{"cells":[{"cell_type":"markdown","id":"7f6f372d","metadata":{"id":"7f6f372d"},"source":["[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/ai2es/WAF_ML_Tutorial_Part1/blob/main/colab_notebooks/Notebook03_TrainValTest.ipynb)\n","\n","# Notebook 03: TrainValTest [Colab Version]\n","\n","### Goal: Understand how to do train/val/test splitting\n","\n","#### Background\n","\n","In the paper, Section X.X, we discuss the importance of separating the total dataset into ```train```, ```validation``` and ```test``` subsets. Please go re-read this section if it is not clear to you why we do this.\n","\n","#### Step 0: Get the github repo (we need some of the functions there)\n","\n","The first step with all of these Google Colab notebooks will be to grab the github repo and cd into the notebooks directory. \n","\n","To run things from the command line, put a ```!``` before your code\n","\n","\n"]},{"cell_type":"code","source":["#get the github repo \n","!git clone https://github.com/ai2es/WAF_ML_Tutorial_Part1.git \n","\n","#cd into the repo so the paths work \n","import os \n","os.chdir('/content/WAF_ML_Tutorial_Part1/jupyter_notebooks/')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jckPeyZGTxaK","executionInfo":{"status":"ok","timestamp":1648651932935,"user_tz":300,"elapsed":25813,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"928dc619-bbb9-40b1-d0f9-37327be3fea6"},"id":"jckPeyZGTxaK","execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'WAF_ML_Tutorial_Part1'...\n","remote: Enumerating objects: 301, done.\u001b[K\n","remote: Counting objects: 100% (301/301), done.\u001b[K\n","remote: Compressing objects: 100% (197/197), done.\u001b[K\n","remote: Total 301 (delta 139), reused 236 (delta 96), pack-reused 0\u001b[K\n","Receiving objects: 100% (301/301), 195.77 MiB | 16.15 MiB/s, done.\n","Resolving deltas: 100% (139/139), done.\n","Checking out files: 100% (100/100), done.\n"]}]},{"cell_type":"markdown","source":["#### Step 1: Import packages and load data. \n","This is basically the same steps as the last notebooks, but this time we load the same dataframe as the previous notebook."],"metadata":{"id":"T5DOYHZTT3J1"},"id":"T5DOYHZTT3J1"},{"cell_type":"code","execution_count":2,"id":"b9b4e1de","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"b9b4e1de","executionInfo":{"status":"ok","timestamp":1648651938352,"user_tz":300,"elapsed":3120,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"5b1549ae-f1ed-4836-f9c3-b25684f4ca9a"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[" q000 q001 q010 q025 q050 q075 q090 q099 \\\n","2018-02-04 16:40:00 -61.31 -59.45 -55.30 -52.59 -47.00 -36.92 -26.560 -4.4163 \n","2018-02-04 16:45:00 -61.90 -59.13 -55.37 -52.52 -47.68 -38.00 -26.753 -6.9400 \n","2018-02-04 16:50:00 -61.16 -58.93 -55.35 -52.55 -48.17 -39.07 -27.013 -8.8400 \n","2018-02-04 16:55:00 -61.63 -58.87 -55.38 -52.68 -48.34 -40.16 -27.030 -8.9163 \n","2018-02-04 17:00:00 -61.67 -58.82 -55.42 -52.81 -48.38 -40.75 -27.240 -9.0526 \n","\n"," q100 event \n","2018-02-04 16:40:00 15.19 Thunderstorm Wind \n","2018-02-04 16:45:00 15.32 Thunderstorm Wind \n","2018-02-04 16:50:00 15.62 Thunderstorm Wind \n","2018-02-04 16:55:00 14.27 Thunderstorm Wind \n","2018-02-04 17:00:00 6.57 Thunderstorm Wind "],"text/html":["\n","
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2018-02-04 16:40:00-61.31-59.45-55.30-52.59-47.00-36.92-26.560-4.416315.19Thunderstorm Wind
2018-02-04 16:45:00-61.90-59.13-55.37-52.52-47.68-38.00-26.753-6.940015.32Thunderstorm Wind
2018-02-04 16:50:00-61.16-58.93-55.35-52.55-48.17-39.07-27.013-8.840015.62Thunderstorm Wind
2018-02-04 16:55:00-61.63-58.87-55.38-52.68-48.34-40.16-27.030-8.916314.27Thunderstorm Wind
2018-02-04 17:00:00-61.67-58.82-55.42-52.81-48.38-40.75-27.240-9.05266.57Thunderstorm Wind
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\n"," "]},"metadata":{},"execution_count":2}],"source":["#needed packages \n","import xarray as xr\n","import matplotlib.pyplot as plt \n","import numpy as np\n","import pandas as pd\n","\n","#plot parameters that I personally like, feel free to make these your own.\n","import matplotlib\n","matplotlib.rcParams['axes.facecolor'] = [0.9,0.9,0.9] #makes a grey background to the axis face\n","matplotlib.rcParams['axes.labelsize'] = 14 #fontsize in pts\n","matplotlib.rcParams['axes.titlesize'] = 14 \n","matplotlib.rcParams['xtick.labelsize'] = 12 \n","matplotlib.rcParams['ytick.labelsize'] = 12 \n","matplotlib.rcParams['legend.fontsize'] = 12 \n","matplotlib.rcParams['legend.facecolor'] = 'w' \n","matplotlib.rcParams['savefig.transparent'] = False\n","\n","#make default resolution of figures much higher (i.e., High definition)\n","%config InlineBackend.figure_format = 'retina'\n","\n","#load an example dataframe\n","df = pd.read_csv('../datasets/sevir/IR_stats_master.csv',index_col=0,low_memory=False,parse_dates=True)\n","#scale back to correct units\n","keys = list(df.keys()[:-1])\n","df[keys] = df[keys]*1e-2\n","#remove outlier\n","df = df.where(df.q000 > -100)\n","#make sure index is in order\n","df = df.sort_index()\n","# df = df.dropna()\n","\n","df.head()"]},{"cell_type":"markdown","id":"1f187813","metadata":{"id":"1f187813"},"source":["#### Step 2: Temporal Split\n","\n","For meteorological data it is often good to use time to split up your data. The way we have build these datasets (i.e., dataframes), encoding time as ```datetimes``` and ```pandas``` makes time selection really simple. For example, maybe we wanted to subset all data from August 2018. We can do that like the following: "]},{"cell_type":"code","execution_count":3,"id":"5c23653b","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5c23653b","executionInfo":{"status":"ok","timestamp":1648651941040,"user_tz":300,"elapsed":185,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"83a5fede-0021-4d6d-fe44-1bf1e95e38be"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(Timestamp('2018-08-01 00:00:00'), Timestamp('2018-09-01 23:55:00'))"]},"metadata":{},"execution_count":3}],"source":["time_range = slice('2018-08-01','2018-09-01')\n","df_august = df[time_range]\n","\n","df_august.index.min(),df_august.index.max()"]},{"cell_type":"markdown","id":"191f0169","metadata":{"id":"191f0169"},"source":["This is really quite a powerful tool, we can do fun things like, show the distribution of minimum infrared brightness temperature on a monthly basis. \n","\n","To actually do this, we will use the ```groupby``` method, that will help us group all the data by their month. "]},{"cell_type":"code","execution_count":6,"id":"16aeb9ab","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":546},"id":"16aeb9ab","executionInfo":{"status":"ok","timestamp":1648651963322,"user_tz":300,"elapsed":2086,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"0a6a9329-10b3-460f-e0e3-d8e950bdc0a7"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"image/png":{"width":351,"height":529}}}],"source":["#this is in order Jan, Feb, Mar ...\n","groups = df.q000.groupby(df.index.month)\n","\n","#for plotting purposes I want to reverse that \n","groups = list(groups)\n","groups = groups[::-1]\n","\n","###### plot stuff #########\n","bins=np.arange(-100,0,4)\n","#midpoints of the bins\n","mids=np.arange(-98,-2,4)\n","#colormap to assign a color for each month \n","cmap = matplotlib.cm.Spectral_r\n","bounds = np.arange(0,1.3,.1)\n","norm = matplotlib.colors.BoundaryNorm(bounds, cmap.N)\n","scalarMap = matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap)\n","###########################\n","\n","###### Actual Plot #########\n","#make fig\n","fig = plt.figure(figsize=(5,7.5))\n","#set not clear facecolor\n","fig.set_facecolor('w')\n","#grab axis handle \n","ax = plt.gca()\n","#loop over all groups \n","for idx,group in groups:\n"," #get the counts per bin \n"," c,b = np.histogram(group.values,bins=bins)\n"," #normalize \n"," c = c/c.sum()\n"," #plot axis line\n"," ax.axhline((idx/10),color='k',zorder=0,alpha=0.5)\n"," #plot curve\n"," ax.fill_between(mids,(idx/10),c+(idx/10),alpha=0.9,facecolor=scalarMap.to_rgba((idx/10)),edgecolor='k')\n","\n","#set plot xlimits\n","ax.set_xlim([-90,-10])\n","#force ticks to show up for each group\n","ax.set_yticks(np.arange(0,1.3,.1))\n","#force ylimits\n","ax.set_ylim([0.05,1.4])\n","#force yticklabels\n","ax.set_yticklabels(['','Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'])\n","#add axis labels\n","ax.set_xlabel('IR Minimum Brightness Temperature, [$\\degree$C]')\n","ax.set_ylabel('Grouped Month')\n","\n","plt.tight_layout()"]},{"cell_type":"markdown","id":"b303f03c","metadata":{"id":"b303f03c"},"source":["As expected, we can see that the summer months have colder cloud tips in their images. Which should correspond to stronger storms! Now, lets follow suit with how the data were split in the paper: \n","\n","training: 2017-01-01 through 2019-06-01
\n","val & test, randomly chunk up the rest:: 2019-06-01 through 2019-12-31\n"]},{"cell_type":"code","execution_count":7,"id":"11967f94","metadata":{"id":"11967f94","executionInfo":{"status":"ok","timestamp":1648651968255,"user_tz":300,"elapsed":251,"user":{"displayName":"Randy C","userId":"12301342565919601334"}}},"outputs":[],"source":["#make training time slice\n","train_time_range = slice('2017-01-01','2019-06-01')\n","#make training dataframe\n","df_train = df[train_time_range]\n","\n","#put the val/test data into one dataframe\n","other_time_range = slice('2019-06-01','2019-12-31')\n","df_other = df[other_time_range]\n","\n","#make list of indices \n","idx = np.arange(0,df_other.shape[0])\n","#set random seed for reproducability \n","np.random.seed(seed=42)\n","#grab random indices for the val and use the rest for test \n","idx_v = np.random.choice(idx,size=int(idx.shape[0]/2),replace=False)\n","#sort it because the randomness puts them out of time order\n","idx_v.sort()\n","idx_t = np.setdiff1d(idx,idx_v)\n","\n","\n","df_validation = df_other.iloc[idx_v]\n","df_test = df_other.iloc[idx_t]"]},{"cell_type":"markdown","id":"9bc7adf3","metadata":{"id":"9bc7adf3"},"source":["Let's take a look at their shapes to make sure the val & test are the same"]},{"cell_type":"code","execution_count":8,"id":"4cab7961","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4cab7961","executionInfo":{"status":"ok","timestamp":1648651970531,"user_tz":300,"elapsed":246,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"7f9c310b-e560-4ba2-dac5-65eb472f9484"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(86338, 86338)"]},"metadata":{},"execution_count":8}],"source":["df_validation.shape[0],df_test.shape[0]"]},{"cell_type":"markdown","id":"ed32b801","metadata":{"id":"ed32b801"},"source":["#### Step 3: Random Split\n","\n","There are times where a pure random split can be used. In those instances, you can use a pre-built function in scikit-learn to do this for you. The first step though, is to convert our input dataframe to a simple numpy matrix of shape, (n_samples,n_features). This matrix is commonly denoted as ```X``` on the scikit website. We also need out output data (i.e., labels), which are commonly denoted as ```y``` which is the shape (n_samples) on scikit's website."]},{"cell_type":"code","execution_count":9,"id":"06dc5a4d","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"06dc5a4d","executionInfo":{"status":"ok","timestamp":1648651972955,"user_tz":300,"elapsed":1131,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"60b630fe-c97f-4f58-df78-15c319196bfc"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["((414872, 9), (102170, 9), (102171, 9))"]},"metadata":{},"execution_count":9}],"source":["from sklearn.model_selection import train_test_split\n","\n","############ make simple X ###############\n","#drop the event column, we dont need that \n","df_noevent = df.drop(columns='event')\n","#make simple numpy matrix of our inputs, X\n","X = df_noevent.to_numpy()\n","###########################################\n","\n","\n","############ make simple y ###############\n","#load the label matrix, the number of GLM flashes\n","df_label = pd.read_csv('../datasets/sevir/LI_stats_master.csv',index_col=0,low_memory=False,parse_dates=True)\n","#make simple numpy vector of the outputs, y\n","y = df_label.c.values\n","###########################################\n","\n","\n","#if we wanted to do a random split, we could use this function \n","X_train, X_other, y_train, y_other = train_test_split(X, y, test_size=0.33, random_state=42)\n","\n","#seeing as there is no specific validation dataset, we must further split validation and test \n","X_validation, X_test, y_validation, y_test = train_test_split(X_other, y_other, test_size=0.5, random_state=42)\n","\n","#check shapes\n","X_train.shape,X_validation.shape,X_test.shape"]},{"cell_type":"markdown","id":"433460c2","metadata":{"id":"433460c2"},"source":["What we have shown you was just for 1 variable (we have 3 others to consider). It takes a bit more effort to do this will all the variables, so I have gone ahead and built this into a function. If you are truly interested, check out the ```load_n_comine_df``` function in the ```aux_functions.py``` script. Below is an example of loading the data into their groups"]},{"cell_type":"code","execution_count":10,"id":"1dd9bfc2","metadata":{"id":"1dd9bfc2","executionInfo":{"status":"ok","timestamp":1648651982866,"user_tz":300,"elapsed":7400,"user":{"displayName":"Randy C","userId":"12301342565919601334"}}},"outputs":[],"source":["#import some helper functions for our other directory.\n","import sys\n","sys.path.insert(1, '../scripts/')\n","from aux_functions import load_n_combine_df\n","(X_train,y_train),(X_validate,y_validate),(X_test,y_test) = load_n_combine_df(path_to_data='../datasets/sevir/',features_to_keep=np.arange(0,36,1),class_labels=True)"]},{"cell_type":"code","source":["#check shapes\n","X_train.shape,X_validation.shape,X_test.shape"],"metadata":{"id":"JHzqbQv3ULnT","executionInfo":{"status":"ok","timestamp":1648651986880,"user_tz":300,"elapsed":222,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"fde5ee42-abf4-4f60-c766-189e08b9f93c","colab":{"base_uri":"https://localhost:8080/"}},"id":"JHzqbQv3ULnT","execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["((446307, 36), (102170, 9), (86296, 36))"]},"metadata":{},"execution_count":11}]}],"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":"3.9.7"},"colab":{"name":"Notebook03_TrainValTest.ipynb","provenance":[]}},"nbformat":4,"nbformat_minor":5}