diff --git a/docs/conf.py b/docs/conf.py
index cb90b729..387af6b0 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -16,7 +16,7 @@
 import sys
 
 sys.path.insert(0, os.path.abspath("."))
-from pastastore import __version__
+from pastastore import __version__  # noqa: E402
 
 # -- Project information -----------------------------------------------------
 
@@ -125,7 +125,6 @@
 #
 # html_sidebars = {}
 
-
 # -- Options for HTMLHelp output ---------------------------------------------
 
 # Output file base name for HTML help builder.
diff --git a/examples/notebooks/ex02_pastastore_plots_and_maps.ipynb b/examples/notebooks/ex02_pastastore_plots_and_maps.ipynb
index 4c2869ce..71ce3365 100644
--- a/examples/notebooks/ex02_pastastore_plots_and_maps.ipynb
+++ b/examples/notebooks/ex02_pastastore_plots_and_maps.ipynb
@@ -31,10 +31,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sys\n",
-    "import os\n",
-    "\n",
-    "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
     "import pastastore as pst\n",
     "import pastas as ps\n",
diff --git a/examples/notebooks/ex03_pastastore_yaml_interface.ipynb b/examples/notebooks/ex03_pastastore_yaml_interface.ipynb
index 073f445f..20cfd4b5 100644
--- a/examples/notebooks/ex03_pastastore_yaml_interface.ipynb
+++ b/examples/notebooks/ex03_pastastore_yaml_interface.ipynb
@@ -163,7 +163,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pastastore.datasets import example_pastastore"
+    "from pastastore.datasets import example_pastastore  # noqa: E402"
    ]
   },
   {
@@ -364,7 +364,7 @@
    ],
    "source": [
     "ml.solve(report=False)\n",
-    "ml.plots.results();"
+    "ml.plots.results()"
    ]
   },
   {
@@ -802,7 +802,7 @@
    ],
    "source": [
     "ml.solve(report=False)\n",
-    "ml.plots.results();"
+    "ml.plots.results()"
    ]
   },
   {
@@ -910,7 +910,7 @@
    ],
    "source": [
     "ml.solve(report=False)\n",
-    "ml.plots.results();"
+    "ml.plots.results()"
    ]
   },
   {
diff --git a/pastastore/__init__.py b/pastastore/__init__.py
index 1ae7869b..6f258d00 100644
--- a/pastastore/__init__.py
+++ b/pastastore/__init__.py
@@ -1,10 +1,11 @@
-from . import connectors, util
-from .connectors import (
+# ruff: noqa: F401
+from pastastore import connectors, util
+from pastastore.connectors import (
     ArcticConnector,
     ArcticDBConnector,
     DictConnector,
     PasConnector,
     PystoreConnector,
 )
-from .store import PastaStore
-from .version import __version__
+from pastastore.store import PastaStore
+from pastastore.version import __version__
diff --git a/pastastore/base.py b/pastastore/base.py
index ecf5517e..7434e9aa 100644
--- a/pastastore/base.py
+++ b/pastastore/base.py
@@ -11,10 +11,10 @@
 from numpy import isin
 from packaging.version import parse as parse_version
 from pastas.io.pas import PastasEncoder
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
-from .util import ItemInLibraryException, _custom_warning, validate_names
-from .version import PASTAS_LEQ_022
+from pastastore.util import ItemInLibraryException, _custom_warning, validate_names
+from pastastore.version import PASTAS_LEQ_022
 
 FrameorSeriesUnion = Union[pd.DataFrame, pd.Series]
 warnings.showwarning = _custom_warning
@@ -934,13 +934,24 @@ def empty_library(
             )
             if ui.lower() != "y":
                 return
-        names = self._parse_names(None, libname)
-        for name in (
-            tqdm(names, desc=f"Deleting items from {libname}") if progressbar else names
-        ):
-            self._del_item(libname, name)
-        self._clear_cache(libname)
-        print(f"Emptied library {libname} in {self.name}: " f"{self.__class__}")
+
+        if libname == "models":
+            # also delete linked modelnames linked to oseries
+            libs = ["models", "oseries_models"]
+        else:
+            libs = [libname]
+
+        # delete items and clear caches
+        for libname in libs:
+            names = self._parse_names(None, libname)
+            for name in (
+                tqdm(names, desc=f"Deleting items from {libname}")
+                if progressbar
+                else names
+            ):
+                self._del_item(libname, name)
+            self._clear_cache(libname)
+            print(f"Emptied library {libname} in {self.name}: " f"{self.__class__}")
 
     def _iter_series(self, libname: str, names: Optional[List[str]] = None):
         """Internal method iterate over time series in library.
diff --git a/pastastore/connectors.py b/pastastore/connectors.py
index 146f3bb5..465be383 100644
--- a/pastastore/connectors.py
+++ b/pastastore/connectors.py
@@ -8,8 +8,8 @@
 import pandas as pd
 from pastas.io.pas import PastasEncoder, pastas_hook
 
-from .base import BaseConnector, ConnectorUtil, ModelAccessor
-from .util import _custom_warning
+from pastastore.base import BaseConnector, ConnectorUtil, ModelAccessor
+from pastastore.util import _custom_warning
 
 FrameorSeriesUnion = Union[pd.DataFrame, pd.Series]
 warnings.showwarning = _custom_warning
diff --git a/pastastore/plotting.py b/pastastore/plotting.py
index 1f4aa1ae..834f19fe 100644
--- a/pastastore/plotting.py
+++ b/pastastore/plotting.py
@@ -14,9 +14,6 @@
     ax = pstore.maps.oseries()
     pstore.maps.add_background_map(ax)  # for adding a background map
 """
-
-from collections.abc import Iterable
-
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
@@ -96,15 +93,11 @@ def _timeseries(
 
         if ax is None:
             if split:
-                fig, axes = plt.subplots(len(names), 1, sharex=True, figsize=figsize)
+                _, axes = plt.subplots(len(names), 1, sharex=True, figsize=figsize)
             else:
-                fig, axes = plt.subplots(1, 1, figsize=figsize)
+                _, axes = plt.subplots(1, 1, figsize=figsize)
         else:
             axes = ax
-            if isinstance(axes, Iterable):
-                fig = axes[0].figure
-            else:
-                fig = axes.figure
 
         tsdict = self.pstore.conn._get_series(
             libname, names, progressbar=progressbar, squeeze=False
@@ -397,20 +390,31 @@ def _data_availability(
                     linewidth=0,
                     rasterized=True,
                 )
+
         # make a colorbar in an ax on the
         # right side, then set the current axes to ax again
         cb = fig.colorbar(pc, ax=ax, cax=cax, extend="both")
         cb.set_ticks(bounds)
         cb.ax.set_yticklabels(labels)
         cb.ax.minorticks_off()
+
         if set_yticks:
-            ax.set_yticks(np.arange(0.5, len(series) + 0.5))
+            ax.set_yticks(np.arange(0.5, len(series) + 0.5), minor=False)
+            ax.set_yticks(np.arange(0, len(series) + 1), minor=True)
             if names is None:
                 names = [s.name for s in series]
             ax.set_yticklabels(names)
+
+            for tick in ax.yaxis.get_major_ticks():  # don't show major ytick marker
+                tick.tick1line.set_visible(False)
+
+            ax.grid(True, which="minor", axis="y")
+            ax.grid(True, which="major", axis="x")
+
         else:
             ax.set_ylabel("Timeseries (-)")
-        ax.grid(True)
+            ax.grid(True, which="both")
+            ax.grid(True, which="both")
 
         return ax
 
@@ -712,6 +716,7 @@ def models(
     def modelstat(
         self,
         statistic,
+        modelnames=None,
         label=True,
         adjust=False,
         cmap="viridis",
@@ -728,6 +733,8 @@ def modelstat(
         ----------
         statistic: str
             name of the statistic, e.g. "evp" or "aic"
+        modelnames : list of str, optional
+            list of modelnames to include
         label: bool, optional
             label points, by default True
         adjust: bool, optional
@@ -757,7 +764,9 @@ def modelstat(
         --------
         self.add_background_map
         """
-        statsdf = self.pstore.get_statistics([statistic], progressbar=False).to_frame()
+        statsdf = self.pstore.get_statistics(
+            [statistic], modelnames=modelnames, progressbar=False
+        ).to_frame()
 
         statsdf["oseries"] = [
             self.pstore.get_models(m, return_dict=True)["oseries"]["name"]
diff --git a/pastastore/store.py b/pastastore/store.py
index c39fee1a..81c7c3e3 100644
--- a/pastastore/store.py
+++ b/pastastore/store.py
@@ -8,11 +8,13 @@
 import pastas as ps
 from packaging.version import parse as parse_version
 from pastas.io.pas import pastas_hook
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
-from .plotting import Maps, Plots
-from .util import _custom_warning
-from .yaml_interface import PastastoreYAML
+from pastastore.base import BaseConnector
+from pastastore.connectors import DictConnector
+from pastastore.plotting import Maps, Plots
+from pastastore.util import _custom_warning
+from pastastore.yaml_interface import PastastoreYAML
 
 FrameorSeriesUnion = Union[pd.DataFrame, pd.Series]
 warnings.showwarning = _custom_warning
@@ -38,14 +40,19 @@ class PastaStore:
         name of the PastaStore, by default takes the name of the Connector object
     """
 
-    def __init__(self, connector, name: str = None):
+    def __init__(
+        self,
+        connector: Optional[BaseConnector] = None,
+        name: Optional[str] = None,
+    ):
         """Initialize PastaStore for managing pastas time series and models.
 
         Parameters
         ----------
-        connector : Connector object
-            object that provides the interface to the
-            database
+        connector : Connector object, optional
+            object that provides the connection to the database. Default is None, which
+            will create a DictConnector. This default Connector does not store data on
+            disk.
         name : str, optional
             name of the PastaStore, if not provided uses the Connector name
         """
@@ -53,6 +60,8 @@ def __init__(self, connector, name: str = None):
             raise DeprecationWarning(
                 "PastaStore expects the connector as the first argument since v1.1!"
             )
+        if connector is None:
+            connector = DictConnector("pastas_db")
         self.conn = connector
         self.name = name if name is not None else self.conn.name
         self._register_connector_methods()
@@ -300,6 +309,81 @@ def get_nearest_stresses(
             data = pd.concat([data, series], axis=0)
         return data
 
+    def get_signatures(
+        self,
+        signatures=None,
+        names=None,
+        libname="oseries",
+        progressbar=False,
+        ignore_errors=False,
+    ):
+        """Get groundwater signatures. NaN-values are returned when the
+        signature could not be computed.
+
+        Parameters
+        ----------
+        signatures : list of str, optional
+            list of groundwater signatures to compute, if None all groundwater
+            signatures in ps.stats.signatures.__all__ are used, by default None
+        names : str, list of str, or None, optional
+            names of the time series, by default None which
+            uses all the time series in the library
+        libname : str
+            name of the library containing the time series
+            ('oseries' or 'stresses'), by default "oseries"
+        progressbar : bool, optional
+            show progressbar, by default False
+        ignore_errors : bool, optional
+            ignore errors when True, i.e. when non-existent timeseries is
+            encountered in names, by default False
+
+        Returns
+        -------
+        signatures_df : pandas.DataFrame
+            DataFrame containing the signatures (columns) per time series (rows)
+        """
+        names = self.conn._parse_names(names, libname=libname)
+
+        if signatures is None:
+            signatures = ps.stats.signatures.__all__.copy()
+
+        # create dataframe for results
+        signatures_df = pd.DataFrame(index=names, columns=signatures, data=np.nan)
+
+        # loop through oseries names
+        desc = "Get groundwater signatures"
+        for name in tqdm(names, desc=desc) if progressbar else names:
+            try:
+                if libname == "oseries":
+                    s = self.conn.get_oseries(name)
+                else:
+                    s = self.conn.get_stresses(name)
+            except Exception as e:
+                if ignore_errors:
+                    signatures_df.loc[name, :] = np.nan
+                    continue
+                else:
+                    raise e
+
+            try:
+                i_signatures = ps.stats.signatures.summary(s.squeeze(), signatures)
+            except Exception as e:
+                if ignore_errors:
+                    i_signatures = []
+                    for signature in signatures:
+                        try:
+                            sign_val = getattr(ps.stats.signatures, signature)(
+                                s.squeeze()
+                            )
+                        except Exception as _:
+                            sign_val = np.nan
+                        i_signatures.append(sign_val)
+                else:
+                    raise e
+            signatures_df.loc[name, signatures] = i_signatures
+
+        return signatures_df
+
     def get_tmin_tmax(self, libname, names=None, progressbar=False):
         """Get tmin and tmax for time series.
 
@@ -334,6 +418,23 @@ def get_tmin_tmax(self, libname, names=None, progressbar=False):
             tmintmax.loc[n, "tmax"] = s.last_valid_index()
         return tmintmax
 
+    def get_extent(self, libname, names=None, buffer=0.0):
+        names = self.conn._parse_names(names, libname=libname)
+        if libname in ["oseries", "stresses"]:
+            df = getattr(self, libname)
+        elif libname == "models":
+            df = self.oseries
+        else:
+            raise ValueError(f"Cannot get extent for library '{libname}'.")
+
+        extent = [
+            df.loc[names, "x"].min() - buffer,
+            df.loc[names, "x"].max() + buffer,
+            df.loc[names, "y"].min() - buffer,
+            df.loc[names, "y"].max() + buffer,
+        ]
+        return extent
+
     def get_parameters(
         self,
         parameters: Optional[List[str]] = None,
@@ -428,13 +529,13 @@ def get_statistics(
 
         modelnames = self.conn._parse_names(modelnames, libname="models")
 
-        # create dataframe for results
-        s = pd.DataFrame(index=modelnames, columns=statistics, data=np.nan)
-
         # if statistics is str
         if isinstance(statistics, str):
             statistics = [statistics]
 
+        # create dataframe for results
+        s = pd.DataFrame(index=modelnames, columns=statistics, data=np.nan)
+
         # loop through model names
         desc = "Get model statistics"
         for mlname in tqdm(modelnames, desc=desc) if progressbar else modelnames:
@@ -836,7 +937,7 @@ def export_model_series_to_csv(
     def from_zip(
         cls,
         fname: str,
-        conn,
+        conn: Optional[BaseConnector] = None,
         storename: Optional[str] = None,
         progressbar: bool = True,
     ):
@@ -846,8 +947,9 @@ def from_zip(
         ----------
         fname : str
             pathname of zipfile
-        conn : Connector object
-            connector for storing loaded data
+        conn : Connector object, optional
+            connector for storing loaded data, default is None which creates a
+            DictConnector. This Connector does not store data on disk.
         storename : str, optional
             name of the PastaStore, by default None, which
             defaults to the name of the Connector.
@@ -861,6 +963,9 @@ def from_zip(
         """
         from zipfile import ZipFile
 
+        if conn is None:
+            conn = DictConnector("pastas_db")
+
         with ZipFile(fname, "r") as archive:
             namelist = [
                 fi for fi in archive.namelist() if not fi.endswith("_meta.json")
@@ -868,7 +973,7 @@ def from_zip(
             for f in tqdm(namelist, desc="Reading zip") if progressbar else namelist:
                 libname, fjson = os.path.split(f)
                 if libname in ["stresses", "oseries"]:
-                    s = pd.read_json(archive.open(f), orient="columns")
+                    s = pd.read_json(archive.open(f), dtype=float, orient="columns")
                     if not isinstance(s.index, pd.DatetimeIndex):
                         s.index = pd.to_datetime(s.index, unit="ms")
                     s = s.sort_index()
@@ -983,9 +1088,45 @@ def get_model_timeseries_names(
                     structure.loc[mlnam, pnam] = 1
                     structure.loc[mlnam, enam] = 1
                 elif "stress" in sm:
-                    for s in sm["stress"]:
+                    smstress = sm["stress"]
+                    if isinstance(smstress, dict):
+                        smstress = [smstress]
+                    for s in smstress:
                         structure.loc[mlnam, s["name"]] = 1
         if dropna:
             return structure.dropna(how="all", axis=1)
         else:
             return structure
+
+    def apply(self, libname, func, names=None, progressbar=True):
+        """Apply function to items in library.
+
+        Supported libraries are oseries, stresses, and models.
+
+        Parameters
+        ----------
+        libname : str
+            library name, supports "oseries", "stresses" and "models"
+        func : callable
+            function that accepts items from one of the supported libraries as input
+        names : str, list of str, optional
+            apply function to these names, by default None which loops over all stored
+            items in library
+        progressbar : bool, optional
+            show progressbar, by default True
+
+        Returns
+        -------
+        dict
+            dict of results of func, with names as keys and results as values
+        """
+        names = self.conn._parse_names(names, libname)
+        result = {}
+        if libname not in ("oseries", "stresses", "models"):
+            raise ValueError(
+                "'libname' must be one of ['oseries', 'stresses', 'models']!"
+            )
+        getter = getattr(self.conn, f"get_{libname}")
+        for n in tqdm(names) if progressbar else names:
+            result[n] = func(getter(n))
+        return result
diff --git a/pastastore/util.py b/pastastore/util.py
index 70ab042a..313c0396 100644
--- a/pastastore/util.py
+++ b/pastastore/util.py
@@ -6,9 +6,9 @@
 from numpy.lib._iotools import NameValidator
 from pandas.testing import assert_series_equal
 from pastas.stats.tests import runs_test, stoffer_toloi
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
-from .version import PASTAS_LEQ_022
+from pastastore.version import PASTAS_LEQ_022
 
 
 def _custom_warning(message, category=UserWarning, filename="", lineno=-1, *args):
@@ -704,6 +704,8 @@ def frontiers_checks(
                         )
                 else:
                     tmem = ml.get_response_tmax(sm_name)
+                    if tmem is None:  # no rfunc in stressmodel
+                        tmem = 0
                     check_tmem_passed = tmem < len_oseries_calib / 2
                     checks.loc[f"calib_period > 2*t_mem_95%: {sm_name}", :] = (
                         tmem,
@@ -736,23 +738,30 @@ def frontiers_checks(
                             "(unit head)/(unit well stress)",
                             check_gain_passed,
                         )
+                    continue
+                elif sm._name == "LinearTrend":
+                    gain = ml.parameters.loc[f"{sm_name}_a", "optimal"]
+                    gain_std = ml.parameters.loc[f"{sm_name}_a", "stderr"]
+                elif sm._name == "StepModel":
+                    gain = ml.parameters.loc[f"{sm_name}_d", "optimal"]
+                    gain_std = ml.parameters.loc[f"{sm_name}_d", "stderr"]
                 else:
                     gain = ml.parameters.loc[f"{sm_name}_A", "optimal"]
                     gain_std = ml.parameters.loc[f"{sm_name}_A", "stderr"]
-                    if gain_std is None:
-                        gain_std = np.nan
-                        check_gain_passed = pd.NA
-                    elif np.isnan(gain_std):
-                        check_gain_passed = pd.NA
-                    else:
-                        check_gain_passed = np.abs(gain) > 2 * gain_std
+
+                if gain_std is None:
+                    gain_std = np.nan
+                    check_gain_passed = pd.NA
+                elif np.isnan(gain_std):
+                    check_gain_passed = pd.NA
+                else:
                     check_gain_passed = np.abs(gain) > 2 * gain_std
-                    checks.loc[f"gain > 2*std: {sm_name}", :] = (
-                        gain,
-                        2 * gain_std,
-                        "(unit head)/(unit well stress)",
-                        check_gain_passed,
-                    )
+                checks.loc[f"gain > 2*std: {sm_name}", :] = (
+                    gain,
+                    2 * gain_std,
+                    "(unit head)/(unit well stress)",
+                    check_gain_passed,
+                )
 
         # Check 5 - Parameter Bounds
         if check5_parambounds:
diff --git a/pastastore/version.py b/pastastore/version.py
index 3afd6c04..e832ee3f 100644
--- a/pastastore/version.py
+++ b/pastastore/version.py
@@ -4,4 +4,4 @@
 PASTAS_VERSION = parse_version(ps.__version__)
 PASTAS_LEQ_022 = PASTAS_VERSION <= parse_version("0.22.0")
 
-__version__ = "1.2.2"
+__version__ = "1.3.0"
diff --git a/pastastore/yaml_interface.py b/pastastore/yaml_interface.py
index 00a28a13..4d07c352 100644
--- a/pastastore/yaml_interface.py
+++ b/pastastore/yaml_interface.py
@@ -2,14 +2,14 @@
 import logging
 import os
 from copy import deepcopy
-from typing import Dict, List, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
 import numpy as np
 import pandas as pd
 import pastas as ps
 import yaml
 
-from .version import PASTAS_LEQ_022
+from pastastore.version import PASTAS_LEQ_022
 
 ps.logger.setLevel("ERROR")
 
@@ -17,7 +17,7 @@
 logger = logging.getLogger(__name__)
 
 
-def _convert_dict_dtypes_for_yaml(d: Dict):
+def _convert_dict_dtypes_for_yaml(d: Dict[str, Any]):
     """Internal method to convert dictionary values for storing in YAML format.
 
     Parameters
diff --git a/tests/test_001_import.py b/tests/test_001_import.py
index f8d84565..6522e5af 100644
--- a/tests/test_001_import.py
+++ b/tests/test_001_import.py
@@ -4,4 +4,4 @@
 def test_import():
     with warnings.catch_warnings():
         warnings.simplefilter(action="ignore", category=FutureWarning)
-        import pastastore
+        import pastastore  # noqa: F401
diff --git a/tests/test_002_connectors.py b/tests/test_002_connectors.py
index 8989218f..f99d0b5a 100644
--- a/tests/test_002_connectors.py
+++ b/tests/test_002_connectors.py
@@ -14,7 +14,7 @@
 
 
 def test_get_library(conn):
-    olib = conn._get_library("oseries")
+    _ = conn._get_library("oseries")
 
 
 def test_add_get_series(request, conn):
@@ -206,13 +206,13 @@ def test_add_stress(conn):
 @pytest.mark.dependency()
 def test_get_oseries(request, conn):
     depends(request, [f"test_add_oseries[{conn.type}]"])
-    o = conn.get_oseries("oseries1")
+    _ = conn.get_oseries("oseries1")
 
 
 @pytest.mark.dependency()
 def test_get_oseries_and_metadata(request, conn):
     depends(request, [f"test_add_oseries[{conn.type}]"])
-    o, m = conn.get_oseries("oseries1", return_metadata=True)
+    _ = conn.get_oseries("oseries1", return_metadata=True)
 
 
 @pytest.mark.dependency()
@@ -225,7 +225,7 @@ def test_get_stress(request, conn):
 @pytest.mark.dependency()
 def test_get_stress_and_metadata(request, conn):
     depends(request, [f"test_add_stress[{conn.type}]"])
-    s, m = conn.get_stresses("prec", return_metadata=True)
+    s, _ = conn.get_stresses("prec", return_metadata=True)
     s.name = "prec"
 
 
diff --git a/tests/test_003_pastastore.py b/tests/test_003_pastastore.py
index a7d398b6..29feae3e 100644
--- a/tests/test_003_pastastore.py
+++ b/tests/test_003_pastastore.py
@@ -39,7 +39,7 @@ def test_search(pstore):
 
 @pytest.mark.dependency()
 def test_create_model(pstore):
-    ml = pstore.create_model("oseries1")
+    _ = pstore.create_model("oseries1")
 
 
 @pytest.mark.dependency()
@@ -139,7 +139,7 @@ def test_get_model(request, pstore):
             f"test_store_model_missing_series[{pstore.type}]",
         ],
     )
-    ml = pstore.conn.get_models("oseries1")
+    _ = pstore.conn.get_models("oseries1")
 
 
 @pytest.mark.dependency()
@@ -158,7 +158,7 @@ def test_del_model(request, pstore):
 
 @pytest.mark.dependency()
 def test_create_models(pstore):
-    mls = pstore.create_models_bulk(
+    _ = pstore.create_models_bulk(
         ["oseries1", "oseries2"], store=True, progressbar=False
     )
     _ = pstore.conn.models
@@ -172,6 +172,13 @@ def test_get_parameters(request, pstore):
     assert p.isna().sum().sum() == 0
 
 
+@pytest.mark.dependency()
+def test_get_signatures(request, pstore):
+    depends(request, [f"test_create_models[{pstore.type}]"])
+    s = pstore.get_signatures(progressbar=False)
+    assert s.shape[1] == len(ps.stats.signatures.__all__)
+
+
 @pytest.mark.dependency()
 def test_iter_models(request, pstore):
     depends(request, [f"test_create_models[{pstore.type}]"])
@@ -181,13 +188,24 @@ def test_iter_models(request, pstore):
 @pytest.mark.dependency()
 def test_solve_models_and_get_stats(request, pstore):
     depends(request, [f"test_create_models[{pstore.type}]"])
-    mls = pstore.solve_models(
+    _ = pstore.solve_models(
         ignore_solve_errors=False, progressbar=False, store_result=True
     )
     stats = pstore.get_statistics(["evp", "aic"], progressbar=False)
     assert stats.index.size == 2
 
 
+@pytest.mark.dependency()
+def test_apply(request, pstore):
+    depends(request, [f"test_solve_models_and_get_stats[{pstore.type}]"])
+
+    def func(ml):
+        return ml.parameters.loc["recharge_A", "optimal"]
+
+    result = pstore.apply("models", func)
+    assert len(result) == 2
+
+
 @pytest.mark.dependency()
 def test_save_and_load_model(request, pstore):
     ml = pstore.create_model("oseries2")
diff --git a/tests/test_004_yaml.py b/tests/test_004_yaml.py
index c2799127..fb165c0a 100644
--- a/tests/test_004_yaml.py
+++ b/tests/test_004_yaml.py
@@ -6,7 +6,6 @@
 from pytest_dependency import depends
 
 import pastastore as pst
-from pastastore.version import PASTAS_LEQ_022
 
 
 @contextmanager