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freedakgmail
2026-07-01 21:06:59 +08:00
parent 97d873b6dc
commit bc7283747f
12 changed files with 2 additions and 12197 deletions
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.gitignore
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@@ -9,3 +9,5 @@ results/
uv.lock
development_setup.md
debug.log
# Generated output files
timesfm-forecasting/examples/*/output/
timesfm-forecasting/examples/anomaly-detection/output/anomaly_detection.json
-448
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@@ -1,448 +0,0 @@
{
"method": "two_phase",
"context_method": "linear_detrend_zscore",
"forecast_method": "quantile_prediction_intervals",
"thresholds": {
"critical_z": 3.0,
"warning_z": 2.0,
"pi_critical_pct": 80,
"pi_warning_pct": 60
},
"context_summary": {
"total": 36,
"critical": 1,
"warning": 0,
"normal": 35,
"res_std": 0.11362
},
"forecast_summary": {
"total": 12,
"critical": 4,
"warning": 1,
"normal": 7
},
"context_detections": [
{
"date": "2022-01",
"value": 0.89,
"trend": 0.837,
"residual": 0.053,
"z_score": 0.467,
"severity": "NORMAL"
},
{
"date": "2022-02",
"value": 0.89,
"trend": 0.8514,
"residual": 0.0386,
"z_score": 0.34,
"severity": "NORMAL"
},
{
"date": "2022-03",
"value": 1.02,
"trend": 0.8658,
"residual": 0.1542,
"z_score": 1.357,
"severity": "NORMAL"
},
{
"date": "2022-04",
"value": 0.88,
"trend": 0.8803,
"residual": -0.0003,
"z_score": -0.002,
"severity": "NORMAL"
},
{
"date": "2022-05",
"value": 0.85,
"trend": 0.8947,
"residual": -0.0447,
"z_score": -0.394,
"severity": "NORMAL"
},
{
"date": "2022-06",
"value": 0.88,
"trend": 0.9092,
"residual": -0.0292,
"z_score": -0.257,
"severity": "NORMAL"
},
{
"date": "2022-07",
"value": 0.88,
"trend": 0.9236,
"residual": -0.0436,
"z_score": -0.384,
"severity": "NORMAL"
},
{
"date": "2022-08",
"value": 0.9,
"trend": 0.9381,
"residual": -0.0381,
"z_score": -0.335,
"severity": "NORMAL"
},
{
"date": "2022-09",
"value": 0.88,
"trend": 0.9525,
"residual": -0.0725,
"z_score": -0.638,
"severity": "NORMAL"
},
{
"date": "2022-10",
"value": 0.95,
"trend": 0.9669,
"residual": -0.0169,
"z_score": -0.149,
"severity": "NORMAL"
},
{
"date": "2022-11",
"value": 0.77,
"trend": 0.9814,
"residual": -0.2114,
"z_score": -1.86,
"severity": "NORMAL"
},
{
"date": "2022-12",
"value": 0.78,
"trend": 0.9958,
"residual": -0.2158,
"z_score": -1.9,
"severity": "NORMAL"
},
{
"date": "2023-01",
"value": 0.87,
"trend": 1.0103,
"residual": -0.1403,
"z_score": -1.235,
"severity": "NORMAL"
},
{
"date": "2023-02",
"value": 0.98,
"trend": 1.0247,
"residual": -0.0447,
"z_score": -0.394,
"severity": "NORMAL"
},
{
"date": "2023-03",
"value": 1.21,
"trend": 1.0392,
"residual": 0.1708,
"z_score": 1.503,
"severity": "NORMAL"
},
{
"date": "2023-04",
"value": 1.0,
"trend": 1.0536,
"residual": -0.0536,
"z_score": -0.472,
"severity": "NORMAL"
},
{
"date": "2023-05",
"value": 0.94,
"trend": 1.0681,
"residual": -0.1281,
"z_score": -1.127,
"severity": "NORMAL"
},
{
"date": "2023-06",
"value": 1.08,
"trend": 1.0825,
"residual": -0.0025,
"z_score": -0.022,
"severity": "NORMAL"
},
{
"date": "2023-07",
"value": 1.18,
"trend": 1.0969,
"residual": 0.0831,
"z_score": 0.731,
"severity": "NORMAL"
},
{
"date": "2023-08",
"value": 1.24,
"trend": 1.1114,
"residual": 0.1286,
"z_score": 1.132,
"severity": "NORMAL"
},
{
"date": "2023-09",
"value": 1.47,
"trend": 1.1258,
"residual": 0.3442,
"z_score": 3.029,
"severity": "CRITICAL"
},
{
"date": "2023-10",
"value": 1.32,
"trend": 1.1403,
"residual": 0.1797,
"z_score": 1.582,
"severity": "NORMAL"
},
{
"date": "2023-11",
"value": 1.18,
"trend": 1.1547,
"residual": 0.0253,
"z_score": 0.222,
"severity": "NORMAL"
},
{
"date": "2023-12",
"value": 1.16,
"trend": 1.1692,
"residual": -0.0092,
"z_score": -0.081,
"severity": "NORMAL"
},
{
"date": "2024-01",
"value": 1.22,
"trend": 1.1836,
"residual": 0.0364,
"z_score": 0.32,
"severity": "NORMAL"
},
{
"date": "2024-02",
"value": 1.35,
"trend": 1.1981,
"residual": 0.1519,
"z_score": 1.337,
"severity": "NORMAL"
},
{
"date": "2024-03",
"value": 1.34,
"trend": 1.2125,
"residual": 0.1275,
"z_score": 1.122,
"severity": "NORMAL"
},
{
"date": "2024-04",
"value": 1.26,
"trend": 1.2269,
"residual": 0.0331,
"z_score": 0.291,
"severity": "NORMAL"
},
{
"date": "2024-05",
"value": 1.15,
"trend": 1.2414,
"residual": -0.0914,
"z_score": -0.804,
"severity": "NORMAL"
},
{
"date": "2024-06",
"value": 1.2,
"trend": 1.2558,
"residual": -0.0558,
"z_score": -0.491,
"severity": "NORMAL"
},
{
"date": "2024-07",
"value": 1.24,
"trend": 1.2703,
"residual": -0.0303,
"z_score": -0.266,
"severity": "NORMAL"
},
{
"date": "2024-08",
"value": 1.3,
"trend": 1.2847,
"residual": 0.0153,
"z_score": 0.135,
"severity": "NORMAL"
},
{
"date": "2024-09",
"value": 1.28,
"trend": 1.2992,
"residual": -0.0192,
"z_score": -0.169,
"severity": "NORMAL"
},
{
"date": "2024-10",
"value": 1.27,
"trend": 1.3136,
"residual": -0.0436,
"z_score": -0.384,
"severity": "NORMAL"
},
{
"date": "2024-11",
"value": 1.22,
"trend": 1.328,
"residual": -0.108,
"z_score": -0.951,
"severity": "NORMAL"
},
{
"date": "2024-12",
"value": 1.2,
"trend": 1.3425,
"residual": -0.1425,
"z_score": -1.254,
"severity": "NORMAL"
}
],
"forecast_detections": [
{
"date": "2025-01",
"actual": 1.2821,
"forecast": 1.2593,
"q10": 1.1407,
"q20": 1.1881,
"q80": 1.324,
"q90": 1.3679,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-02",
"actual": 1.1522,
"forecast": 1.2857,
"q10": 1.1406,
"q20": 1.1961,
"q80": 1.3751,
"q90": 1.4254,
"severity": "WARNING",
"was_injected": false
},
{
"date": "2025-03",
"actual": 1.3358,
"forecast": 1.295,
"q10": 1.1269,
"q20": 1.1876,
"q80": 1.4035,
"q90": 1.4643,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-04",
"actual": 2.0594,
"forecast": 1.2208,
"q10": 1.0353,
"q20": 1.1042,
"q80": 1.331,
"q90": 1.4017,
"severity": "CRITICAL",
"was_injected": true
},
{
"date": "2025-05",
"actual": 1.0747,
"forecast": 1.1703,
"q10": 0.9691,
"q20": 1.0431,
"q80": 1.2892,
"q90": 1.3632,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-06",
"actual": 1.1442,
"forecast": 1.1456,
"q10": 0.942,
"q20": 1.0111,
"q80": 1.2703,
"q90": 1.3454,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-07",
"actual": 1.2917,
"forecast": 1.1702,
"q10": 0.9504,
"q20": 1.0348,
"q80": 1.2998,
"q90": 1.3807,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-08",
"actual": 1.2519,
"forecast": 1.2027,
"q10": 0.9709,
"q20": 1.0594,
"q80": 1.3408,
"q90": 1.4195,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-09",
"actual": 0.6364,
"forecast": 1.191,
"q10": 0.9594,
"q20": 1.0404,
"q80": 1.3355,
"q90": 1.417,
"severity": "CRITICAL",
"was_injected": true
},
{
"date": "2025-10",
"actual": 1.2073,
"forecast": 1.1491,
"q10": 0.9079,
"q20": 0.9953,
"q80": 1.2869,
"q90": 1.3775,
"severity": "NORMAL",
"was_injected": false
},
{
"date": "2025-11",
"actual": 1.3851,
"forecast": 1.0805,
"q10": 0.8361,
"q20": 0.926,
"q80": 1.2284,
"q90": 1.3122,
"severity": "CRITICAL",
"was_injected": false
},
{
"date": "2025-12",
"actual": 1.8294,
"forecast": 1.0613,
"q10": 0.8022,
"q20": 0.8952,
"q80": 1.2169,
"q90": 1.296,
"severity": "CRITICAL",
"was_injected": true
}
]
}
timesfm-forecasting/examples/anomaly-detection/output/anomaly_detection.png
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timesfm-forecasting/examples/covariates-forecasting/output/covariates_data.png
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timesfm-forecasting/examples/covariates-forecasting/output/covariates_metadata.json
-59
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@@ -1,59 +0,0 @@
{
"description": "Synthetic retail sales data with covariates for TimesFM XReg demo",
"note_on_real_data": "For real datasets (e.g., Kaggle Rossmann Store Sales), download to tempfile.mkdtemp() -- do NOT commit to this repo.",
"stores": {
"store_A": {
"type": "premium",
"region": "urban",
"base_sales": 1000,
"mean_sales_context": 1148.7
},
"store_B": {
"type": "standard",
"region": "suburban",
"base_sales": 750,
"mean_sales_context": 907.0
},
"store_C": {
"type": "discount",
"region": "rural",
"base_sales": 500,
"mean_sales_context": 645.3
}
},
"dimensions": {
"context_length": 24,
"horizon_length": 12,
"total_length": 36,
"num_stores": 3,
"csv_rows": 108
},
"covariates": {
"dynamic_numerical": [
"price"
],
"dynamic_categorical": [
"promotion",
"holiday",
"day_of_week"
],
"static_categorical": [
"store_type",
"region"
]
},
"effect_magnitudes": {
"holiday": "+200 units per holiday week",
"promotion": "+150 units per promotion week",
"price": "-20 units per $1 above base price"
},
"xreg_modes": {
"xreg + timesfm": "Regression on TimesFM residuals (default)",
"timesfm + xreg": "TimesFM on regression residuals"
},
"bug_fixes_history": [
"v1: Variable-shadowing -- all stores had identical covariates",
"v2: Fixed shadowing; CONTEXT_LEN 48->24",
"v3: Added component decomposition (base, price/promo/holiday effects); 2x2 sharex viz"
]
}
timesfm-forecasting/examples/covariates-forecasting/output/sales_with_covariates.csv
-109
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@@ -1,109 +0,0 @@
store_id,week,split,sales,base_sales,price,price_effect,promotion,holiday,day_of_week,store_type,region
store_A,0,context,1369.59,1012.19,11.6299,7.4,1,1,0,premium,urban
store_A,1,context,973.53,973.04,11.9757,0.49,0,0,1,premium,urban
store_A,2,context,1064.63,1059.16,11.7269,5.46,0,0,2,premium,urban
store_A,3,context,1077.59,1080.99,12.1698,-3.4,0,0,3,premium,urban
store_A,4,context,980.39,979.14,11.9372,1.26,0,0,4,premium,urban
store_A,5,context,1011.7,1018.36,12.3327,-6.65,0,0,5,premium,urban
store_A,6,context,1084.16,1088.16,12.2003,-4.01,0,0,6,premium,urban
store_A,7,context,1085.98,1082.23,11.8124,3.75,0,0,0,premium,urban
store_A,8,context,1098.52,1105.17,12.3323,-6.65,0,0,1,premium,urban
store_A,9,context,1075.62,1081.71,12.3048,-6.1,0,0,2,premium,urban
store_A,10,context,1312.23,1159.98,11.8875,2.25,1,0,3,premium,urban
store_A,11,context,1368.02,1163.79,11.7883,4.23,0,1,4,premium,urban
store_A,12,context,1138.41,1142.06,12.1825,-3.65,0,0,5,premium,urban
store_A,13,context,1197.29,1190.09,11.6398,7.2,0,0,6,premium,urban
store_A,14,context,1174.12,1168.12,11.6999,6.0,0,0,0,premium,urban
store_A,15,context,1128.16,1118.3,11.5074,9.85,0,0,1,premium,urban
store_A,16,context,1163.81,1169.55,12.2869,-5.74,0,0,2,premium,urban
store_A,17,context,1114.18,1117.48,12.1649,-3.3,0,0,3,premium,urban
store_A,18,context,1186.87,1190.98,12.2052,-4.1,0,0,4,premium,urban
store_A,19,context,1147.27,1152.88,12.2807,-5.61,0,0,5,premium,urban
store_A,20,context,1146.48,1145.66,11.9589,0.82,0,0,6,premium,urban
store_A,21,context,1121.83,1123.21,12.0687,-1.37,0,0,0,premium,urban
store_A,22,context,1203.28,1196.08,11.6398,7.2,0,0,1,premium,urban
store_A,23,context,1344.9,1137.19,11.6145,7.71,0,1,2,premium,urban
store_A,24,horizon,1118.64,1122.01,12.1684,-3.37,0,0,3,premium,urban
store_A,25,horizon,1121.14,1120.56,11.9711,0.58,0,0,4,premium,urban
store_A,26,horizon,1149.99,1151.29,12.0652,-1.3,0,0,5,premium,urban
store_A,27,horizon,1284.67,1139.97,12.265,-5.3,1,0,6,premium,urban
store_A,28,horizon,1284.67,1137.36,12.1347,-2.69,1,0,0,premium,urban
store_A,29,horizon,1132.79,1133.86,12.0536,-1.07,0,0,1,premium,urban
store_A,30,horizon,1197.3,1198.49,12.0592,-1.18,0,0,2,premium,urban
store_A,31,horizon,1247.22,1093.3,11.804,3.92,1,0,3,premium,urban
store_A,32,horizon,1095.84,1086.46,11.5308,9.38,0,0,4,premium,urban
store_A,33,horizon,1073.83,1072.57,11.9367,1.27,0,0,5,premium,urban
store_A,34,horizon,1134.51,1128.8,11.7146,5.71,0,0,6,premium,urban
store_A,35,horizon,1351.15,1149.32,11.9085,1.83,0,1,0,premium,urban
store_B,0,context,1062.53,712.0,9.9735,0.53,1,1,0,standard,suburban
store_B,1,context,904.49,749.83,9.767,4.66,1,0,1,standard,suburban
store_B,2,context,813.63,810.26,9.8316,3.37,0,0,2,standard,suburban
store_B,3,context,720.11,720.53,10.0207,-0.41,0,0,3,standard,suburban
store_B,4,context,820.78,819.55,9.9389,1.22,0,0,4,standard,suburban
store_B,5,context,833.27,823.7,9.5216,9.57,0,0,5,standard,suburban
store_B,6,context,795.26,801.78,10.3263,-6.53,0,0,6,standard,suburban
store_B,7,context,770.37,778.29,10.3962,-7.92,0,0,0,standard,suburban
store_B,8,context,855.92,848.72,9.6402,7.2,0,0,1,standard,suburban
store_B,9,context,832.33,833.41,10.054,-1.08,0,0,2,standard,suburban
store_B,10,context,1029.44,871.61,9.6086,7.83,1,0,3,standard,suburban
store_B,11,context,1066.35,869.8,10.1722,-3.44,0,1,4,standard,suburban
store_B,12,context,942.86,938.49,9.7812,4.38,0,0,5,standard,suburban
store_B,13,context,1015.99,869.18,10.1594,-3.19,1,0,6,standard,suburban
store_B,14,context,836.44,840.98,10.227,-4.54,0,0,0,standard,suburban
store_B,15,context,885.72,891.1,10.2686,-5.37,0,0,1,standard,suburban
store_B,16,context,901.45,893.6,9.6077,7.85,0,0,2,standard,suburban
store_B,17,context,1080.63,938.95,10.416,-8.32,1,0,3,standard,suburban
store_B,18,context,922.14,916.74,9.7302,5.4,0,0,4,standard,suburban
store_B,19,context,904.66,895.41,9.5374,9.25,0,0,5,standard,suburban
store_B,20,context,935.48,936.58,10.0549,-1.1,0,0,6,standard,suburban
store_B,21,context,979.23,826.64,9.8709,2.58,1,0,0,standard,suburban
store_B,22,context,837.49,844.09,10.3298,-6.6,0,0,1,standard,suburban
store_B,23,context,1021.39,827.56,10.3083,-6.17,0,1,2,standard,suburban
store_B,24,horizon,847.21,843.55,9.8171,3.66,0,0,3,standard,suburban
store_B,25,horizon,789.27,798.33,10.4529,-9.06,0,0,4,standard,suburban
store_B,26,horizon,877.09,872.91,9.7909,4.18,0,0,5,standard,suburban
store_B,27,horizon,832.42,832.72,10.0151,-0.3,0,0,6,standard,suburban
store_B,28,horizon,781.9,777.02,9.756,4.88,0,0,0,standard,suburban
store_B,29,horizon,781.04,789.76,10.436,-8.72,0,0,1,standard,suburban
store_B,30,horizon,844.57,837.86,9.6646,6.71,0,0,2,standard,suburban
store_B,31,horizon,863.43,854.33,9.5449,9.1,0,0,3,standard,suburban
store_B,32,horizon,898.12,896.82,9.9351,1.3,0,0,4,standard,suburban
store_B,33,horizon,1070.58,930.42,10.4924,-9.85,1,0,5,standard,suburban
store_B,34,horizon,820.4,828.24,10.3917,-7.83,0,0,6,standard,suburban
store_B,35,horizon,965.86,770.83,10.2486,-4.97,0,1,0,standard,suburban
store_C,0,context,709.12,501.23,7.1053,7.89,0,1,0,discount,rural
store_C,1,context,651.44,492.78,7.0666,8.67,1,0,1,discount,rural
store_C,2,context,659.15,511.04,7.5944,-1.89,1,0,2,discount,rural
store_C,3,context,733.06,575.98,7.1462,7.08,1,0,3,discount,rural
store_C,4,context,712.21,568.7,7.8247,-6.49,1,0,4,discount,rural
store_C,5,context,615.23,611.44,7.3103,3.79,0,0,5,discount,rural
store_C,6,context,568.99,561.87,7.1439,7.12,0,0,6,discount,rural
store_C,7,context,541.12,549.54,7.921,-8.42,0,0,0,discount,rural
store_C,8,context,583.57,576.88,7.1655,6.69,0,0,1,discount,rural
store_C,9,context,607.34,603.04,7.2847,4.31,0,0,2,discount,rural
store_C,10,context,613.79,606.86,7.1536,6.93,0,0,3,discount,rural
store_C,11,context,919.49,561.8,7.1155,7.69,1,1,4,discount,rural
store_C,12,context,622.61,613.04,7.0211,9.58,0,0,5,discount,rural
store_C,13,context,630.52,621.63,7.0554,8.89,0,0,6,discount,rural
store_C,14,context,721.62,715.12,7.1746,6.51,0,0,0,discount,rural
store_C,15,context,699.18,690.25,7.0534,8.93,0,0,1,discount,rural
store_C,16,context,578.85,580.67,7.5911,-1.82,0,0,2,discount,rural
store_C,17,context,598.23,601.84,7.6807,-3.61,0,0,3,discount,rural
store_C,18,context,554.43,552.3,7.3936,2.13,0,0,4,discount,rural
store_C,19,context,587.39,583.75,7.318,3.64,0,0,5,discount,rural
store_C,20,context,615.58,615.67,7.5045,-0.09,0,0,6,discount,rural
store_C,21,context,638.68,646.18,7.875,-7.5,0,0,0,discount,rural
store_C,22,context,555.99,563.01,7.8511,-7.02,0,0,1,discount,rural
store_C,23,context,768.83,559.7,7.0435,9.13,0,1,2,discount,rural
store_C,24,horizon,499.62,493.25,7.1815,6.37,0,0,3,discount,rural
store_C,25,horizon,570.9,565.64,7.2367,5.27,0,0,4,discount,rural
store_C,26,horizon,677.52,522.5,7.2494,5.01,1,0,5,discount,rural
store_C,27,horizon,685.25,536.68,7.5712,-1.42,1,0,6,discount,rural
store_C,28,horizon,517.46,515.78,7.4163,1.67,0,0,0,discount,rural
store_C,29,horizon,549.38,540.36,7.0493,9.01,0,0,1,discount,rural
store_C,30,horizon,470.04,467.51,7.3736,2.53,0,0,2,discount,rural
store_C,31,horizon,622.9,473.37,7.5238,-0.48,1,0,3,discount,rural
store_C,32,horizon,620.09,612.12,7.1017,7.97,0,0,4,discount,rural
store_C,33,horizon,614.45,471.12,7.8335,-6.67,1,0,5,discount,rural
store_C,34,horizon,484.25,475.29,7.052,8.96,0,0,6,discount,rural
store_C,35,horizon,781.64,590.14,7.9248,-8.5,0,1,0,discount,rural
1 store_id week split sales base_sales price price_effect promotion holiday day_of_week store_type region
2 store_A 0 context 1369.59 1012.19 11.6299 7.4 1 1 0 premium urban
3 store_A 1 context 973.53 973.04 11.9757 0.49 0 0 1 premium urban
4 store_A 2 context 1064.63 1059.16 11.7269 5.46 0 0 2 premium urban
5 store_A 3 context 1077.59 1080.99 12.1698 -3.4 0 0 3 premium urban
6 store_A 4 context 980.39 979.14 11.9372 1.26 0 0 4 premium urban
7 store_A 5 context 1011.7 1018.36 12.3327 -6.65 0 0 5 premium urban
8 store_A 6 context 1084.16 1088.16 12.2003 -4.01 0 0 6 premium urban
9 store_A 7 context 1085.98 1082.23 11.8124 3.75 0 0 0 premium urban
10 store_A 8 context 1098.52 1105.17 12.3323 -6.65 0 0 1 premium urban
11 store_A 9 context 1075.62 1081.71 12.3048 -6.1 0 0 2 premium urban
12 store_A 10 context 1312.23 1159.98 11.8875 2.25 1 0 3 premium urban
13 store_A 11 context 1368.02 1163.79 11.7883 4.23 0 1 4 premium urban
14 store_A 12 context 1138.41 1142.06 12.1825 -3.65 0 0 5 premium urban
15 store_A 13 context 1197.29 1190.09 11.6398 7.2 0 0 6 premium urban
16 store_A 14 context 1174.12 1168.12 11.6999 6.0 0 0 0 premium urban
17 store_A 15 context 1128.16 1118.3 11.5074 9.85 0 0 1 premium urban
18 store_A 16 context 1163.81 1169.55 12.2869 -5.74 0 0 2 premium urban
19 store_A 17 context 1114.18 1117.48 12.1649 -3.3 0 0 3 premium urban
20 store_A 18 context 1186.87 1190.98 12.2052 -4.1 0 0 4 premium urban
21 store_A 19 context 1147.27 1152.88 12.2807 -5.61 0 0 5 premium urban
22 store_A 20 context 1146.48 1145.66 11.9589 0.82 0 0 6 premium urban
23 store_A 21 context 1121.83 1123.21 12.0687 -1.37 0 0 0 premium urban
24 store_A 22 context 1203.28 1196.08 11.6398 7.2 0 0 1 premium urban
25 store_A 23 context 1344.9 1137.19 11.6145 7.71 0 1 2 premium urban
26 store_A 24 horizon 1118.64 1122.01 12.1684 -3.37 0 0 3 premium urban
27 store_A 25 horizon 1121.14 1120.56 11.9711 0.58 0 0 4 premium urban
28 store_A 26 horizon 1149.99 1151.29 12.0652 -1.3 0 0 5 premium urban
29 store_A 27 horizon 1284.67 1139.97 12.265 -5.3 1 0 6 premium urban
30 store_A 28 horizon 1284.67 1137.36 12.1347 -2.69 1 0 0 premium urban
31 store_A 29 horizon 1132.79 1133.86 12.0536 -1.07 0 0 1 premium urban
32 store_A 30 horizon 1197.3 1198.49 12.0592 -1.18 0 0 2 premium urban
33 store_A 31 horizon 1247.22 1093.3 11.804 3.92 1 0 3 premium urban
34 store_A 32 horizon 1095.84 1086.46 11.5308 9.38 0 0 4 premium urban
35 store_A 33 horizon 1073.83 1072.57 11.9367 1.27 0 0 5 premium urban
36 store_A 34 horizon 1134.51 1128.8 11.7146 5.71 0 0 6 premium urban
37 store_A 35 horizon 1351.15 1149.32 11.9085 1.83 0 1 0 premium urban
38 store_B 0 context 1062.53 712.0 9.9735 0.53 1 1 0 standard suburban
39 store_B 1 context 904.49 749.83 9.767 4.66 1 0 1 standard suburban
40 store_B 2 context 813.63 810.26 9.8316 3.37 0 0 2 standard suburban
41 store_B 3 context 720.11 720.53 10.0207 -0.41 0 0 3 standard suburban
42 store_B 4 context 820.78 819.55 9.9389 1.22 0 0 4 standard suburban
43 store_B 5 context 833.27 823.7 9.5216 9.57 0 0 5 standard suburban
44 store_B 6 context 795.26 801.78 10.3263 -6.53 0 0 6 standard suburban
45 store_B 7 context 770.37 778.29 10.3962 -7.92 0 0 0 standard suburban
46 store_B 8 context 855.92 848.72 9.6402 7.2 0 0 1 standard suburban
47 store_B 9 context 832.33 833.41 10.054 -1.08 0 0 2 standard suburban
48 store_B 10 context 1029.44 871.61 9.6086 7.83 1 0 3 standard suburban
49 store_B 11 context 1066.35 869.8 10.1722 -3.44 0 1 4 standard suburban
50 store_B 12 context 942.86 938.49 9.7812 4.38 0 0 5 standard suburban
51 store_B 13 context 1015.99 869.18 10.1594 -3.19 1 0 6 standard suburban
52 store_B 14 context 836.44 840.98 10.227 -4.54 0 0 0 standard suburban
53 store_B 15 context 885.72 891.1 10.2686 -5.37 0 0 1 standard suburban
54 store_B 16 context 901.45 893.6 9.6077 7.85 0 0 2 standard suburban
55 store_B 17 context 1080.63 938.95 10.416 -8.32 1 0 3 standard suburban
56 store_B 18 context 922.14 916.74 9.7302 5.4 0 0 4 standard suburban
57 store_B 19 context 904.66 895.41 9.5374 9.25 0 0 5 standard suburban
58 store_B 20 context 935.48 936.58 10.0549 -1.1 0 0 6 standard suburban
59 store_B 21 context 979.23 826.64 9.8709 2.58 1 0 0 standard suburban
60 store_B 22 context 837.49 844.09 10.3298 -6.6 0 0 1 standard suburban
61 store_B 23 context 1021.39 827.56 10.3083 -6.17 0 1 2 standard suburban
62 store_B 24 horizon 847.21 843.55 9.8171 3.66 0 0 3 standard suburban
63 store_B 25 horizon 789.27 798.33 10.4529 -9.06 0 0 4 standard suburban
64 store_B 26 horizon 877.09 872.91 9.7909 4.18 0 0 5 standard suburban
65 store_B 27 horizon 832.42 832.72 10.0151 -0.3 0 0 6 standard suburban
66 store_B 28 horizon 781.9 777.02 9.756 4.88 0 0 0 standard suburban
67 store_B 29 horizon 781.04 789.76 10.436 -8.72 0 0 1 standard suburban
68 store_B 30 horizon 844.57 837.86 9.6646 6.71 0 0 2 standard suburban
69 store_B 31 horizon 863.43 854.33 9.5449 9.1 0 0 3 standard suburban
70 store_B 32 horizon 898.12 896.82 9.9351 1.3 0 0 4 standard suburban
71 store_B 33 horizon 1070.58 930.42 10.4924 -9.85 1 0 5 standard suburban
72 store_B 34 horizon 820.4 828.24 10.3917 -7.83 0 0 6 standard suburban
73 store_B 35 horizon 965.86 770.83 10.2486 -4.97 0 1 0 standard suburban
74 store_C 0 context 709.12 501.23 7.1053 7.89 0 1 0 discount rural
75 store_C 1 context 651.44 492.78 7.0666 8.67 1 0 1 discount rural
76 store_C 2 context 659.15 511.04 7.5944 -1.89 1 0 2 discount rural
77 store_C 3 context 733.06 575.98 7.1462 7.08 1 0 3 discount rural
78 store_C 4 context 712.21 568.7 7.8247 -6.49 1 0 4 discount rural
79 store_C 5 context 615.23 611.44 7.3103 3.79 0 0 5 discount rural
80 store_C 6 context 568.99 561.87 7.1439 7.12 0 0 6 discount rural
81 store_C 7 context 541.12 549.54 7.921 -8.42 0 0 0 discount rural
82 store_C 8 context 583.57 576.88 7.1655 6.69 0 0 1 discount rural
83 store_C 9 context 607.34 603.04 7.2847 4.31 0 0 2 discount rural
84 store_C 10 context 613.79 606.86 7.1536 6.93 0 0 3 discount rural
85 store_C 11 context 919.49 561.8 7.1155 7.69 1 1 4 discount rural
86 store_C 12 context 622.61 613.04 7.0211 9.58 0 0 5 discount rural
87 store_C 13 context 630.52 621.63 7.0554 8.89 0 0 6 discount rural
88 store_C 14 context 721.62 715.12 7.1746 6.51 0 0 0 discount rural
89 store_C 15 context 699.18 690.25 7.0534 8.93 0 0 1 discount rural
90 store_C 16 context 578.85 580.67 7.5911 -1.82 0 0 2 discount rural
91 store_C 17 context 598.23 601.84 7.6807 -3.61 0 0 3 discount rural
92 store_C 18 context 554.43 552.3 7.3936 2.13 0 0 4 discount rural
93 store_C 19 context 587.39 583.75 7.318 3.64 0 0 5 discount rural
94 store_C 20 context 615.58 615.67 7.5045 -0.09 0 0 6 discount rural
95 store_C 21 context 638.68 646.18 7.875 -7.5 0 0 0 discount rural
96 store_C 22 context 555.99 563.01 7.8511 -7.02 0 0 1 discount rural
97 store_C 23 context 768.83 559.7 7.0435 9.13 0 1 2 discount rural
98 store_C 24 horizon 499.62 493.25 7.1815 6.37 0 0 3 discount rural
99 store_C 25 horizon 570.9 565.64 7.2367 5.27 0 0 4 discount rural
100 store_C 26 horizon 677.52 522.5 7.2494 5.01 1 0 5 discount rural
101 store_C 27 horizon 685.25 536.68 7.5712 -1.42 1 0 6 discount rural
102 store_C 28 horizon 517.46 515.78 7.4163 1.67 0 0 0 discount rural
103 store_C 29 horizon 549.38 540.36 7.0493 9.01 0 0 1 discount rural
104 store_C 30 horizon 470.04 467.51 7.3736 2.53 0 0 2 discount rural
105 store_C 31 horizon 622.9 473.37 7.5238 -0.48 1 0 3 discount rural
106 store_C 32 horizon 620.09 612.12 7.1017 7.97 0 0 4 discount rural
107 store_C 33 horizon 614.45 471.12 7.8335 -6.67 1 0 5 discount rural
108 store_C 34 horizon 484.25 475.29 7.052 8.96 0 0 6 discount rural
109 store_C 35 horizon 781.64 590.14 7.9248 -8.5 0 1 0 discount rural
timesfm-forecasting/examples/global-temperature/output/animation_data.json
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timesfm-forecasting/examples/global-temperature/output/forecast_output.csv
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date,point_forecast,mean,q10,q20,q30,q40,q50,q60,q70,q80,q90
2025-01-01,1.2223774,1.2215943,1.1230627,1.1613995,1.1832488,1.2030286,1.2223774,1.240989,1.2626991,1.2927711,1.339603
2025-02-01,1.2563584,1.2502017,1.1482248,1.1891649,1.2134029,1.2355918,1.2563584,1.2787917,1.3061507,1.3358022,1.3880283
2025-03-01,1.286477,1.2816916,1.1694773,1.2141376,1.2430503,1.2636719,1.286477,1.3101407,1.3365126,1.3725822,1.4265702
2025-04-01,1.240488,1.2406754,1.119298,1.1689228,1.1957527,1.2162383,1.240488,1.265359,1.2880774,1.3237736,1.3806401
2025-05-01,1.2026378,1.1969143,1.0776879,1.1280149,1.1554759,1.1801765,1.2026378,1.2274072,1.2546852,1.2890899,1.3469675
2025-06-01,1.21002,1.1963896,1.0811386,1.1352499,1.1687461,1.1853771,1.21002,1.2333429,1.255994,1.2938039,1.3532466
2025-07-01,1.2253109,1.2151253,1.0917634,1.1474797,1.176413,1.2029413,1.2253109,1.250956,1.2764856,1.3113455,1.3728349
2025-08-01,1.2421811,1.2292916,1.1043029,1.1598811,1.1929151,1.2164187,1.2421811,1.266998,1.2924675,1.3304923,1.394975
2025-09-01,1.269735,1.2603163,1.1239274,1.1872942,1.2162873,1.242951,1.269735,1.2976494,1.3236798,1.3580028,1.4252181
2025-10-01,1.2496669,1.2436218,1.0962446,1.1630417,1.1938806,1.221712,1.2496669,1.2757387,1.3041382,1.3376691,1.409816
2025-11-01,1.2135266,1.2031629,1.0545524,1.1223581,1.157211,1.1864623,1.2135266,1.2447275,1.2706528,1.3091388,1.3801678
2025-12-01,1.2034141,1.1867243,1.0412307,1.1113251,1.1433371,1.1752325,1.2034141,1.2308054,1.2621957,1.2912495,1.370078
1 date point_forecast mean q10 q20 q30 q40 q50 q60 q70 q80 q90
2 2025-01-01 1.2223774 1.2215943 1.1230627 1.1613995 1.1832488 1.2030286 1.2223774 1.240989 1.2626991 1.2927711 1.339603
3 2025-02-01 1.2563584 1.2502017 1.1482248 1.1891649 1.2134029 1.2355918 1.2563584 1.2787917 1.3061507 1.3358022 1.3880283
4 2025-03-01 1.286477 1.2816916 1.1694773 1.2141376 1.2430503 1.2636719 1.286477 1.3101407 1.3365126 1.3725822 1.4265702
5 2025-04-01 1.240488 1.2406754 1.119298 1.1689228 1.1957527 1.2162383 1.240488 1.265359 1.2880774 1.3237736 1.3806401
6 2025-05-01 1.2026378 1.1969143 1.0776879 1.1280149 1.1554759 1.1801765 1.2026378 1.2274072 1.2546852 1.2890899 1.3469675
7 2025-06-01 1.21002 1.1963896 1.0811386 1.1352499 1.1687461 1.1853771 1.21002 1.2333429 1.255994 1.2938039 1.3532466
8 2025-07-01 1.2253109 1.2151253 1.0917634 1.1474797 1.176413 1.2029413 1.2253109 1.250956 1.2764856 1.3113455 1.3728349
9 2025-08-01 1.2421811 1.2292916 1.1043029 1.1598811 1.1929151 1.2164187 1.2421811 1.266998 1.2924675 1.3304923 1.394975
10 2025-09-01 1.269735 1.2603163 1.1239274 1.1872942 1.2162873 1.242951 1.269735 1.2976494 1.3236798 1.3580028 1.4252181
11 2025-10-01 1.2496669 1.2436218 1.0962446 1.1630417 1.1938806 1.221712 1.2496669 1.2757387 1.3041382 1.3376691 1.409816
12 2025-11-01 1.2135266 1.2031629 1.0545524 1.1223581 1.157211 1.1864623 1.2135266 1.2447275 1.2706528 1.3091388 1.3801678
13 2025-12-01 1.2034141 1.1867243 1.0412307 1.1113251 1.1433371 1.1752325 1.2034141 1.2308054 1.2621957 1.2912495 1.370078
timesfm-forecasting/examples/global-temperature/output/forecast_output.json
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{
"model": "TimesFM 2.5 (200M) PyTorch",
"input": {
"source": "NOAA GISTEMP Global Temperature Anomaly",
"n_observations": 36,
"date_range": "2022-01 to 2024-12",
"mean_anomaly_c": 1.09
},
"forecast": {
"horizon": 12,
"dates": [
"2025-01",
"2025-02",
"2025-03",
"2025-04",
"2025-05",
"2025-06",
"2025-07",
"2025-08",
"2025-09",
"2025-10",
"2025-11",
"2025-12"
],
"point": [
1.2223774194717407,
1.2563583850860596,
1.286476969718933,
1.240488052368164,
1.202637791633606,
1.2100199460983276,
1.2253109216690063,
1.2421810626983643,
1.2697349786758423,
1.2496669292449951,
1.2135266065597534,
1.2034140825271606
],
"quantiles": {
"mean": [
1.2215943336486816,
1.25020170211792,
1.281691551208496,
1.240675449371338,
1.1969143152236938,
1.1963895559310913,
1.215125322341919,
1.229291558265686,
1.260316252708435,
1.243621826171875,
1.2031629085540771,
1.186724305152893
],
"10%": [
1.1230627298355103,
1.1482248306274414,
1.1694773435592651,
1.119297981262207,
1.0776878595352173,
1.0811386108398438,
1.0917633771896362,
1.1043028831481934,
1.123927354812622,
1.0962445735931396,
1.054552435874939,
1.0412306785583496
],
"20%": [
1.161399483680725,
1.1891648769378662,
1.2141375541687012,
1.168922781944275,
1.1280149221420288,
1.1352498531341553,
1.1474796533584595,
1.1598811149597168,
1.1872942447662354,
1.1630417108535767,
1.1223580837249756,
1.1113251447677612
],
"30%": [
1.18324875831604,
1.2134028673171997,
1.2430503368377686,
1.195752739906311,
1.1554758548736572,
1.1687461137771606,
1.1764130592346191,
1.1929150819778442,
1.2162872552871704,
1.193880558013916,
1.1572109460830688,
1.1433371305465698
],
"40%": [
1.2030285596847534,
1.2355917692184448,
1.263671875,
1.216238260269165,
1.1801764965057373,
1.1853771209716797,
1.2029412984848022,
1.216418743133545,
1.2429510354995728,
1.2217119932174683,
1.1864622831344604,
1.1752325296401978
],
"50%": [
1.2223774194717407,
1.2563583850860596,
1.286476969718933,
1.240488052368164,
1.202637791633606,
1.2100199460983276,
1.2253109216690063,
1.2421810626983643,
1.2697349786758423,
1.2496669292449951,
1.2135266065597534,
1.2034140825271606
],
"60%": [
1.2409889698028564,
1.2787916660308838,
1.3101407289505005,
1.2653590440750122,
1.2274072170257568,
1.2333428859710693,
1.2509560585021973,
1.266998052597046,
1.2976493835449219,
1.2757387161254883,
1.2447274923324585,
1.2308053970336914
],
"70%": [
1.2626991271972656,
1.3061506748199463,
1.336512565612793,
1.2880773544311523,
1.2546851634979248,
1.2559939622879028,
1.276485562324524,
1.292467474937439,
1.323679804801941,
1.30413818359375,
1.2706527709960938,
1.2621957063674927
],
"80%": [
1.2927711009979248,
1.3358021974563599,
1.372582197189331,
1.3237736225128174,
1.2890899181365967,
1.2938039302825928,
1.3113454580307007,
1.3304922580718994,
1.358002781867981,
1.3376691341400146,
1.3091387748718262,
1.2912495136260986
],
"90%": [
1.3396029472351074,
1.3880282640457153,
1.426570177078247,
1.3806401491165161,
1.3469674587249756,
1.3532465696334839,
1.3728349208831787,
1.394974946975708,
1.425218105316162,
1.409816026687622,
1.380167841911316,
1.3700779676437378
]
}
},
"summary": {
"forecast_mean_c": 1.235,
"forecast_max_c": 1.286,
"forecast_min_c": 1.203,
"vs_last_year_mean": -0.017
}
}
timesfm-forecasting/examples/global-temperature/output/forecast_visualization.png
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timesfm-forecasting/examples/global-temperature/output/interactive_forecast.html
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