Remove deprecated functions

etta-drone
Dan Howe 6 years ago
parent a5d4eff9e3
commit 8b14686c4c

@ -26,94 +26,6 @@ from cycler import cycler
from survey_tools import call_lastools, extract_pts, update_survey_output
def plot_profiles(profile_info, profile, output_loc, LL_limit):
#plot the profile. expects output from CC_split_profile
YminorLocator=MultipleLocator(0.5)
XminorLocator=MultipleLocator(5)
fig,ax=plt.subplots(figsize=(8, 3))
num_plots=len(profile_info.keys())-1
colormap = plt.cm.jet
ax.set_prop_cycle(cycler('color', [colormap(i) for i in np.linspace(0, 0.9, num_plots)]))
max_y=0
for date in profile_info.keys():
if date!='info':
plt.plot(profile_info[date]['Chainage'], profile_info[date]['Elevation'], label=date)
try:
if max([i for i in profile_info[date]['Elevation'] if pd.isnull(i)==False])>max_y:
max_y=max([i for i in profile_info[date]['Elevation'] if pd.isnull(i)==False])
except:
print("empty elevation section for %s" % date)
plt.plot([LL_limit,LL_limit], [-1,max_y], 'r--', alpha=0.5, label="Landward Limit")
plt.xlabel('Chainage (m)',weight='bold')
plt.ylabel('Elevation (m AHD)',weight='bold')
plt.legend(loc='upper right', bbox_to_anchor=(1.3,1))
plt.title(profile)
plt.rcParams['font.size']=8
ax.set_ylim([-1,math.ceil(max_y)])
ax.xaxis.set_minor_locator(XminorLocator)
ax.yaxis.set_minor_locator(YminorLocator)
ax.xaxis.grid(True, which='minor', color='k', linestyle='-', alpha=0.3)
ax.yaxis.grid(True,which='minor',color='k', linestyle='-', alpha=0.3)
plt.grid(which='major', color='k', linestyle='-')
today=datetime.datetime.now().date().strftime('%Y%m%d')
plt.savefig(os.path.join(output_loc, '%s_%s.png' % (today, profile)),bbox_inches='tight',dpi=900)
plt.clf()
return None
def CC_split_profile(file2read):
# this reads the profile files and splits it into dates
file_master=pd.read_csv(file2read)
beach_original=file_master['Beach'].tolist()
profile_original=file_master['Profile'].tolist()
date_original=file_master['Date'].tolist()
chainage_original=file_master['Chainage'].tolist()
elevation_original=file_master['Elevation'].tolist()
easting_original=file_master['Easting'].tolist()
northing_original=file_master['Northing'].tolist()
data={}
i=0
#add info on the beach and profile number
data['info']={'Profile':profile_original[0], 'Beach':beach_original[0]}
date_now=date_original[0]
while i<len(file_master):
chainage_tmp=[]
elevation_tmp=[]
easting_tmp=[]
northing_tmp=[]
while i<len(file_master) and date_now==date_original[i]:
chainage_tmp.append(chainage_original[i])
elevation_tmp.append(elevation_original[i])
easting_tmp.append(easting_original[i])
northing_tmp.append(northing_original[i])
i=i+1
data[date_now]={'Beach': beach_original[i-1], 'Profile':profile_original[i-1],'Easting': easting_tmp, 'Northing':northing_tmp, 'Elevation':elevation_tmp, 'Chainage':chainage_tmp}
if i<len(file_master):
date_now=date_original[i]
return data
def profile_plots_volume(csv_loc, LL_xlsx, output_xlsx, graph_location):
#get a list of all csvs which will each be analysed
file_list=[]
@ -203,7 +115,7 @@ def remove_temp_files(directory):
return None
def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
def plot_profiles(profile_name, survey_date, csv_output_dir, graph_loc, ch_limits):
csv_name = profile_name + '.csv'
profiles = pd.read_csv(os.path.join(csv_output_dir, csv_name))
@ -216,8 +128,7 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
ax = plt.axes()
for col in profiles.columns:
profile = profiles.loc[ch_min:, col]
date_str = col.split('_')[-1]
date = '{}-{}-{}'.format(date_str[:4], date_str[4:6], date_str[6:])
date = '{}-{}-{}'.format(survey_date[:4], survey_date[4:6], survey_date[6:])
ax.plot(profile.index, profile, label=date)
@ -232,6 +143,7 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
png_name = os.path.join(graph_loc, profile_name + '.png')
plt.savefig(png_name, bbox_inches='tight', dpi=300)
plt.close()
input_file = 'Parameter Files/las-manipulation-survey-2.xlsx'
@ -302,7 +214,7 @@ for i, row in params_file.iterrows():
# Plot profiles of current beach
profile_names = df['Profile'].unique()
for profile_name in profile_names:
plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits)
plot_profiles(profile_name, survey_date, csv_output_dir, graph_loc, ch_limits)
#delete the temp files from the tmp_dir and the interim_dir

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