/_static_trainables.py

@@ -19,7 +19,7 @@
 from sklearn.metrics import mean_squared_error
 from tensorflow.keras import layers, models, optimizers
 
-from q2_time.feature_space._process_train import process_train
+from q2_ritme.feature_space._process_train import process_train
 
 
 def _predict_rmse(model: BaseEstimator, X: np.ndarray, y: np.ndarray) -> float:

q2_time/plugin_setup.py → q2_ritme/plugin_setup.py

@@ -8,15 +8,15 @@
 
 from qiime2.plugin import Citations, Plugin
 
-from q2_time import __version__
+from q2_ritme import __version__
 
-citations = Citations.load("citations.bib", package="q2_time")
+citations = Citations.load("citations.bib", package="q2_ritme")
 
 plugin = Plugin(
-    name="time",
+    name="ritme",
     version=__version__,
-    website="https://github.com/adamovanja/q2-time",
-    package="q2_time",
+    website="https://github.com/adamovanja/q2-ritme",
+    package="q2_ritme",
     description="This is a QIIME 2 plugin for longitudinal modeling applied to "
     "microbial time-series.",
     short_description="",

q2_time/process_data.py → q2_ritme/process_data.py

@@ -3,8 +3,8 @@
 from sklearn.model_selection import GroupShuffleSplit
 
 # todo: adjust to json file to be read in from user
-from q2_time.config import HOST_ID, SEED_DATA, TARGET, TRAIN_SIZE
-from q2_time.simulate_data import simulate_data
+from q2_ritme.config import HOST_ID, SEED_DATA, TARGET, TRAIN_SIZE
+from q2_ritme.simulate_data import simulate_data
 
 
 def load_data(path2md: str = None, path2ft: str = None) -> (pd.DataFrame, pd.DataFrame):

q2_time/tests/test_feature_space.py → q2_ritme/tests/test_feature_space.py

@@ -7,16 +7,16 @@
 from scipy.stats.mstats import gmean
 from skbio.stats.composition import ilr
 
-from q2_time.feature_space._process_train import process_train
-from q2_time.feature_space.transform_features import (
+from q2_ritme.feature_space._process_train import process_train
+from q2_ritme.feature_space.transform_features import (
     PSEUDOCOUNT,
     alr,
     transform_features,
 )
 
 
 class TestTransformFeatures(TestPluginBase):
-    package = "q2_time.test"
+    package = "q2_ritme.test"
 
     def setUp(self):
         super().setUp()
@@ -119,7 +119,7 @@ def test_transform_features_error(self):
 
 
 class TestProcessTrain(TestPluginBase):
-    package = "q2_time.test"
+    package = "q2_ritme.test"
 
     def setUp(self):
         super().setUp()
@@ -144,8 +144,8 @@ def _assert_called_with_df(self, mock, expected_df, *expected_args):
         for expected, actual in zip(expected_args, args[1:]):
             assert expected == actual, f"Expected {expected}, but got {actual}"
 
-    @patch("q2_time.feature_space._process_train.transform_features")
-    @patch("q2_time.feature_space._process_train.split_data_by_host")
+    @patch("q2_ritme.feature_space._process_train.transform_features")
+    @patch("q2_ritme.feature_space._process_train.split_data_by_host")
     def test_process_train(self, mock_split_data_by_host, mock_transform_features):
         # Arrange
         ls_ft = ["F0", "F1"]

q2_time/tests/test_process_data.py → q2_ritme/tests/test_process_data.py

@@ -6,7 +6,7 @@
 from pandas.testing import assert_frame_equal
 from qiime2.plugin.testing import TestPluginBase
 
-from q2_time.process_data import (
+from q2_ritme.process_data import (
     filter_merge_n_sort,
     load_data,
     load_n_split_data,
@@ -15,7 +15,7 @@
 
 
 class TestProcessData(TestPluginBase):
-    package = "q2_time.test"
+    package = "q2_ritme.test"
 
     def setUp(self):
         super().setUp()

q2_time/tests/test_simulate_data.py → q2_ritme/tests/test_simulate_data.py

@@ -3,13 +3,13 @@
 from pandas.testing import assert_frame_equal
 from qiime2.plugin.testing import TestPluginBase
 
-from q2_time.simulate_data import simulate_feature_table, simulate_metadata
+from q2_ritme.simulate_data import simulate_feature_table, simulate_metadata
 
 
 class TestFeatureTableSimulation(TestPluginBase):
     """Test all related to simulate_feature_table"""
 
-    package = "q2_time.tests"
+    package = "q2_ritme.tests"
 
     def test_default_feature_table(self):
         """Test default functionality"""
@@ -40,7 +40,7 @@ def test_randomness(self):
 class TestMetadataSimulation(TestPluginBase):
     """Test all related to simulate_metadata"""
 
-    package = "q2_time.tests"
+    package = "q2_ritme.tests"
 
     def setUp(self):
         super().setUp()

q2_time/tests/test_static_searchspace.py → q2_ritme/tests/test_static_searchspace.py

@@ -1,12 +1,12 @@
 from qiime2.plugin.testing import TestPluginBase
 
-from q2_time.model_space import _static_searchspace as ss
+from q2_ritme.model_space import _static_searchspace as ss
 
 
 class TestStaticSearchSpace(TestPluginBase):
     """Test all static search space dictionaries"""
 
-    package = "q2_time.tests"
+    package = "q2_ritme.tests"
 
     def setUp(self):
         super().setUp()

q2_time/tests/test_static_trainables.py → q2_ritme/tests/test_static_trainables.py

@@ -9,13 +9,13 @@
 from sklearn.linear_model import LinearRegression
 from sklearn.metrics import mean_squared_error
 
-from q2_time.model_space import _static_trainables as st
+from q2_ritme.model_space import _static_trainables as st
 
 
 class TestHelperFunctions(TestPluginBase):
     """Test all related to helper functions used by static_trainables"""
 
-    package = "q2_time.tests"
+    package = "q2_ritme.tests"
 
     def setUp(self):
         super().setUp()
@@ -46,7 +46,7 @@ def test_report_results_manually(self, mock_get_trial_dir, mock_report):
 
 
 class TestTrainables(TestPluginBase):
-    package = "q2_time.tests"
+    package = "q2_ritme.tests"
 
     def setUp(self):
         super().setUp()
@@ -64,9 +64,9 @@ def setUp(self):
         self.seed_data = 0
         self.seed_model = 0
 
-    @patch("q2_time.model_space._static_trainables.process_train")
-    @patch("q2_time.model_space._static_trainables.LinearRegression")
-    @patch("q2_time.model_space._static_trainables._report_results_manually")
+    @patch("q2_ritme.model_space._static_trainables.process_train")
+    @patch("q2_ritme.model_space._static_trainables.LinearRegression")
+    @patch("q2_ritme.model_space._static_trainables._report_results_manually")
     def test_train_linreg(self, mock_report, mock_linreg, mock_process_train):
         # define input parameters
         config = {"fit_intercept": True}
@@ -92,9 +92,9 @@ def test_train_linreg(self, mock_report, mock_linreg, mock_process_train):
         mock_linreg_instance.fit.assert_called_once()
         mock_report.assert_called_once()
 
-    @patch("q2_time.model_space._static_trainables.process_train")
-    @patch("q2_time.model_space._static_trainables.RandomForestRegressor")
-    @patch("q2_time.model_space._static_trainables._report_results_manually")
+    @patch("q2_ritme.model_space._static_trainables.process_train")
+    @patch("q2_ritme.model_space._static_trainables.RandomForestRegressor")
+    @patch("q2_ritme.model_space._static_trainables._report_results_manually")
     def test_train_rf(self, mock_report, mock_rf, mock_process_train):
         # Arrange
         config = {"n_estimators": 100, "max_depth": 10}
@@ -122,9 +122,9 @@ def test_train_rf(self, mock_report, mock_rf, mock_process_train):
         mock_rf_instance.fit.assert_called_once()
         mock_report.assert_called_once()
 
-    @patch("q2_time.model_space._static_trainables.process_train")
-    @patch("q2_time.model_space._static_trainables.models.Sequential")
-    @patch("q2_time.model_space._static_trainables.k_cc")
+    @patch("q2_ritme.model_space._static_trainables.process_train")
+    @patch("q2_ritme.model_space._static_trainables.models.Sequential")
+    @patch("q2_ritme.model_space._static_trainables.k_cc")
     def test_train_nn(self, mock_checkpoint, mock_nn, mock_process_train):
         # Arrange
         config = {
@@ -162,10 +162,10 @@ def test_train_nn(self, mock_checkpoint, mock_nn, mock_process_train):
         mock_nn_instance.fit.assert_called_once()
         mock_checkpoint.assert_called_once()
 
-    @patch("q2_time.model_space._static_trainables.process_train")
-    @patch("q2_time.model_space._static_trainables.xgb.DMatrix")
-    @patch("q2_time.model_space._static_trainables.xgb.train")
-    @patch("q2_time.model_space._static_trainables.xgb_cc")
+    @patch("q2_ritme.model_space._static_trainables.process_train")
+    @patch("q2_ritme.model_space._static_trainables.xgb.DMatrix")
+    @patch("q2_ritme.model_space._static_trainables.xgb.train")
+    @patch("q2_ritme.model_space._static_trainables.xgb_cc")
     def test_train_xgb(
         self, mock_checkpoint, mock_xgb_train, mock_dmatrix, mock_process_train
     ):

q2_time/tune_models.py → q2_ritme/tune_models.py

@@ -9,8 +9,8 @@
 from ray.tune.schedulers import AsyncHyperBandScheduler, HyperBandScheduler
 
 # todo: adjust to json file to be read in from user
-from q2_time.model_space import _static_searchspace as ss
-from q2_time.model_space import _static_trainables as st
+from q2_ritme.model_space import _static_searchspace as ss
+from q2_ritme.model_space import _static_trainables as st
 
 model_trainables = {
     # model_type: trainable