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Level domain protection #169

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merged 4 commits into from
Jan 23, 2023
Merged

Level domain protection #169

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92e0f03
Added mypy/flake8 installation to CONTRIBUTING instructions
kdgutier Jan 23, 2023
174541d
Added level (0,100] domain protection
kdgutier Jan 23, 2023
afb8ecd
Merge branch 'main' of ssh://github.com/Nixtla/hierarchicalforecast i…
kdgutier Jan 23, 2023
58eba71
Fixed domain protection from (0,100] -> [0,100)
kdgutier Jan 23, 2023
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10 changes: 5 additions & 5 deletions hierarchicalforecast/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,7 @@ def _reverse_engineer_sigmah(Y_hat_df, y_hat, model_name):
pi_col = pi_model_name[0]
sign = -1 if 'lo' in pi_col else 1
level_col = re.findall('[\d]+[.,\d]+|[\d]*[.][\d]+|[\d]+', pi_col)
level_col = float(level_col[0])
level_col = float(level_col[-1])
z = norm.ppf(0.5 + level_col / 200)
sigmah = Y_hat_df[pi_col].values.reshape(n_series,-1)
sigmah = sign * (sigmah - y_hat) / z
Expand Down Expand Up @@ -127,9 +127,9 @@ def _prepare_fit(self,

# Protect level list
if (level is not None):
level_outside_domain = np.any((np.array(level) <= 0)|(np.array(level) > 100 ))
level_outside_domain = np.any((np.array(level) < 0)|(np.array(level) >= 100 ))
if level_outside_domain and (intervals_method in ['normality', 'permbu']):
raise Exception('Level outside domain, send `level` list in (0,100]')
raise Exception('Level outside domain, send `level` list in [0,100)')

# Declare output names
drop_cols = ['ds', 'y'] if 'y' in Y_hat_df.columns else ['ds']
Expand Down Expand Up @@ -193,7 +193,7 @@ def reconcile(self,
If a class of `self.reconciles` receives `y_hat_insample`, `Y_df` must include them as columns.<br>
`S`: pd.DataFrame with summing matrix of size `(base, bottom)`, see [aggregate method](https://nixtla.github.io/hierarchicalforecast/utils.html#aggregate).<br>
`tags`: Each key is a level and its value contains tags associated to that level.<br>
`level`: positive float list (0-100], confidence levels for prediction intervals.<br>
`level`: positive float list [0,100), confidence levels for prediction intervals.<br>
`intervals_method`: str, method used to calculate prediction intervals, one of `normality`, `bootstrap`, `permbu`.<br>
`num_samples`: int=-1, if positive return that many probabilistic coherent samples.
`seed`: int=0, random seed for numpy generator's replicability.<br>
Expand Down Expand Up @@ -316,7 +316,7 @@ def bootstrap_reconcile(self,
If a class of `self.reconciles` receives `y_hat_insample`, `Y_df` must include them as columns.<br>
`S`: pd.DataFrame with summing matrix of size `(base, bottom)`, see [aggregate method](https://nixtla.github.io/hierarchicalforecast/utils.html#aggregate).<br>
`tags`: Each key is a level and its value contains tags associated to that level.<br>
`level`: float list 0-100, confidence levels for prediction intervals.<br>
`level`: positive float list [0,100), confidence levels for prediction intervals.<br>
`intervals_method`: str, method used to calculate prediction intervals, one of `normality`, `bootstrap`, `permbu`.<br>
`num_samples`: int=-1, if positive return that many probabilistic coherent samples.
`num_seeds`: int=1, random seed for numpy generator's replicability.<br>
Expand Down
12 changes: 6 additions & 6 deletions nbs/core.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@
" pi_col = pi_model_name[0]\n",
" sign = -1 if 'lo' in pi_col else 1\n",
" level_col = re.findall('[\\d]+[.,\\d]+|[\\d]*[.][\\d]+|[\\d]+', pi_col)\n",
" level_col = float(level_col[0])\n",
" level_col = float(level_col[-1])\n",
" z = norm.ppf(0.5 + level_col / 200)\n",
" sigmah = Y_hat_df[pi_col].values.reshape(n_series,-1)\n",
" sigmah = sign * (sigmah - y_hat) / z\n",
Expand Down Expand Up @@ -227,9 +227,9 @@
" \n",
" # Protect level list\n",
" if (level is not None):\n",
" level_outside_domain = np.any((np.array(level) <= 0)|(np.array(level) > 100 ))\n",
" level_outside_domain = np.any((np.array(level) < 0)|(np.array(level) >= 100 ))\n",
" if level_outside_domain and (intervals_method in ['normality', 'permbu']):\n",
" raise Exception('Level outside domain, send `level` list in (0,100]')\n",
" raise Exception('Level outside domain, send `level` list in [0,100)')\n",
"\n",
" # Declare output names\n",
" drop_cols = ['ds', 'y'] if 'y' in Y_hat_df.columns else ['ds']\n",
Expand Down Expand Up @@ -293,7 +293,7 @@
" If a class of `self.reconciles` receives `y_hat_insample`, `Y_df` must include them as columns.<br>\n",
" `S`: pd.DataFrame with summing matrix of size `(base, bottom)`, see [aggregate method](https://nixtla.github.io/hierarchicalforecast/utils.html#aggregate).<br>\n",
" `tags`: Each key is a level and its value contains tags associated to that level.<br>\n",
" `level`: positive float list (0-100], confidence levels for prediction intervals.<br>\n",
" `level`: positive float list [0,100), confidence levels for prediction intervals.<br>\n",
" `intervals_method`: str, method used to calculate prediction intervals, one of `normality`, `bootstrap`, `permbu`.<br>\n",
" `num_samples`: int=-1, if positive return that many probabilistic coherent samples.\n",
" `seed`: int=0, random seed for numpy generator's replicability.<br>\n",
Expand Down Expand Up @@ -416,7 +416,7 @@
" If a class of `self.reconciles` receives `y_hat_insample`, `Y_df` must include them as columns.<br>\n",
" `S`: pd.DataFrame with summing matrix of size `(base, bottom)`, see [aggregate method](https://nixtla.github.io/hierarchicalforecast/utils.html#aggregate).<br>\n",
" `tags`: Each key is a level and its value contains tags associated to that level.<br>\n",
" `level`: float list 0-100, confidence levels for prediction intervals.<br>\n",
" `level`: positive float list [0,100), confidence levels for prediction intervals.<br>\n",
" `intervals_method`: str, method used to calculate prediction intervals, one of `normality`, `bootstrap`, `permbu`.<br>\n",
" `num_samples`: int=-1, if positive return that many probabilistic coherent samples.\n",
" `num_seeds`: int=1, random seed for numpy generator's replicability.<br>\n",
Expand Down Expand Up @@ -930,7 +930,7 @@
"test_fail(\n",
" hrec.reconcile,\n",
" contains='Level outside domain',\n",
" args=(hier_grouped_hat_df, S_grouped_df, tags_grouped, hier_grouped_df, [0, 80, 90], 'permbu',)\n",
" args=(hier_grouped_hat_df, S_grouped_df, tags_grouped, hier_grouped_df, [-1, 80, 90], 'permbu',)\n",
")\n",
"test_fail(\n",
" hrec.reconcile,\n",
Expand Down