diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/core/processes/base.py b/core/processes/base.py
index 9dadb0470eab4de33f56538e9008382496415fda..142bd6c3fa2c5ef0fc578d3d09bfa47530482619 100644
--- a/core/processes/base.py
+++ b/core/processes/base.py
@@ -1,54 +1 @@
-from pathlib import Path, PosixPath
-from typing import Union
-from abc import ABC, abstractmethod
-
-from yaml import safe_load, dump
-
-
-class ParametersABC(ABC):
- """
- Base class to add yaml functionality to parameters
-
- """
-
- def to_dict(self):
- return self.__dict__
-
- @classmethod
- def from_dict(cls, d: dict):
- return cls(**d)
-
- def to_yaml(self, path: Union[PosixPath, str] = None):
- if path:
- with open(Path(path), "w") as f:
- dump(self.to_dict(), f)
- return dump(self.to_dict())
-
- @classmethod
- def from_yaml(cls, path: Union[PosixPath, str]):
- with open(Path(file)) as f:
- params = safe_load(f)
- return cls(**params)
-
- @classmethod
- @abstractmethod
- def default(cls):
- pass
-
-
-class ProcessABC(ABC):
- "Base class for processes"
-
- def __init__(self, parameters):
- self._parameters = parameters
-
- for k, v in parameters.to_dict().items(): # access parameters directly
- setattr(self, k, v)
-
- @property
- def parameters(self):
- return self._parameters
-
- @abstractmethod
- def run(self):
- pass
+from agora.base import ParametersABC, ProcessABC
\ No newline at end of file
diff --git a/core/processes/dsignal.py b/core/processes/dsignal.py
index c596075721934a2517c4a20c648deabce8db1453..484ad59944c12cd12005c02b9470b84d8f2f19d7 100644
--- a/core/processes/dsignal.py
+++ b/core/processes/dsignal.py
@@ -1,7 +1,6 @@
import pandas as pd
from postprocessor.core.processes.base import ParametersABC, ProcessABC
-from postprocessor.core.functions.tracks import clean_tracks, merge_tracks, join_tracks
class dsignalParameters(ParametersABC):
diff --git a/core/processes/gpsignal.py b/core/processes/gpsignal.py
new file mode 100644
index 0000000000000000000000000000000000000000..f6cdb45fbd1416630382246fb3152c9d99184076
--- /dev/null
+++ b/core/processes/gpsignal.py
@@ -0,0 +1,97 @@
+"""Gaussian process fit of a Signal."""
+import logging
+
+from postprocessor.core.processes.base import ParametersABC, ProcessABC
+import numpy as np
+import pandas as pd
+
+import gaussian_processes.gaussianprocess as gp
+
+def estimate_gr(volume, dt, noruns, bounds, verbose):
+ """
+ Parameters
+ ----------
+
+ volume : pd.Series
+ The volume series of a given cell
+ dt : float
+ The time interval in hours
+ noruns : int
+ The number of runs for optimisation
+ bounds : dict
+ The hyperparameter bounds used for optimisation
+ verbose : bool
+ If True, prints results
+
+ Returns
+ -------
+ """
+ volume = volume.values
+ n = len(volume)
+ idx = np.arange(n)
+ t = idx * dt
+ y = volume[volume > 0]
+ x = t[volume > 0]
+ idx = idx[volume > 0]
+ # Fit the GP
+ mg = gp.maternGP(bounds, x, y)
+ mg.findhyperparameters(noruns=noruns)
+ if verbose:
+ mg.results() # Prints out the hyperparameters
+ mg.predict(x, derivs=2) # Saves the predictions to object
+ # Save the predictions to a csv file so they can be reused
+ results = dict(time=mg.x, volume=mg.y, fit_time=mg.xnew, fit_volume=mg.f,
+ growth_rate=mg.df, d_growth_rate=mg.ddf,
+ volume_var=mg.fvar, growth_rate_var=mg.dfvar,
+ d_growth_rate_var=mg.ddfvar)
+ for name, value in results.items():
+ results[name] = np.full((n, ), np.nan)
+ results[name][idx] = value
+ return results
+
+# Give that to a writer: NOTE the writer needs to learn how to write the
+# output of a process that returns multiple signals like this one does.
+
+class gpParameters(ParametersABC):
+ default_dict = dict(dt=5,
+ noruns=5,
+ bounds={0: (-2, 3),
+ 1: (-2, 1),
+ 2: (-4, -1)},
+ verbose=False)
+ def __init__(self, dt, noruns, bounds, verbose):
+ """
+ Parameters
+ ----------
+ dt : float
+ The time step between time points, in minutes
+ noruns : int
+ The number of times the optimisation is tried
+ bounds : dict
+ Hyperparameter bounds for the Matern Kernel
+ verbose : bool
+ Determines whether to print hyperparameter results
+ """
+ self.dt = dt
+ self.noruns = noruns
+ self.bounds = bounds
+ self.verbose = verbose
+
+ @classmethod
+ def default(cls):
+ return cls.from_dict(cls.default_dict)
+
+
+class GPSignal(ProcessABC):
+ """Gaussian process fit of a Signal.
+ """
+ def __init__(self, parameters: gpParameters):
+ super().__init__(parameters)
+
+ def run(self, signal: pd.DataFrame):
+ results = signal.apply(lambda x: estimate_gr(x,
+ **self.parameters.to_dict()),
+ result_type='expand').T
+ multi_signal = {name: pd.DataFrame(np.vstack(results[name]))
+ for name in results.columns}
+ return multi_signal
diff --git a/core/processes/merger.py b/core/processes/merger.py
index 1fa07b9191f7d2e0b2370c54b0364581b00b8de4..f7e90a5cb0b2fe50be7542c642ebd986d8f63152 100644
--- a/core/processes/merger.py
+++ b/core/processes/merger.py
@@ -1,4 +1,4 @@
-from postprocessor.core.processes.base import ParametersABC, ProcessABC
+from agora.base import ParametersABC, ProcessABC
from postprocessor.core.functions.tracks import get_joinable
diff --git a/core/processes/picker.py b/core/processes/picker.py
index 2c057df93afd40a1a109f2866191e8d2c0451a02..3668e92291d9889cd7def4a04d8302c2296bfa98 100644
--- a/core/processes/picker.py
+++ b/core/processes/picker.py
@@ -6,7 +6,7 @@ import pandas as pd
from core.cells import CellsHDF
-from postprocessor.core.processes.base import ParametersABC, ProcessABC
+from agora.base import ParametersABC, ProcessABC
from postprocessor.core.functions.tracks import max_ntps, max_nonstop_ntps
@@ -106,7 +106,7 @@ class picker(ProcessABC):
):
threshold_asint = _as_int(threshold, signals.shape[1])
case_mgr = {
- "present": signals.apply(max_ntps, axis=1) > threshold_asint,
+ "present": signals.notna().sum(axis=1) > threshold_asint,
"nonstoply_present": signals.apply(max_nonstop_ntps, axis=1)
> threshold_asint,
"quantile": [np.quantile(signals.values[signals.notna()], threshold)],
diff --git a/core/processor.py b/core/processor.py
index e5eb499525991fcb7d8aed774a08472400e37176..239edd99314d004c5f4301060c2ce074a0f67936 100644
--- a/core/processor.py
+++ b/core/processor.py
@@ -5,13 +5,13 @@ from pydoc import locate
import numpy as np
import pandas as pd
-from postprocessor.core.processes.base import ParametersABC
-from postprocessor.core.processes.merger import mergerParameters, merger
-from postprocessor.core.processes.picker import pickerParameters, picker
+from agora.base import ParametersABC
from core.io.writer import Writer
from core.io.signal import Signal
from core.cells import Cells
+from postprocessor.core.processes.merger import mergerParameters, merger
+from postprocessor.core.processes.picker import pickerParameters, picker
class PostProcessorParameters(ParametersABC):
@@ -165,9 +165,17 @@ class PostProcessor:
else:
raise ("Outpath not defined", type(dataset))
- self.write_result(
- "/postprocessing/" + process + "/" + outpath, result, metadata={}
- )
+ if isinstance(result, dict): # Multiple Signals as output
+ for k, v in result:
+ self.write_result(
+ "/postprocessing/" + process + "/" + outpath +
+ f'/{k}',
+ v, metadata={}
+ )
+ else:
+ self.write_result(
+ "/postprocessing/" + process + "/" + outpath, result, metadata={}
+ )
def write_result(
self, path: str, result: Union[List, pd.DataFrame, np.ndarray], metadata: Dict