diff --git a/data/datasets.py b/data/datasets.py index 14b9901..e2309b1 100644 --- a/data/datasets.py +++ b/data/datasets.py @@ -147,4 +147,4 @@ class ForecastDataset(Dataset): return x, y, x_time, y_time def inverse_transform(self, data): - return self.scaler.inverse_transform(data) \ No newline at end of file + return self.scaler.inverse_transform(data) diff --git a/experiments/base.py b/experiments/base.py index 45d5b8c..064b87e 100644 --- a/experiments/base.py +++ b/experiments/base.py @@ -62,9 +62,12 @@ class Experiment(ABC): # write command file command_file = os.path.join(instance_path, 'command') with open(command_file, 'w') as cmd: + # cmd.write(f'python -m {module} ' + # f'--config_path={instance_config_path} ' + # f'run >> {instance_path}/instance.log 2>&1') cmd.write(f'python -m {module} ' - f'--config_path={instance_config_path} ' - f'run >> {instance_path}/instance.log 2>&1') + f'--config_path={instance_config_path} ' + f'run 2>&1 | tee -a {instance_path}/instance.log') @abstractmethod def instance(self): @@ -102,4 +105,4 @@ class Experiment(ABC): def build_experiment(self): if EXPERIMENTS_PATH in str(self.root): raise Exception('Cannot build ensemble from ensemble member configuration.') - self.build() \ No newline at end of file + self.build() diff --git a/experiments/configs/Stocks/96M.gin b/experiments/configs/Stocks/96M.gin new file mode 100644 index 0000000..4685988 --- /dev/null +++ b/experiments/configs/Stocks/96M.gin @@ -0,0 +1,37 @@ +build.experiment_name = 'Stocks/96M' +build.module = 'experiments.forecast' +build.repeat = 1 +build.variables_dict = { +} + +instance.model_type = 'deeptime' +instance.save_vals = False + +get_optimizer.lr = 1e-3 +get_optimizer.lambda_lr = 1. +get_optimizer.weight_decay = 0. + +get_scheduler.warmup_epochs = 5 + +get_data.batch_size = 256 + +train.loss_name = 'mse' +train.epochs = 50 +train.clip = 10. + +Checkpoint.patience = 7 + +deeptime.layer_size = 256 +deeptime.inr_layers = 5 +deeptime.n_fourier_feats = 4096 +deeptime.scales = [0.01, 0.1, 1, 5, 10, 20, 50, 100] + +ForecastDataset.data_path = 'stocks/OXY_2019.csv.gz' +ForecastDataset.target = 'RSMKs_18_144_72' +ForecastDataset.scale = True +ForecastDataset.cross_learn = False +ForecastDataset.time_features = [] +ForecastDataset.normalise_time_features = True +ForecastDataset.features = 'M' +ForecastDataset.horizon_len = 96 +ForecastDataset.lookback_mult = 1 diff --git a/experiments/configs/Stocks/96S.gin b/experiments/configs/Stocks/96S.gin new file mode 100644 index 0000000..fdc3990 --- /dev/null +++ b/experiments/configs/Stocks/96S.gin @@ -0,0 +1,37 @@ +build.experiment_name = 'Stocks/96S' +build.module = 'experiments.forecast' +build.repeat = 1 +build.variables_dict = { +} + +instance.model_type = 'deeptime' +instance.save_vals = False + +get_optimizer.lr = 1e-3 +get_optimizer.lambda_lr = 1. +get_optimizer.weight_decay = 0. + +get_scheduler.warmup_epochs = 5 + +get_data.batch_size = 256 + +train.loss_name = 'mse' +train.epochs = 50 +train.clip = 10. + +Checkpoint.patience = 7 + +deeptime.layer_size = 256 +deeptime.inr_layers = 5 +deeptime.n_fourier_feats = 4096 +deeptime.scales = [0.01, 0.1, 1, 5, 10, 20, 50, 100] + +ForecastDataset.data_path = 'stocks/OXY_2019.csv.gz' +ForecastDataset.target = 'RSMKs_18_144_72' +ForecastDataset.scale = True +ForecastDataset.cross_learn = False +ForecastDataset.time_features = [] +ForecastDataset.normalise_time_features = True +ForecastDataset.features = 'S' +ForecastDataset.horizon_len = 96 +ForecastDataset.lookback_mult = 3 diff --git a/experiments/configs/Stocks/96Splus.gin b/experiments/configs/Stocks/96Splus.gin new file mode 100644 index 0000000..b1ac55b --- /dev/null +++ b/experiments/configs/Stocks/96Splus.gin @@ -0,0 +1,37 @@ +build.experiment_name = 'Stocks/96Splus' +build.module = 'experiments.forecast' +build.repeat = 1 +build.variables_dict = { +} + +instance.model_type = 'deeptime2' +instance.save_vals = False + +get_optimizer.lr = 1e-3 +get_optimizer.lambda_lr = 1. +get_optimizer.weight_decay = 0. + +get_scheduler.warmup_epochs = 5 + +get_data.batch_size = 256 + +train.loss_name = 'mse' +train.epochs = 50 +train.clip = 10. + +Checkpoint.patience = 7 + +deeptime2.layer_size = 256 +deeptime2.inr_layers = 5 +deeptime2.n_fourier_feats = 4096 +deeptime2.scales = [0.01, 0.1, 1, 5, 10, 20, 50, 100] + +ForecastDataset.data_path = 'stocks/OXY_2019.csv.gz' +ForecastDataset.target = 'RSMKs_18_144_72' +ForecastDataset.scale = True +ForecastDataset.cross_learn = False +ForecastDataset.time_features = [] +ForecastDataset.normalise_time_features = True +ForecastDataset.features = 'S' +ForecastDataset.horizon_len = 96 +ForecastDataset.lookback_mult = 3 diff --git a/experiments/configs/Stocks/96Splusshort.gin b/experiments/configs/Stocks/96Splusshort.gin new file mode 100644 index 0000000..3e7630b --- /dev/null +++ b/experiments/configs/Stocks/96Splusshort.gin @@ -0,0 +1,37 @@ +build.experiment_name = 'Stocks/96Splusshort' +build.module = 'experiments.forecast' +build.repeat = 1 +build.variables_dict = { +} + +instance.model_type = 'deeptime2' +instance.save_vals = False + +get_optimizer.lr = 1e-3 +get_optimizer.lambda_lr = 1. +get_optimizer.weight_decay = 0. + +get_scheduler.warmup_epochs = 5 + +get_data.batch_size = 256 + +train.loss_name = 'mse' +train.epochs = 50 +train.clip = 10. + +Checkpoint.patience = 7 + +deeptime2.layer_size = 256 +deeptime2.inr_layers = 5 +deeptime2.n_fourier_feats = 4096 +deeptime2.scales = [0.01, 0.1, 1, 5, 10, 20, 50, 100] + +ForecastDataset.data_path = 'stocks/OXY_2019.csv.gz' +ForecastDataset.target = 'RSMKs_18_144_72' +ForecastDataset.scale = True +ForecastDataset.cross_learn = False +ForecastDataset.time_features = [] +ForecastDataset.normalise_time_features = True +ForecastDataset.features = 'S' +ForecastDataset.horizon_len = 6 +ForecastDataset.lookback_mult = 8 diff --git a/experiments/configs/Stocks/96Sshort.gin b/experiments/configs/Stocks/96Sshort.gin new file mode 100644 index 0000000..e2babe4 --- /dev/null +++ b/experiments/configs/Stocks/96Sshort.gin @@ -0,0 +1,37 @@ +build.experiment_name = 'Stocks/96Sshort' +build.module = 'experiments.forecast' +build.repeat = 1 +build.variables_dict = { +} + +instance.model_type = 'deeptime' +instance.save_vals = False + +get_optimizer.lr = 1e-3 +get_optimizer.lambda_lr = 1. +get_optimizer.weight_decay = 0. + +get_scheduler.warmup_epochs = 5 + +get_data.batch_size = 256 + +train.loss_name = 'mse' +train.epochs = 50 +train.clip = 10. + +Checkpoint.patience = 7 + +deeptime.layer_size = 256 +deeptime.inr_layers = 5 +deeptime.n_fourier_feats = 4096 +deeptime.scales = [0.01, 0.1, 1, 5, 10, 20, 50, 100] + +ForecastDataset.data_path = 'stocks/OXY_2019.csv.gz' +ForecastDataset.target = 'RSMKs_18_144_72' +ForecastDataset.scale = True +ForecastDataset.cross_learn = False +ForecastDataset.time_features = [] +ForecastDataset.normalise_time_features = True +ForecastDataset.features = 'S' +ForecastDataset.horizon_len = 6 +ForecastDataset.lookback_mult = 8 diff --git a/mjc_notes.md b/mjc_notes.md index 31cde70..c0fe558 100644 --- a/mjc_notes.md +++ b/mjc_notes.md @@ -1,4 +1,5 @@ # install environment + ```sh # try with pip torch WORKS! export PROJ=deeptime @@ -13,11 +14,12 @@ pip install tsai # note that I've also recorded the env in requirements -python -m experiments.forecast --config_path=storage/experiments/Exchange/192S/repeat=0/config.gin run >> storage/experiments/Exchange/192S/repeat=0/instance.log 2>&1% +python -m experiments.forecast --config_path=storage/experiments/Exchange/192S/repeat=0/config.gin run | tee -a storage/experiments/Exchange/192S/repeat=0/instance.log 2>&1% ``` + # run -``` +```sh python -m experiments.forecast --config_path=storage/experiments/Exchange/96S/repeat=0/config.gin run python -m experiments.forecast --config_path=storage/experiments/Exchange/96Splus/repeat=0/config.gin run @@ -31,3 +33,16 @@ python -m experiments.forecast --config_path=storage/experiments/Exchange/96Ssho # Lessons Single variate works much better. The output is not just a straight line. Likely because we have limited the output, not the input + +# stocks + +```sh +python -m experiments.forecast --config_path=experiments/configs/Stocks/96S.gin build_experiment +python -m experiments.forecast --config_path=storage/experiments/Stocks/96S/repeat=0/config.gin run +``` + + +``` +make build-all path=experiments/configs/Stocks +./run.sh +``` diff --git a/run.sh b/run.sh index db83ec1..71d378e 100755 --- a/run.sh +++ b/run.sh @@ -1,4 +1,4 @@ -for dataset in ECL ETTm2 Exchange ILI Traffic Weather; do +for dataset in ECL ETTm2 Exchange ILI Traffic Weather Stocks; do for instance in `/bin/ls -d storage/experiments/$dataset/*/*`; do echo $instance make run command=${instance}/command diff --git a/scratch-single.ipynb b/scratch-single.ipynb index 192f384..2a37ffa 100644 --- a/scratch-single.ipynb +++ b/scratch-single.ipynb @@ -125,25 +125,25 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 34, "id": "768530be", "metadata": { "ExecuteTime": { - "end_time": "2022-11-20T06:28:43.599757Z", - "start_time": "2022-11-20T06:28:43.593884Z" + "end_time": "2022-11-20T06:52:29.098202Z", + "start_time": "2022-11-20T06:52:29.093424Z" } }, "outputs": [], "source": [ "\n", "\n", - "def plot_multi(model_names=[\"deeptime\"], save_paths=[Path(\"storage/experiments/Exchange/96M/repeat=0\")], i=200, title=None, plot=True):\n", - " for j in range(len(model_names)):\n", - " model_name = model_names[j]\n", + "def plot_multi(save_paths=[Path(\"storage/experiments/Exchange/96M/repeat=0\")], i=200, title=None, plot=True):\n", + " for j in range(len(save_paths)):\n", " save_path = save_paths[j]\n", "\n", " gin.clear_config()\n", " gin.parse_config(open(save_path/\"config.gin\"))\n", + " model_name = gin.query_parameter(\"instance.model_type\")\n", "\n", " train_set, train_loader = get_data(flag='train', batch_size=2)\n", "\n", @@ -159,12 +159,6 @@ " x, y, x_time, y_time = map(to_tensor, b)\n", " with torch.no_grad():\n", " forecast = model(x, x_time, y_time)\n", - "\n", - "# if title is None:\n", - "# title = str(save_path).split('/')[-3:]\n", - "# title = \"-\".join(title)\n", - "\n", - "\n", " \n", " colors = list(mcolors.BASE_COLORS.keys())\n", " l = x.shape[1]\n", @@ -175,22 +169,13 @@ " i_past = list(range(l))\n", " i_future = list(range(l, l+l2))\n", "\n", - " linestyles = [ '--', '-.', '-', ':']\n", " if plot:\n", - " ls = linestyles[j]\n", - " print(ls)\n", - " if j==0:\n", - " \n", - " \n", - " for k in range(x.shape[-1]):\n", - " plt.plot(i_past, x2[:, k], c=colors[k], label=f\"var {k}\")\n", - " for k in range(x.shape[-1]):\n", - " plt.plot(i_future, y2[:, k], c=colors[k])\n", + " plt.plot(i_past, x2[:, 0], c=colors[0], label=f\"past\")\n", + " plt.plot(i_future, y2[:, 0], c=colors[0], label=\"future true\", alpha=0.5)\n", " \n", " mtitle = str(save_path).split('/')[-2:-1]\n", " mtitle = \"-\".join(mtitle)\n", - " for k in range(x.shape[-1]):\n", - " plt.plot(i_future, forecast2[:, k], c=colors[j], linestyle=ls, label=f\"{mtitle}\" if k==0 else None)\n", + " plt.plot(i_future, forecast2[:, 0], c=colors[j], linestyle='--', label=f\"{mtitle}\")\n", " plt.legend()\n", " plt.title(title)\n", " return x2, y2, forecast2, i_past, i_future\n" @@ -198,12 +183,25 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, + "id": "739ee5e3", + "metadata": { + "ExecuteTime": { + "end_time": "2022-11-20T06:50:03.264769Z", + "start_time": "2022-11-20T06:50:03.262375Z" + } + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 35, "id": "b8843217", "metadata": { "ExecuteTime": { - "end_time": "2022-11-20T06:28:44.027370Z", - "start_time": "2022-11-20T06:28:43.868638Z" + "end_time": "2022-11-20T06:52:29.508811Z", + "start_time": "2022-11-20T06:52:29.353139Z" } }, "outputs": [ @@ -211,12 +209,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "--\n", "receptive field [552 234 114]=[138 18 2]*[[ 1 1 1]\n", " [ 1 2 4]\n", " [ 1 4 16]\n", - " [ 1 6 36]]\n", - "-.\n" + " [ 1 6 36]]\n" ] }, { @@ -225,13 +221,13 @@ "1" ] }, - "execution_count": 11, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -241,7 +237,7 @@ } ], "source": [ - "plot_multi(model_names=[\"deeptime\", \"deeptime2\"],\n", + "plot_multi(\n", " save_paths=[\n", " Path(\"storage/experiments/Exchange/96S/repeat=0\"),\n", " Path(\"storage/experiments/Exchange/96Splus/repeat=0\"),\n", @@ -253,12 +249,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 36, "id": "d39ba7c5", "metadata": { "ExecuteTime": { - "end_time": "2022-11-20T06:28:44.558033Z", - "start_time": "2022-11-20T06:28:44.028541Z" + "end_time": "2022-11-20T06:52:41.798916Z", + "start_time": "2022-11-20T06:52:41.260013Z" } }, "outputs": [ @@ -266,13 +262,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "--\n", "receptive field [690 378 242]=[138 18 2]*[[ 1 1 1]\n", " [ 1 2 4]\n", " [ 1 4 16]\n", " [ 1 6 36]\n", - " [ 1 8 64]]\n", - "-.\n" + " [ 1 8 64]]\n" ] }, { @@ -281,13 +275,13 @@ "1" ] }, - "execution_count": 12, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -297,7 +291,7 @@ } ], "source": [ - "plot_multi(model_names=[\"deeptime\", \"deeptime2\"],\n", + "plot_multi(\n", " save_paths=[\n", " Path(\"storage/experiments/Exchange/96Sshort/repeat=0\"),\n", " Path(\"storage/experiments/Exchange/96Splusshort/repeat=0\"),\n", diff --git a/storage/datasets/stocks/OXY_2019.csv.gz b/storage/datasets/stocks/OXY_2019.csv.gz new file mode 100644 index 0000000..49330b1 Binary files /dev/null and b/storage/datasets/stocks/OXY_2019.csv.gz differ diff --git a/storage/datasets/stocks/OXY_2020.csv.gz b/storage/datasets/stocks/OXY_2020.csv.gz new file mode 100644 index 0000000..6b1e22d Binary files /dev/null and b/storage/datasets/stocks/OXY_2020.csv.gz differ