claudecode/AvianVisitors
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

adding working daily_plot.py

Browse Source
This commit is contained in:
Patrick McGuire
2021-12-01 09:13:05 -05:00
parent 7dd3d723f6
commit 92716f556a
1 changed files with 10 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/daily_plot.py
+10 -10
View File
@@ -17,7 +17,7 @@ df['Date']=pd.to_datetime(df['Date'])
df['Time']=pd.to_datetime(df['Time'])
#Add round hours to dataframe
df['Hour of day'] = [r.hour for r in df.Time]
df['Hour of Day'] = [r.hour for r in df.Time]
#Create separate dataframes for separate locations
df_jhb=df[df.Lat > -32]
@@ -25,7 +25,7 @@ df_ec = df[df.Lat < -32]
#Get todays readings for Joburg
now = datetime.now()
df_jhb_today = df_jhb[df_jhb['Date']==now.strftime("%d-%m-%y")]
df_jhb_today = df_jhb[df_jhb['Date']==now.strftime("%Y-%m-%d")]
# Definition to start getting top N detections - work in process
def filter_by_freq(df: pd.DataFrame, column: str, min_freq: int) -> pd.DataFrame:
@@ -80,7 +80,7 @@ plot.set(xlabel="Detections")
#Generate crosstab matrix for heatmap plot
heat = pd.crosstab(df_jhb_top10_today['Com_Name'],df_jhb_top10_today['Hour of day'])
heat = pd.crosstab(df_jhb_top10_today['Com_Name'],df_jhb_top10_today['Hour of Day'])
#Order heatmap Birds by frequency of occurrance
heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_jhb_top10_today['Com_Name']).iloc[:10].index)
heat.sort_index(level=0, inplace=True)
@@ -98,16 +98,16 @@ for _, spine in plot.spines.items():
spine.set_visible(True)
plot.set(ylabel=None)
plot.set(xlabel="Hour of day")
plot.set(xlabel="Hour of Day")
#Set combined plot layout and titles
plt.tight_layout()
f.subplots_adjust(top=0.9)
plt.suptitle("Last Updated: "+ str(now.strftime("%B %d, %Y %I:%M%P")))
plt.suptitle("Last Updated: "+ str(now.strftime("%B, %d at %I:%M%P")))
#Save combined plot
savename='/home/pi/BirdSongs/Extracted/Combo-'+str(now.strftime("%d-%m-%Y"))+'.png'
plt.savefig(savename)
plt.close()
#Get bottom 10 today
@@ -124,9 +124,9 @@ f, axs = plt.subplots(1, 2, figsize = (8, 4), gridspec_kw=dict(width_ratios=[3,
plot=sns.countplot(y='Com_Name', data = df_jhb_bot10_today, palette = pal+"_r", order=pd.value_counts(df_jhb_bot10_today['Com_Name']).iloc[:10].index, ax=axs[0])
plot.set_yticklabels(['\n'.join(textwrap.wrap(ticklabel.get_text(),17)) for ticklabel in plot.get_yticklabels()])
plot.set(ylabel=None)
plot.set(xlabel="Detections")
plot.set(xlabel="no. of detections")
#Generate crosstab matrix for heatmap plot
heat = pd.crosstab(df_jhb_bot10_today['Com_Name'],df_jhb_bot10_today['Hour of day'])
heat = pd.crosstab(df_jhb_bot10_today['Com_Name'],df_jhb_bot10_today['Hour of Day'])
#Order heatmap Birds by frequency of occurrance
heat.index = pd.CategoricalIndex(heat.index, categories = pd.value_counts(df_jhb_bot10_today['Com_Name']).iloc[:10].index)
@@ -146,9 +146,9 @@ plot.set(ylabel=None)
plt.tight_layout()
f.subplots_adjust(top=0.9)
plt.suptitle("Bottom 10 Detected: "+ str(now.strftime("%d-%h-%Y %H:%M")))
plot.set(xlabel="Hour of day")
plot.set(xlabel="Hour of Day")
#Save combined plot
savename='/home/pi/BirdSongs/Extracted/Combo2-'+str(now.strftime("%d-%m-%Y"))+'.png'
plt.savefig(savename)
plt.show()
plt.close()