diff --git a/notebooks/Rain event detection methods.ipynb b/notebooks/Rain event detection methods.ipynb new file mode 100644 index 0000000..0a02e42 --- /dev/null +++ b/notebooks/Rain event detection methods.ipynb @@ -0,0 +1,382 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload \n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-01-02 17:43:36.084473: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2024-01-02 17:43:36.084517: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2024-01-02 17:43:36.085395: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2024-01-02 17:43:36.090921: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", + "2024-01-02 17:43:36.940670: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", + "WARNING:absl:Skipping variable loading for optimizer 'Adam', because it has 9 variables whereas the saved optimizer has 1 variables. \n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib as mpl\n", + "import tqdm\n", + "import xarray as xr\n", + "import pandas as pd\n", + "import pycomlink.processing.wet_dry.cnn as cnn\n", + "import pycomlink.processing.wet_dry.mlp as mlp\n", + "import pycomlink as pycml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load and preprocess example data \n", + "\n", + "These steps are similar to the steps performed in the notebook \"Basic CML processing workflow.ipynb\". " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Load data\n", + "data_path = pycml.io.examples.get_example_data_path()\n", + "cmls = xr.open_dataset(data_path + '/example_cml_data.nc')\n", + "\n", + "# select 3 different CMLs to study\n", + "cmls = cmls.isel(cml_id = [0, 10, 370])\n", + "\n", + "# Remove outliers, compute tl and interpolate missing values\n", + "cmls['tsl'] = cmls.tsl.where(cmls.tsl != 255.0)\n", + "cmls['rsl'] = cmls.rsl.where(cmls.rsl != -99.9)\n", + "cmls['tl'] = cmls.tsl - cmls.rsl # calculate total loss (previous TRSL)\n", + "cmls['tl'] = cmls.tl.interpolate_na(dim='time', method='linear', max_gap='5min')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Do wet-dry classification using different methods and determine baseline\n", + "\n", + "This compares 3 different ways of finding wet and dry periods in the CML time series. " + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|███████████████████████████████████████| 3/3 [00:01<00:00, 1.75it/s]\n", + "100%|███████████████████████████████████████| 3/3 [00:03<00:00, 1.01s/it]\n" + ] + } + ], + "source": [ + "# wet dry detection using rsd\n", + "cmls['wet_rsd'] = cmls.tl.rolling(time=60, center=True).std() > 0.8\n", + "\n", + "# wet dry detection using MLP\n", + "cmls['wet_mlp'] = (('cml_id', 'time'), np.zeros([cmls.cml_id.size, cmls.time.size]))\n", + "for cml_id in tqdm.tqdm(cmls.cml_id.values):\n", + " mlp_out = mlp.mlp_wet_dry(\n", + " trsl_channel_1 = cmls.sel(cml_id = cml_id).isel(channel_id = 0).tl.values,\n", + " trsl_channel_2 = cmls.sel(cml_id = cml_id).isel(channel_id = 1).tl.values,\n", + " )\n", + " cmls['wet_mlp'].loc[{'cml_id':cml_id}]= np.argmax(mlp_out, axis = 1)\n", + "\n", + "# wet dry detection using CNN\n", + "cmls['wet_cnn'] = (('cml_id', 'time'), np.zeros([cmls.cml_id.size, cmls.time.size]))\n", + "for cml_id in tqdm.tqdm(cmls.cml_id.values):\n", + " cnn_out = cnn.cnn_wet_dry(\n", + " trsl_channel_1 = cmls.sel(cml_id = cml_id).isel(channel_id = 0).tl.values,\n", + " trsl_channel_2 = cmls.sel(cml_id = cml_id).isel(channel_id = 1).tl.values,\n", + " )\n", + " cmls['wet_cnn'].loc[{'cml_id':cml_id}]= cnn_out > 0.82" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Determine baseline for the \n", + "cmls['baseline_rsd'] = pycml.processing.baseline.baseline_constant(trsl=cmls.tl, wet=cmls.wet_rsd, n_average_last_dry=5)\n", + "cmls['baseline_mlp'] = pycml.processing.baseline.baseline_constant(trsl=cmls.tl, wet=cmls.wet_mlp, n_average_last_dry=5)\n", + "cmls['baseline_cnn'] = pycml.processing.baseline.baseline_constant(trsl=cmls.tl, wet=cmls.wet_cnn, n_average_last_dry=5)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot TL and baseline for good CML" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "start = '2018-05-13T22'\n", + "end = '2018-05-14'\n", + "cml_plot = cmls.sel(time = slice(start, end)).isel(cml_id = 0, channel_id = 0)\n", + "\n", + "# convert float to bool for plotting the shaded areas\n", + "cml_plot['wet_rsd'] = cml_plot.fillna(0).wet_rsd.astype(bool)\n", + "cml_plot['wet_mlp'] = cml_plot.fillna(0).wet_mlp.astype(bool)\n", + "cml_plot['wet_cnn'] = cml_plot.fillna(0).wet_cnn.astype(bool)\n", + "\n", + "\n", + "fig, axs = plt.subplots(3, 1, figsize=(12,5), sharex=True)\n", + "cml_plot.tl.plot.line(x='time', ax=axs[0], label = 'TL');\n", + "cml_plot.tl.plot.line(x='time', ax=axs[1], label = 'TL');\n", + "cml_plot.tl.plot.line(x='time', ax=axs[2], label = 'TL');\n", + "\n", + "# shaded rsd\n", + "cml_plot['wet_rsd'][0] = 0 \n", + "cml_plot['wet_rsd'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_rsd, -1) & ~cml_plot.wet_rsd\n", + "wet_end = np.roll(cml_plot.wet_rsd, 1) & ~cml_plot.wet_rsd\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[0].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "# shaded mlp\n", + "cml_plot['wet_mlp'][0] = 0 \n", + "cml_plot['wet_mlp'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_mlp, -1) & ~cml_plot.wet_mlp\n", + "wet_end = np.roll(cml_plot.wet_mlp, 1) & ~cml_plot.wet_mlp\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[1].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "# shaded mlp\n", + "cml_plot['wet_cnn'][0] = 0 \n", + "cml_plot['wet_cnn'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_cnn, -1) & ~cml_plot.wet_cnn\n", + "wet_end = np.roll(cml_plot.wet_cnn, 1) & ~cml_plot.wet_cnn\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[2].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "\n", + "cml_plot.baseline_rsd.plot.line(x='time', ax=axs[0], label ='baseline');\n", + "cml_plot.baseline_mlp.plot.line(x='time', ax=axs[1], label ='baseline');\n", + "cml_plot.baseline_cnn.plot.line(x='time', ax=axs[2], label ='baseline');\n", + "\n", + "axs[0].set_title('');\n", + "axs[0].set_xlabel('')\n", + "axs[1].set_title('');\n", + "axs[1].set_xlabel('')\n", + "axs[2].set_title('');\n", + "axs[0].set_ylabel('RSD')\n", + "axs[1].set_ylabel('MLP')\n", + "axs[2].set_ylabel('CNN')\n", + "\n", + "axs[0].legend(loc = 'upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Notes: \n", + "\n", + "- The RSD method identifies 3 rainy periods. \n", + "- The MLP method is able to identify several rainy periods around 16:00.\n", + "- The CNN generally estimates longer wet periods. \n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot TL and baseline for a less good CML" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "start = '2018-05-15T22'\n", + "end = '2018-05-16T12'\n", + "cml_plot = cmls.sel(time = slice(start, end)).isel(cml_id = 2, channel_id = 0)\n", + "\n", + "# convert float to bool for plotting the shaded areas\n", + "cml_plot['wet_rsd'] = cml_plot.fillna(0).wet_rsd.astype(bool)\n", + "cml_plot['wet_mlp'] = cml_plot.fillna(0).wet_mlp.astype(bool)\n", + "cml_plot['wet_cnn'] = cml_plot.fillna(0).wet_cnn.astype(bool)\n", + "\n", + "fig, axs = plt.subplots(3, 1, figsize=(12,5), sharex=True)\n", + "cml_plot.tl.plot.line(x='time', ax=axs[0], label = 'TL');\n", + "cml_plot.tl.plot.line(x='time', ax=axs[1], label = 'TL');\n", + "cml_plot.tl.plot.line(x='time', ax=axs[2], label = 'TL');\n", + "\n", + "# shaded rsd\n", + "cml_plot['wet_rsd'][0] = 0 \n", + "cml_plot['wet_rsd'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_rsd, -1) & ~cml_plot.wet_rsd\n", + "wet_end = np.roll(cml_plot.wet_rsd, 1) & ~cml_plot.wet_rsd\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[0].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "# shaded mlp\n", + "cml_plot['wet_mlp'][0] = 0 \n", + "cml_plot['wet_mlp'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_mlp, -1) & ~cml_plot.wet_mlp\n", + "wet_end = np.roll(cml_plot.wet_mlp, 1) & ~cml_plot.wet_mlp\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[1].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "# shaded mlp\n", + "cml_plot['wet_cnn'][0] = 0 \n", + "cml_plot['wet_cnn'][-1] = 0 \n", + "wet_start = np.roll(cml_plot.wet_cnn, -1) & ~cml_plot.wet_cnn\n", + "wet_end = np.roll(cml_plot.wet_cnn, 1) & ~cml_plot.wet_cnn\n", + "for wet_start_i, wet_end_i in zip(\n", + " wet_start.values.nonzero()[0],\n", + " wet_end.values.nonzero()[0],\n", + "):\n", + " axs[2].axvspan(cml_plot.time.values[wet_start_i], cml_plot.time.values[wet_end_i], color='b', alpha=0.1)\n", + "\n", + "\n", + "cml_plot.baseline_rsd.plot.line(x='time', ax=axs[0], label ='baseline');\n", + "cml_plot.baseline_mlp.plot.line(x='time', ax=axs[1], label ='baseline');\n", + "cml_plot.baseline_cnn.plot.line(x='time', ax=axs[2], label ='baseline');\n", + "\n", + "axs[0].set_title('');\n", + "axs[0].set_xlabel('')\n", + "axs[1].set_title('');\n", + "axs[1].set_xlabel('')\n", + "axs[2].set_title('');\n", + "axs[0].set_ylabel('RSD')\n", + "axs[1].set_ylabel('MLP')\n", + "axs[2].set_ylabel('CNN')\n", + "\n", + "axs[0].legend(loc = 'upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Notes: \n", + "- The RSD method finds the two largest events, but does not predict rainfall at 04:30.\n", + "- The MLP method predicts rainfall at 04:30. \n", + "- The CNN generally estimates longer wet periods. \n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pycomlink/processing/wet_dry/mlp.py b/pycomlink/processing/wet_dry/mlp.py new file mode 100644 index 0000000..f64e6c1 --- /dev/null +++ b/pycomlink/processing/wet_dry/mlp.py @@ -0,0 +1,97 @@ +import numpy as np +from numpy.lib.stride_tricks import sliding_window_view +import tensorflow as tf +import pkg_resources +import pandas as pd + +def get_model_file_path(): + return pkg_resources.resource_filename( + "pycomlink", "/processing/wet_dry/mlp_model_files" + ) + +model = tf.keras.models.load_model(str(get_model_file_path() + "/model_mlp.keras")) + +def mlp_wet_dry( + trsl_channel_1, + trsl_channel_2, + threshold=None, # 0.5 is often good, or argmax +): + """ + Wet dry classification using a simple neural network: + + This MLP calculates wet and dry periods using a 40 minutes rolling window + for the CML signal loss from two sublinks (trsl_channel_1 and + trsl_channel_2) with temporal resolution equal to 1 minute. It consists of + one fully connected hidden layers with 20 neurons using the relu + activation function. The MLP was trained to predict rainfall recorded + at narby disdrometers at 10 minute resolution for one month of data with 14 + pairs of CMLs and disdrometers from different locations in Norway. The MLP + was trained using MLPClassifier from sklearn and then transformed + to tensorflow to be compatible with the pycomlink environment. + + If only one channel is available from the CML, use that channel for both + trsl_channel_1 and trsl_channel_2. + + The error "WARNING:absl:Skipping variable loading for optimizer 'Adam', + because it has 13 variables whereas the saved optimizer has 1 variables." + can safely be ignored. + + Parameters + ---------- + trsl_channel_1 : iterable of float + Time series of received signal level of channel 1 + trsl_channel_2 : iterable of float + Time series of received signal level of channel 2 + threshold : float + Threshold (0 - 1) for setting event as wet or dry. If set to None + (default), returns the continuous probability of wet [0, 1] from the + logistic activation function. + + Returns + ------- + iterable of float + Time series of wet/dry probability or (if threshold is provided) + wet dry classification + + References + ---------- + + + """ + # Normalization + trsl_channel_1_norm = (trsl_channel_1 - np.nanmean(trsl_channel_1)) / np.nanstd(trsl_channel_1) + trsl_channel_2_norm = (trsl_channel_2 - np.nanmean(trsl_channel_2)) / np.nanstd(trsl_channel_2) + + # add nan to start and end + windowsize = 40 # use two channels + x_start = np.ones([int(windowsize/2), windowsize*2])*np.nan + x_end = np.ones([int(windowsize/2)- 1, windowsize*2])*np.nan + + # sliding window + sliding_window_ch1 = sliding_window_view( + trsl_channel_1_norm, + window_shape = windowsize + ) + + sliding_window_ch2 = sliding_window_view( + trsl_channel_2_norm, + window_shape = windowsize + ) + + x_fts = np.vstack( + [x_start, np.hstack([sliding_window_ch1, sliding_window_ch2]), x_end] + ) + + mlp_pred = np.zeros([x_fts.shape[0], 2])*np.nan + indices = np.argwhere(~np.isnan(x_fts).any(axis = 1)).ravel() + + if indices.size > 0: # else: predictions are kept as nan + mlp_pred_ = model.predict(x_fts[indices], verbose=0) + mlp_pred[indices] = mlp_pred_ + + if threshold == None: + return mlp_pred + else: + mlp_pred = mlp_pred[:, 1] + mlp_pred[indices] = mlp_pred[indices] > threshold + return mlp_pred diff --git a/pycomlink/processing/wet_dry/mlp_model_files/model_mlp.keras b/pycomlink/processing/wet_dry/mlp_model_files/model_mlp.keras new file mode 100644 index 0000000..dca9e30 Binary files /dev/null and b/pycomlink/processing/wet_dry/mlp_model_files/model_mlp.keras differ diff --git a/pycomlink/tests/test_wet_dry_mlp.py b/pycomlink/tests/test_wet_dry_mlp.py new file mode 100644 index 0000000..df3b24d --- /dev/null +++ b/pycomlink/tests/test_wet_dry_mlp.py @@ -0,0 +1,69 @@ +import unittest +import numpy as np +from pycomlink.processing.wet_dry.mlp import mlp_wet_dry + +class Testmlppred(unittest.TestCase): + """ + This runs the same tests as test_wet_dry_cnn.py but with different + content in truth_raw. + """ + + def test_mlppred(self): + trsl_channel_1 = np.arange(0, 60 * 8).astype(float) + trsl_channel_2 = np.arange(0, 60 * 8).astype(float) + + trsl_channel_1[310] = np.nan # shorter window than in cnn + + pred_raw = mlp_wet_dry( + trsl_channel_1, + trsl_channel_2, + threshold=None, + )[:, 1] + + pred = mlp_wet_dry( + trsl_channel_1, + trsl_channel_2, + threshold=0.197, # low threshold for testing + ) + + # check if length of array is the same + assert len(pred_raw) == 60 * 8 + assert len(pred) == 60 * 8 + + # check if array is as expected + truth_raw = np.array( + [ + 0.19271295, + 0.19395444, + 0.19520202, + 0.19645563, + 0.19771534, + 0.19898114, + 0.20025298, + 0.20153098, + 0.20281503, + 0.20410511, + 0.20540135, + np.nan, + np.nan, + ] + ) + truth = np.array( + [ + 0, + 0, + 0, + 0, + 1, + 1, + 1, + 1, + 1, + 1, + 1, + np.nan, + np.nan, + ] + ) + np.testing.assert_almost_equal(pred[280:293], truth) + np.testing.assert_almost_equal(pred_raw[280:293], truth_raw, decimal=7)