From 27f58b18dce9d2e767ef6474da55f08871a43da7 Mon Sep 17 00:00:00 2001
From: Peter Swain <peter.swain@ed.ac.uk>
Date: Sat, 18 Feb 2023 18:16:03 +0000
Subject: [PATCH] reorganised, with provisional functions in limbo
---
dataloader.py | 30 +++----
figs2pdf.py | 12 +++
growth_rate.py | 87 +++++++++++++++----
entropy.py => limbo/entropy.py | 0
.../find_cytokinesis.py | 0
.../find_cytokinesis_diane.py | 0
search_OMERO.py => limbo/search_OMERO.py | 0
tsa_inprogress.py => limbo/tsa_inprogress.py | 0
plotting.py | 33 +++----
run_gr.py | 49 -----------
10 files changed, 112 insertions(+), 99 deletions(-)
create mode 100644 figs2pdf.py
rename entropy.py => limbo/entropy.py (100%)
rename find_cytokinesis.py => limbo/find_cytokinesis.py (100%)
rename find_cytokinesis_diane.py => limbo/find_cytokinesis_diane.py (100%)
rename search_OMERO.py => limbo/search_OMERO.py (100%)
rename tsa_inprogress.py => limbo/tsa_inprogress.py (100%)
delete mode 100644 run_gr.py
diff --git a/dataloader.py b/dataloader.py
index 7127279..4f2d320 100644
--- a/dataloader.py
+++ b/dataloader.py
@@ -6,13 +6,7 @@ import pprint
try:
from postprocessor.grouper import NameGrouper
except ModuleNotFoundError:
- try:
- import sys
-
- sys.path.append("/Users/pswain/wip/aliby/src")
- from postprocessor.grouper import NameGrouper
- except ModuleNotFoundError:
- print("Can only load tsv files - cannot find postprocessor")
+ print("Can only load tsv files - cannot find postprocessor")
class dataloader:
@@ -70,7 +64,7 @@ class dataloader:
kind="line", data=dl.df)
"""
- def __init__(self, indir=".", outdir=".", ls=True):
+ def __init__(self, indir=None, outdir=".", ls=True):
# from grouper.siglist to abbrevations
self.g2a_dict = {
"extraction/GFP/max/median": "median_GFP",
@@ -87,7 +81,10 @@ class dataloader:
self.a2g_dict = {v: k for (k, v) in self.g2a_dict.items()}
# establish paths
self.outdirpath = Path(outdir)
- self.indirpath = Path(indir)
+ if indir is None:
+ self.indirpath = None
+ else:
+ self.indirpath = Path(indir)
if ls:
self.ls
@@ -104,13 +101,14 @@ class dataloader:
.datasets dictionary.
"""
pp = pprint.PrettyPrinter()
- # find raw data
- print("\nData directory is", str(self.indirpath.resolve()))
- print("Experiments available:")
- dirs = [f.name for f in self.indirpath.glob("*") if f.is_dir()]
- # directories of data are stored in experiments
- self.experiments = {i: name for i, name in enumerate(dirs)}
- pp.pprint(self.experiments)
+ if self.indirpath is not None:
+ # find h5 data
+ print("\nData directory is", str(self.indirpath.resolve()))
+ print("Experiments available:")
+ dirs = [f.name for f in self.indirpath.glob("*") if f.is_dir()]
+ # directories of data are stored in experiments
+ self.experiments = {i: name for i, name in enumerate(dirs)}
+ pp.pprint(self.experiments)
# find processed data
print("\nWorking directory is", str(self.outdirpath.resolve()))
print("Datasets available:")
diff --git a/figs2pdf.py b/figs2pdf.py
new file mode 100644
index 0000000..fa269ed
--- /dev/null
+++ b/figs2pdf.py
@@ -0,0 +1,12 @@
+from matplotlib.backends.backend_pdf import PdfPages
+import matplotlib.pyplot as plt
+
+
+def figs2pdf(savename):
+ """Save all open figures to a pdf file."""
+ if "." not in savename:
+ savename += ".pdf"
+ with PdfPages(savename) as pp:
+ for i in plt.get_fignums():
+ plt.figure(i)
+ pp.savefig()
diff --git a/growth_rate.py b/growth_rate.py
index cae9ee1..d3dd568 100644
--- a/growth_rate.py
+++ b/growth_rate.py
@@ -6,6 +6,71 @@ import numpy as np
import pandas as pd
import gaussianprocessderivatives as gp
+from dataloader import dataloader
+from figs2pdf import figs2pdf
+
+
+def find_all_grs(
+ dataname,
+ max_no_cells=None,
+ indir=None,
+ outdir=".",
+ use_tsv=True,
+):
+ """
+ Find mother and bud growth rates.
+
+ Parameters
+ ----------
+ dataname: str
+ Name of experiment, passed to dataloader.
+ max_no_cells: None or int
+ The maximum number of cells to process.
+ indir: str (optional)
+ The directory containing the h5 files.
+ outdir: str (optional)
+ The directory containing any tsv files to load and where tsv
+ files will be saved.
+ use_tsv: boolean (optional)
+ If True, load initial data from a tsv file.
+
+ Example
+ -------
+ >>> find_all_grs("Pdr5", max_no_cells=2, outdir="tsv_files")
+ """
+ # only save if all cells are processed
+ if max_no_cells is None:
+ save = True
+ else:
+ save = False
+ # get data
+ dl = dataloader(indir=indir, outdir=outdir)
+ dl.load(dataname, use_tsv=use_tsv)
+ b_vol = dl.wide_df("bud_volume")
+ m_vol = dl.wide_df("volume")
+ buddings = dl.wide_df("buddings")
+ # find bud growth rate
+ res_b = find_gr(
+ b_vol,
+ buddings,
+ max_no_cells=max_no_cells,
+ bounds={0: (0, 8)},
+ )
+ if save:
+ pickle.dump(res_b, open(dataname + "_res_b.pkl", "wb"))
+ figs2pdf(dataname + "_b.pdf")
+ plt.close("all")
+ # find mother growth rate
+ res_m = find_gr(m_vol, max_no_cells=max_no_cells)
+ if save:
+ pickle.dump(res_m, open(dataname + "_res_m.pkl", "wb"))
+ figs2pdf(dataname + "_m.pdf")
+ plt.close("all")
+ # add to dataframe and save
+ if save:
+ addgrfrompkl(dl, ".")
+ dl.save(dataname)
+
def find_gr(
volume_df,
@@ -15,9 +80,7 @@ def find_gr(
verbose=True,
max_no_cells=None,
):
- """
- Use a Gaussian process to estimate the single-cell growth rates.
- """
+ """Use a Gaussian process to find single-cell growth rates."""
# default bounds on hyperparameters
# Julian_bounds = {0: (-2, 3), 1: (-2, 0), 2: (0, 3)}
if buddings_df is None:
@@ -112,12 +175,10 @@ def find_gr(
return res_df
-###
-
-
def runGP(x, y, bounds, noruns, signals, verbose, title, maxnofigs=70):
"""
Run GP on a single time series.
+
Results returned as a dictionary.
"""
# drop NaNs
@@ -164,12 +225,10 @@ def runGP(x, y, bounds, noruns, signals, verbose, title, maxnofigs=70):
return res
-###
-
-
def reNaN(oldlist, i_nan):
"""
Add back NaN dropped from an array.
+
Takes a list of arrays and puts back NaN for each array
at indices i_nan.
"""
@@ -184,13 +243,11 @@ def reNaN(oldlist, i_nan):
return oldlist
-###
-
-
def addgrfrompkl(dl, pkldir):
"""
- Load growth rate from pickle files and add to and save dataframe
- in a dataloader instance.
+ Load growth rate from pickle files.
+
+ Add to and save dataframe in a dataloader instance.
Arguments
---------
@@ -207,5 +264,5 @@ def addgrfrompkl(dl, pkldir):
# add to dataframe
for res in [res_b, res_m]:
for signal in res:
- tdf = dl._long_df(res[signal], signal)
+ tdf = dataloader.long_df(res[signal], signal)
dl.df = pd.merge(dl.df, tdf, on=["id", "time"], how="left")
diff --git a/entropy.py b/limbo/entropy.py
similarity index 100%
rename from entropy.py
rename to limbo/entropy.py
diff --git a/find_cytokinesis.py b/limbo/find_cytokinesis.py
similarity index 100%
rename from find_cytokinesis.py
rename to limbo/find_cytokinesis.py
diff --git a/find_cytokinesis_diane.py b/limbo/find_cytokinesis_diane.py
similarity index 100%
rename from find_cytokinesis_diane.py
rename to limbo/find_cytokinesis_diane.py
diff --git a/search_OMERO.py b/limbo/search_OMERO.py
similarity index 100%
rename from search_OMERO.py
rename to limbo/search_OMERO.py
diff --git a/tsa_inprogress.py b/limbo/tsa_inprogress.py
similarity index 100%
rename from tsa_inprogress.py
rename to limbo/tsa_inprogress.py
diff --git a/plotting.py b/plotting.py
index c4f616e..9676054 100644
--- a/plotting.py
+++ b/plotting.py
@@ -18,6 +18,11 @@ def kymograph(
title=None,
returnfig=False,
):
+ """
+ Plot a heatmap.
+
+ Typically each row is a single cell and the x-axis shows time.
+ """
if hue == "births":
cmap = "Greys"
elif "growth_rate" in hue:
@@ -62,13 +67,8 @@ def kymograph(
return fig, ax
-###
-
-
def plot_random_time_series(time, values, signalname=None, number=5):
- """
- Plots random time series on mouse click and terminates on a key press
- """
+ """Plot random time series on mouse click and terminates on a key press."""
fig = plt.figure()
go = True
@@ -97,9 +97,6 @@ def plot_random_time_series(time, values, signalname=None, number=5):
print(".")
-###
-
-
def plot_lineage(
idx,
df,
@@ -111,7 +108,8 @@ def plot_lineage(
plot_G1=False,
):
"""
- Plots the signals for one cell lineage.
+ Plot the signals for one cell lineage.
+
If "growth_rate" or "volume" is a signal, plots the signal for the
mother and the different buds.
@@ -138,17 +136,17 @@ def plot_lineage(
raise Exception("idx not part of dataframe")
signals = gu.makelist(signals)
nosubplots = len(signals)
- # show buddingss if possible
+ # show buddings if possible
if "buddings" in df.columns:
buddings = df[df.id == idx]["buddings"].to_numpy()
b_pts = np.where(buddings)[0]
if "births" in df.columns:
buddings = df[df.id == idx]["births"].to_numpy()
b_pts = np.where(buddings)[0]
- if len(b_pts) == 1:
- nb_pts = np.concatenate((b_pts, [len(buddings) - 1]))
- else:
- nb_pts = b_pts
+ if len(b_pts) == 1:
+ nb_pts = np.concatenate((b_pts, [len(buddings) - 1]))
+ else:
+ nb_pts = b_pts
# show cytokinesis point if possible
if cyto_pts_signal and cyto_pts_signal in df.columns:
cyto = df[df.id == idx][cyto_pts_signal].to_numpy()
@@ -232,9 +230,6 @@ def plot_lineage(
plt.show()
-###
-
-
def plot_replicate_array(
data,
t=None,
@@ -247,7 +242,7 @@ def plot_replicate_array(
show=True,
):
"""
- Plots summary statistics versus axis 1 for an array of replicates.
+ Plot summary statistics versus axis 1 (time) for an array of replicates.
Parameters
----------
diff --git a/run_gr.py b/run_gr.py
deleted file mode 100644
index 3d76025..0000000
--- a/run_gr.py
+++ /dev/null
@@ -1,49 +0,0 @@
-import matplotlib.pylab as plt
-import pickle
-import genutils as gu
-from mywela.dataloader import dataloader
-from mywela.growth_rate import find_gr, addgrfrompkl
-
-
-datadir = "/Users/pswain/ECDF/Swainlab/aliby_datasets/Arin"
-dataname = "26643_2022_05_23_flavin_htb2_glucose_20gpL_01_00"
-# dataname = "25681_2022_04_30_flavin_htb2_glucose_10mgpL_01_00"
-
-max_no_cells = None
-use_tsv = True
-
-pxsize = 0.182
-if max_no_cells is None:
- save = True
-else:
- save = False
-
-# get data
-dl = dataloader(
- datadir, outdir="/Users/pswain/Dropbox/wip/uscope_analyses/tsv_data"
-)
-dl.load(dataname, use_tsv=use_tsv)
-
-# data
-b_vol = dl.wide_df("bud_volume")
-m_vol = dl.wide_df("volume")
-births = dl.wide_df("births")
-
-# bud growth rate
-res_b = find_gr(b_vol, births, max_no_cells=max_no_cells, bounds={0: (0, 8)})
-if save:
- pickle.dump(res_b, open(dataname + "_res_b.pkl", "wb"))
- gu.figs2pdf(dataname + "_b.pdf")
- plt.close("all")
-
-# mother growth rate
-res_m = find_gr(m_vol, max_no_cells=max_no_cells)
-if save:
- pickle.dump(res_m, open(dataname + "_res_m.pkl", "wb"))
- gu.figs2pdf(dataname + "_m.pdf")
- plt.close("all")
-
-# add to dataframe
-if save:
- addgrfrompkl(dl, ".")
- dl.save(dataname)
--
GitLab