Skip to content

Commit

Permalink
Merge pull request #94 from NDoering99/Code_Class_movement
Browse files Browse the repository at this point in the history 
move openmmdl_analysis functions to clases and clean code
  • Loading branch information
@talagayev
talagayev authored Aug 7, 2024
2 parents 3008f2c + da1bd99 commit 4eaeb21
Show file tree
Hide file tree
Showing 16 changed files with 3,043 additions and 2,610 deletions.
2 changes: 1 addition & 1 deletion openmmdl/_version.py
View file
Original file line number Diff line number Diff line change
@@ -1 +1 @@
__version__ = "1.0.0+724.g9044002.dirty"
__version__ = "0.9.2+12.g3008f2c.dirty"
112 changes: 100 additions & 12 deletions openmmdl/openmmdl_analysis/barcode_generation.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,32 @@ def __init__(self, df):
df (pandas dataframe): Dataframe containing all interactions from plip analysis (typically df_all)
"""
self.df = df
self.interactions = self.gather_interactions()

def gather_interactions(self):
hydrophobic_interactions = self.df.filter(regex="hydrophobic").columns
acceptor_interactions = self.df.filter(regex="Acceptor_hbond").columns
donor_interactions = self.df.filter(regex="Donor_hbond").columns
pistacking_interactions = self.df.filter(regex="pistacking").columns
halogen_interactions = self.df.filter(regex="halogen").columns
waterbridge_interactions = self.df.filter(regex="waterbridge").columns
pication_interactions = self.df.filter(regex="pication").columns
saltbridge_ni_interactions = self.df.filter(regex="NI_saltbridge").columns
saltbridge_pi_interactions = self.df.filter(regex="PI_saltbridge").columns
metal_interactions = self.df.filter(regex="metal").columns

return {
"hydrophobic": hydrophobic_interactions,
"acceptor": acceptor_interactions,
"donor": donor_interactions,
"pistacking": pistacking_interactions,
"halogen": halogen_interactions,
"waterbridge": waterbridge_interactions,
"pication": pication_interactions,
"saltbridge_ni": saltbridge_ni_interactions,
"saltbridge_pi": saltbridge_pi_interactions,
"metal": metal_interactions,
}

def generate_barcode(self, interaction):
"""
Expand Down Expand Up @@ -62,6 +88,24 @@ def generate_waterids_barcode(self, interaction):

return waterid_barcode

def interacting_water_ids(self, waterbridge_interactions):
"""Generates a list of all water ids that form water bridge interactions.
Args:
df_all (pandas dataframe): dataframe containing all interactions from plip analysis (typicaly df_all)
waterbridge_interactions (list): list of strings containing the names of all water bridge interactions
Returns:
list: list of all unique water ids that form water bridge interactions
"""
interacting_waters = []
for waterbridge_interaction in waterbridge_interactions:
waterid_barcode = self.generate_waterids_barcode(waterbridge_interaction)
for waterid in waterid_barcode:
if waterid != 0:
interacting_waters.append(waterid)
return list(set(interacting_waters))


class BarcodePlotter:
def __init__(self, df_all):
Expand All @@ -85,17 +129,33 @@ def plot_barcodes(self, barcodes, save_path):
for i, (title, barcode) in enumerate(barcodes.items()):
ax = axs[i]
ax.set_axis_off()
ax.imshow(barcode.reshape(1, -1), cmap="binary", aspect="auto", interpolation="nearest", vmin=0, vmax=1)
ax.imshow(
barcode.reshape(1, -1),
cmap="binary",
aspect="auto",
interpolation="nearest",
vmin=0,
vmax=1,
)

percent_occurrence = (barcode.sum() / len(barcode)) * 100
ax.text(1.05, 0.5, f"{percent_occurrence:.2f}%", transform=ax.transAxes, va="center", fontsize=8)
ax.text(
1.05,
0.5,
f"{percent_occurrence:.2f}%",
transform=ax.transAxes,
va="center",
fontsize=8,
)
ax.set_title(title, fontweight="bold", fontsize=8)

os.makedirs(os.path.dirname(save_path), exist_ok=True)
plt.tight_layout()
plt.savefig(save_path, dpi=300, bbox_inches="tight")

def plot_waterbridge_piechart(self, waterbridge_barcodes, waterbridge_interactions, fig_type):
def plot_waterbridge_piechart(
self, waterbridge_barcodes, waterbridge_interactions, fig_type
):
if not waterbridge_barcodes:
print("No Piecharts to plot.")
return
Expand All @@ -105,7 +165,9 @@ def plot_waterbridge_piechart(self, waterbridge_barcodes, waterbridge_interactio

for waterbridge_interaction in waterbridge_interactions:
plt.clf()
waterid_barcode = self.barcode_gen.generate_waterids_barcode(waterbridge_interaction)
waterid_barcode = self.barcode_gen.generate_waterids_barcode(
waterbridge_interaction
)
waters_count = {}

for waterid in waterid_barcode:
Expand All @@ -117,12 +179,24 @@ def plot_waterbridge_piechart(self, waterbridge_barcodes, waterbridge_interactio

threshold = 7
total_values = sum(values)
small_ids = [id for id, value in waters_count.items() if (value / total_values) * 100 < threshold]
small_ids = [
id
for id, value in waters_count.items()
if (value / total_values) * 100 < threshold
]

if small_ids:
small_count = sum(count for id, count in waters_count.items() if id in small_ids)
values = [count if id not in small_ids else small_count for id, count in waters_count.items()]
labels = [f"ID {id}" if id not in small_ids else "" for id in waters_count.keys()]
small_count = sum(
count for id, count in waters_count.items() if id in small_ids
)
values = [
count if id not in small_ids else small_count
for id, count in waters_count.items()
]
labels = [
f"ID {id}" if id not in small_ids else ""
for id in waters_count.keys()
]

plt.pie(
values,
Expand All @@ -134,7 +208,9 @@ def plot_waterbridge_piechart(self, waterbridge_barcodes, waterbridge_interactio
plt.axis("equal")
plt.title(str(waterbridge_interaction), fontweight="bold")
legend_labels = [f"ID {id}" for id in waters_count.keys()]
legend = plt.legend(legend_labels, loc="upper right", bbox_to_anchor=(1.2, 1))
legend = plt.legend(
legend_labels, loc="upper right", bbox_to_anchor=(1.2, 1)
)
plt.setp(legend.get_texts(), fontsize="small")
plt.text(
0.5,
Expand All @@ -145,15 +221,25 @@ def plot_waterbridge_piechart(self, waterbridge_barcodes, waterbridge_interactio
transform=plt.gcf().transFigure,
)
plt.subplots_adjust(top=0.99, bottom=0.01)
plt.savefig(f"Barcodes/Waterbridge_Piecharts/{waterbridge_interaction}.{fig_type}", bbox_inches="tight", dpi=300)
plt.savefig(
f"Barcodes/Waterbridge_Piecharts/{waterbridge_interaction}.{fig_type}",
bbox_inches="tight",
dpi=300,
)

def plot_barcodes_grouped(self, interactions, interaction_type, fig_type):
ligatoms_dict = {}
for interaction in interactions:
ligatom = interaction.split("_")
ligatom.pop(0)
ligatom.pop(-1)
if interaction_type in ["acceptor", "donor", "waterbridge", "saltbridge_ni", "saltbridge_pi"]:
if interaction_type in [
"acceptor",
"donor",
"waterbridge",
"saltbridge_ni",
"saltbridge_pi",
]:
ligatom.pop(-1)
if interaction_type in ["saltbridge_ni", "saltbridge_pi"]:
ligatom.pop(-1)
Expand All @@ -178,4 +264,6 @@ def plot_barcodes_grouped(self, interactions, interaction_type, fig_type):
grouped_array = grouped_array.astype(int)
total_interactions[ligatom] = grouped_array

self.plot_barcodes(total_interactions, f"./Barcodes/{interaction_type}_interactions.{fig_type}")
self.plot_barcodes(
total_interactions, f"./Barcodes/{interaction_type}_interactions.{fig_type}"
)
Loading

0 comments on commit 4eaeb21

Please sign in to comment.