From 5cd939d1c6c3eeb82ede3e9c53bb14f413f1be3a Mon Sep 17 00:00:00 2001
From: Rui Ribeiro <rui.ribeiro@icloud.com>
Date: Wed, 9 Nov 2022 13:19:31 +0100
Subject: [PATCH] release
---
.gitignore | 2 ++
SSBtoolkit-Tutorial2-EBRAINS.ipynb | 29 ------------------
SSBtoolkit-Tutorial3A-EBRAINS.ipynb | 29 ------------------
SSBtoolkit-Tutorial3B-tauRAMD-EBRAINS.ipynb | 29 ------------------
SSBtoolkit-Tutorial4-OXTR-EBRAINS.ipynb | 29 ------------------
.../pathways/__pycache__/Gs.cpython-39.pyc | Bin 8888 -> 8410 bytes
src/lib/ssbtoolkit.py | 12 ++++++--
7 files changed, 11 insertions(+), 119 deletions(-)
diff --git a/.gitignore b/.gitignore
index 73346d4..075c900 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,8 +1,10 @@
SSBtoolkit-Tutorial1-DEV.ipynb
SSBtoolkit-Tutorial2-DEV.ipynb
+SSBtoolkit-Tutorial3A-DEV.ipynb
SSBtoolkit-Tutorial4-OXTR-DEV.ipynb
src/lib/__pycache__/
src/lib/autogrid_reference_files/
src/lib/autogrids/
+src/lib/ssbtoolkit_BK.py
.ipynb_checkpoints/
debugging.txt
diff --git a/SSBtoolkit-Tutorial2-EBRAINS.ipynb b/SSBtoolkit-Tutorial2-EBRAINS.ipynb
index c16479c..b7a2aae 100644
--- a/SSBtoolkit-Tutorial2-EBRAINS.ipynb
+++ b/SSBtoolkit-Tutorial2-EBRAINS.ipynb
@@ -441,35 +441,6 @@
"💡 The potency predicted values can be exported as a python dictionary using the function `sim.PotencyToDict()` or saved in a csv file: `sim.PotencyToCSV()`. "
]
},
- {
- "cell_type": "markdown",
- "id": "7650013b",
- "metadata": {},
- "source": [
- "## Save results on Google Drive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "2d5ed71a",
- "metadata": {},
- "outputs": [],
- "source": [
- "from google.colab import drive\n",
- "drive.mount('/gdrive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "16081378",
- "metadata": {},
- "outputs": [],
- "source": [
- "sim.PotencyToCSV(path='/gdrive/MyDrive/XX') ## change XX accordingly. "
- ]
- },
{
"cell_type": "markdown",
"id": "f2f97975",
diff --git a/SSBtoolkit-Tutorial3A-EBRAINS.ipynb b/SSBtoolkit-Tutorial3A-EBRAINS.ipynb
index c120758..656fe15 100644
--- a/SSBtoolkit-Tutorial3A-EBRAINS.ipynb
+++ b/SSBtoolkit-Tutorial3A-EBRAINS.ipynb
@@ -384,35 +384,6 @@
"💡 The potency predicted values can be exported as a python dictionary using the function `sim.PotencyToDict()` or saved in a csv file: `sim.PotencyToCSV()`. "
]
},
- {
- "cell_type": "markdown",
- "id": "fe6271ed",
- "metadata": {},
- "source": [
- "## Save results on Google Drive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c5f82273",
- "metadata": {},
- "outputs": [],
- "source": [
- "from google.colab import drive\n",
- "drive.mount('/gdrive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "bd888ea5",
- "metadata": {},
- "outputs": [],
- "source": [
- "sim.PotencyToCSV(path='/gdrive/MyDrive/XX') ## change XX accordingly."
- ]
- },
{
"cell_type": "markdown",
"id": "a7c9bbc4",
diff --git a/SSBtoolkit-Tutorial3B-tauRAMD-EBRAINS.ipynb b/SSBtoolkit-Tutorial3B-tauRAMD-EBRAINS.ipynb
index 4a8b8f2..9953102 100644
--- a/SSBtoolkit-Tutorial3B-tauRAMD-EBRAINS.ipynb
+++ b/SSBtoolkit-Tutorial3B-tauRAMD-EBRAINS.ipynb
@@ -458,35 +458,6 @@
"💡 The potency predicted values can be exported as a python dictionary using the function `sim.PotencyToDict()` or saved in a csv file: `sim.PotencyToCSV()`. "
]
},
- {
- "cell_type": "markdown",
- "id": "e9e16ef7",
- "metadata": {},
- "source": [
- "## Save results on Google Drive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "d3ace9c6",
- "metadata": {},
- "outputs": [],
- "source": [
- "from google.colab import drive\n",
- "drive.mount('/gdrive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "2df68659",
- "metadata": {},
- "outputs": [],
- "source": [
- "sim.PotencyToCSV(path='/gdrive/MyDrive/XX') ## change XX accordingly."
- ]
- },
{
"cell_type": "markdown",
"id": "65febe37",
diff --git a/SSBtoolkit-Tutorial4-OXTR-EBRAINS.ipynb b/SSBtoolkit-Tutorial4-OXTR-EBRAINS.ipynb
index 6ace35f..0ed02cb 100644
--- a/SSBtoolkit-Tutorial4-OXTR-EBRAINS.ipynb
+++ b/SSBtoolkit-Tutorial4-OXTR-EBRAINS.ipynb
@@ -285,35 +285,6 @@
"sim.plotCurves()"
]
},
- {
- "cell_type": "markdown",
- "id": "5fd46fe3",
- "metadata": {},
- "source": [
- "## Save results on Google Drive"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "3e476cad",
- "metadata": {},
- "outputs": [],
- "source": [
- "from google.colab import drive\n",
- "drive.mount('/gdrive')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "b98afd3b",
- "metadata": {},
- "outputs": [],
- "source": [
- "sim.plotCurves(save=True, filename='/gdrive/MyDrive/XX') ## change XX accordingly. "
- ]
- },
{
"cell_type": "markdown",
"id": "ff3d7f41",
diff --git a/src/lib/pathways/__pycache__/Gs.cpython-39.pyc b/src/lib/pathways/__pycache__/Gs.cpython-39.pyc
index f2526a339a1f76d36c791c488a40bd6551e3282a..e02e32e3bab2e6b49e52d2b05a528f23cf2d6d92 100644
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diff --git a/src/lib/ssbtoolkit.py b/src/lib/ssbtoolkit.py
index 7b20da1..23b9aa8 100644
--- a/src/lib/ssbtoolkit.py
+++ b/src/lib/ssbtoolkit.py
@@ -648,9 +648,9 @@ class simulation:
except:
self._PathwayParameters = self._DefaultPathwayParametersDataFrame.set_index('Parameter').iloc[:,0].to_dict()
- elif self._DefaultPathwayParametersDataFrame.empty and self._binding_kinetic_parameters is not None:
- self._DefaultPathwayParametersDataFrame = pd.read_csv('src/lib/pathways/{}_parameters.csv'.format(self._pathway))
- self._PathwayParameters = {**self._DefaultPathwayParametersDataFrame.set_index('Parameter').iloc[:,0].to_dict(), **self._binding_kinetic_parameters}
+ #elif self._DefaultPathwayParametersDataFrame.empty and self._binding_kinetic_parameters is not None:
+ # self._DefaultPathwayParametersDataFrame = pd.read_csv('src/lib/pathways/{}_parameters.csv'.format(self._pathway))
+ #self._PathwayParameters = {**self._DefaultPathwayParametersDataFrame.set_index('Parameter').iloc[:,0].to_dict(), **self._binding_kinetic_parameters}
elif self._DefaultPathwayParametersDataFrame.empty is False and self._binding_kinetic_parameters is not None:
try:
@@ -673,6 +673,12 @@ class simulation:
data=[]
utils.printProgressBar(0, len(self._lig_conc_range), prefix = "{:<15}".format(ligand_name[:15]), suffix = 'Complete', length = 50)
+ ###DANGER ZONE###
+ if self._DefaultPathwayParametersDataFrame.empty and self._binding_kinetic_parameters is not None:
+ self._DefaultPathwayParametersDataFrame = pd.read_csv('src/lib/pathways/{}_parameters.csv'.format(self._pathway))
+ self._PathwayParameters = {**self._DefaultPathwayParametersDataFrame.set_index('Parameter').iloc[:,0].to_dict(), **self._binding_kinetic_parameters[self._ligands.index(ligand)]}
+ ######################
+
for idx in range(len(self._lig_conc_range)):
ligand_conc = self._lig_conc_range[idx]
--
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