/
hydrograph2.py
1550 lines (1028 loc) · 53.2 KB
/
hydrograph2.py
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# -*- coding: utf-8 -*-
"""
Copyright 2014-2015 Jean-Sebastien Gosselin
email: jnsebgosselin@gmail.com
This file is part of WHAT (Well Hydrograph Analysis Toolbox).
WHAT is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>
"""
#----- STANDARD LIBRARY IMPORTS -----
from os import path
from calendar import monthrange
import csv
from math import sin, cos, sqrt, atan2, radians
#from time import clock
#----- THIRD PARTY IMPORTS -----
import numpy as np
import matplotlib as mpl
mpl.use('Qt4Agg')
mpl.rcParams['backend.qt4'] = 'PySide'
#from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
#from matplotlib.backends.backend_cairo import FigureCanvasCairo as FigureCanvas
#from matplotlib.backends.backend_cairo import RendererCairo as Renderer
import matplotlib.pyplot as plt
from PySide import QtGui
from xlrd.xldate import xldate_from_date_tuple
from xlrd import xldate_as_tuple, open_workbook
#from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT
#---- PERSONAL IMPORTS ----
import database as db
#import meteo
class LabelDatabase():
def __init__(self, language): #------------------------------ English -----
self.temperature = u'Tmax weekly (°C)'
self.mbgs = 'Water Level at Well %s (mbgs)'
self.masl = 'Water Level at Well %s (masl)'
self.precip = 'Ptot weekly (mm)'
self.station_meteo = 'Climatological Station = %s (located %0.1f km from the well)'
self.month_names = ["JAN", "FEB", "MAR", "APR", "MAY", "JUN",
"JUL", "AUG", "SEP", "OCT", "NOV", "DEC"]
if language == 'French': #-------------------------------- French -----
self.mbgs = "Niveau d'eau au puits %s (mbgs)"
self.masl = "Niveau d'eau au puits %s (masl)"
self.precip = 'Ptot hebdo (mm)'
self.temperature = u'Tmax hebdo (°C)'
self.station_meteo = u'Station climatologique = %s (située à %0.1f km du puits)'
self.month_names = ["JAN", u"FÉV", "MAR", "AVR", "MAI", "JUN",
"JUL", u"AOÛ", "SEP", "OCT", "NOV", u"DÉC"]
class Hydrograph(mpl.figure.Figure):
def __init__(self, *args, **kargs):
super(Hydrograph, self).__init__(*args, **kargs)
self.isHydrographExists = False
#---- set canvas and renderer ----
self.set_canvas(FigureCanvas(self))
self.canvas.get_renderer()
#---- Fig Init ----
self.fwidth = 11.0
self.fheight = 8.5
self.patch.set_facecolor('white')
#---- Database ----
HeaderDB = db.FileHeaders()
self.header = HeaderDB.graph_layout
#---- Scales ----
self.WLmin = 0
self.WLscale = 0
self.RAINscale = 20
self.TIMEmin = 36526
self.TIMEmax = 36526
self.NZGrid = 20 # Dundurn: 17 # Old version: 26
#---- Labels ----
self.title_state = 0 # 0: No title; 1: With Title
self.title_text = 'Add A Title To The Figure Here'
self.language = 'English'
#---- Layout Options
self.WLdatum = 0 # 0: mbgs; 1: masl
self.trend_line = 0
self.isLegend = False
self.meteoOn = True # controls wether meteo data are plotted or not
self.gridLines = 2 # 0 -> None, 1 -> "-" 2 -> ":"
self.datemode = 'month' # 'month' or 'year'
self.label_font_size = 14
self.date_labels_display_pattern = 3
#---- Waterlvl Obj ----
self.WaterLvlObj = []
#---- Daily Weather ----
self.fmeteo = [] # path to the weather data file (.out)
self.finfo = [] # path the the .log file associated with the .out file
self.TIMEmeteo = np.array([])
self.TMAX = np.array([])
self.PTOT = np.array([])
self.RAIN = np.array([])
#---- Bin Redistributed Weather ----
self.bTIME = np.array([])
self.bTMAX = np.array([])
self.bPTOT = np.array([])
self.bRAIN = np.array([])
self.bwidth_indx = 1
# 0: 1 day;
# 1: 7 days;
# 2: 15 days;
# 3: 30 days;
# 4: monthly;
# 5: yearly
self.NMissPtot = []
def generate_hydrograph(self, MeteoObj): #================================
#---- Reinit Figure ----
self.clf()
fheight = self.fheight # Figure height in inches
fwidth = self.fwidth # Figure width in inches
if self.meteoOn == False:
fheight /= 2
self.set_size_inches(fwidth, fheight, forward=True)
#---- Update Variables ----
WaterLvlObj = self.WaterLvlObj
if self.meteoOn == True:
#---- Assign Weather Data ----
self.name_meteo = MeteoObj.STA
DATA = MeteoObj.DATA
# DATA = [YEAR, MONTH, DAY, TMAX, TMIN, TMEAN, PTOT, ETP, RAIN]
self.TIMEmeteo = MeteoObj.TIME # Time in numeric format (days)
self.TMAX = DATA[:, 3] # Daily maximum temperature (deg C)
self.PTOT = DATA[:, 6] # Daily total precipitation (mm)
self.RAIN = DATA[:, -1]
#---- Resample Data in Bins ----
self.resample_bin()
#-------------------------------------------------- AXES CREATION ----
# http://stackoverflow.com/questions/15303284/
# multiple-y-scales-but-only-one-enabled-for-pan-and-zoom
# http://matplotlib.1069221.n5.nabble.com/Control-twinx-series-zorder-
# ax2-series-behind-ax1-series-or-place-ax2-on-left-ax1
# -on-right-td12994.html
#--- Time (host) ---
# Also holds the gridlines.
self.ax1 = self.add_axes([0, 0, 1, 1], frameon=False)
#--- Frame ---
# Only used to display the frame so it is always on top.
self.ax0 = self.add_axes(self.ax1.get_position(), frameon=True)
self.ax0.patch.set_visible(False)
self.ax0.set_zorder(self.ax1.get_zorder() + 20)
self.ax0.tick_params(bottom='off', top='off', left='off', right='off',
labelbottom='off', labelleft='off')
# for loc in ['top', 'bottom', 'right', 'left']:
# self.ax0.spines[loc].set_linewidth(0.5)
#--- Water Levels ---
self.ax2 = self.ax1.twinx()
self.ax2.set_zorder(self.ax1.get_zorder() + 10)
self.ax2.yaxis.set_ticks_position('left')
self.ax2.yaxis.set_label_position('left')
self.ax2.tick_params(axis='y', direction='out', labelsize=10)
for loc in ['top', 'bottom', 'right', 'left']:
self.ax2.spines[loc].set_visible(False)
self.update_waterlvl_scale()
if self.meteoOn == True:
#--- Precipitation ---
self.ax3 = self.ax1.twinx()
self.ax3.set_zorder(self.ax1.get_zorder() + 10)
self.ax3.set_navigate(False)
for loc in ['top', 'bottom', 'right', 'left']:
self.ax3.spines[loc].set_visible(False)
#--- Air Temperature ---
self.ax4 = self.ax1.twinx()
self.ax4.set_zorder(self.ax1.get_zorder() - 10)
self.ax4.set_navigate(False)
for loc in ['top', 'bottom', 'right', 'left']:
self.ax4.spines[loc].set_visible(False)
#-------------------------------------------------- Update margins ---
self.bottom_margin = 0.75
self.set_margins() # set margins for all the axes
#--------------------------------------------------- FIGURE TITLE ----
self.dZGrid_inch = (fheight - 2 * self.bottom_margin) / self.NZGrid
xTitle = (self.TIMEmin + self.TIMEmax) / 2.
ytitle = self.NZGrid + (0.4 / self.dZGrid_inch)
self.figTitle = self.ax1.text(xTitle, ytitle, self.title_text,
fontsize=18 * fheight / 8.5,
horizontalalignment='center',
verticalalignment='center')
self.draw_figure_title()
#------------------------------------------- WEATHER STATION TEXT ----
# Calculate horizontal distance between weather station and
# observation well.
LAT1 = float(WaterLvlObj.LAT)
LON1 = float(WaterLvlObj.LON)
LAT2 = float(MeteoObj.LAT)
LON2 = float(MeteoObj.LON)
self.dist = LatLong2Dist(LAT1, LON1, LAT2, LON2)
# display text on figure
text1_ypos = self.NZGrid + 0.025 / self.dZGrid_inch
self.text1 = self.ax1.text(self.TIMEmax, text1_ypos, '',
rotation=0, verticalalignment='bottom',
horizontalalignment='right', fontsize=10)
#---------------------------------------------------- TIME + GRID ----
self.xlab = [] # Initiate variable
self.set_time_scale()
self.ax1.xaxis.set_ticklabels([])
self.ax1.xaxis.set_ticks_position('bottom')
self.ax1.tick_params(axis='both',direction='out')
self.ax1.set_yticks(np.arange(0, self.NZGrid, 2))
self.ax1.yaxis.set_ticklabels([])
self.ax1.tick_params(axis='y', length=0)
self.ax1.patch.set_facecolor('none')
self.set_gridLines()
#---------------------------------------------------- WATER LEVEL ----
#---- Continuous Line Datalogger ----
self.l1_ax2, = self.ax2.plot([], [], '-', zorder = 10, linewidth=1)
#---- Data Point Datalogger ----
self.l2_ax2, = self.ax2.plot([], [], '.', color=[0.65, 0.65, 1.],
markersize=5)
#---- Manual Mesures ----
self.h_WLmes, = self.ax2.plot([], [], 'o', zorder = 15,
label='Manual measures')
plt.setp(self.h_WLmes, markerfacecolor='none', markersize=5,
markeredgecolor=(1, 0.25, 0.25), markeredgewidth=1.5)
self.draw_waterlvl()
#-------------------------------------------------------- WEATHER ----
if self.meteoOn == True:
#---------------------------------------------- PRECIPITATION ----
self.update_precip_scale()
self.ax3.yaxis.set_ticks_position('right')
self.ax3.yaxis.set_label_position('right')
self.ax3.tick_params(axis='y', direction='out', labelsize=10)
#---- INIT ARTISTS ----
self.PTOT_bar, = self.ax3.plot([], [])
self.RAIN_bar, = self.ax3.plot([], [])
self.baseline, = self.ax3.plot([self.TIMEmin, self.TIMEmax],
[0, 0], 'k')
#-------------------------------------------- AIR TEMPERATURE ----
TEMPmin = -40
TEMPscale = 20
TEMPmax = 40
self.ax4.axis(ymin=TEMPmax-TEMPscale*self.NZGrid,
ymax=TEMPmax)
yticks_position = np.array([TEMPmin, 0, TEMPmax])
self.ax4.set_yticks(yticks_position)
self.ax4.yaxis.set_ticks_position('left')
self.ax4.tick_params(axis='y', direction='out', labelsize=10)
self.ax4.yaxis.set_label_position('left')
#---- INIT ARTISTS ----
self.l1_ax4, = self.ax4.plot([], []) # fill shape
self.l2_ax4, = self.ax4.plot([], [], color='black') # contour line
#------------------------------------- MISSING VALUES MARKERS ----
if self.finfo:
#---- PRECIPITATION ----
PTOTmiss_time, _ = load_weather_log(self.finfo,
'Total Precip (mm)',
self.bTIME, self.bPTOT)
self.NMissPtot = len(PTOTmiss_time)
y = np.ones(self.NMissPtot) * -5 * self.RAINscale / 20.
self.PTOTmiss_dots, = self.ax3.plot(PTOTmiss_time, y, '.r')
plt.setp(self.PTOTmiss_dots, markersize=3)
#---- Air Temperature ----
Temp_missing_time, _ = load_weather_log(self.finfo,
'Max Temp (deg C)',
self.bTIME, self.bTMAX)
NMissTMAX = len(Temp_missing_time)
y = np.ones(NMissTMAX) * 35
TMAXmiss_dots, = self.ax4.plot(Temp_missing_time, y, '.r')
plt.setp(TMAXmiss_dots, markersize=3)
self.draw_weather()
#--------------------------------------------------- DRAW YLABELS ----
self.draw_ylabels()
#--------------------------------------------------------- LEGEND ----
if self.isLegend == True:
#---- Water Level ----
self.ax2.legend(loc=4, numpoints=1, fontsize=10, ncol=2)
#---- Weather ----
rec1 = plt.Rectangle((0, 0), 1, 1, fc=[0.65,0.65,0.65])
rec2 = plt.Rectangle((0, 0), 1, 1, fc=[0, 0, 1])
rec3 = plt.Rectangle((0, 0), 1, 1, fc=[1, 0.65, 0.65])
labels = ['Snow', 'Rain', 'Air Temperature', 'Missing Data']
self.ax4.legend([rec1, rec2, rec3, TMAXmiss_dots], labels,
loc=[0.01, 0.45], numpoints=1, fontsize=10)
#---------------------------------------------------- UPDATE FLAG ----
self.isHydrographExists = True
def set_fig_size(self, fwidth, fheight): #================================
self.fwidth = fwidth # Figure width in inches
self.fheight = fheight # Figure height in inches
self.set_size_inches(fwidth, fheight)
self.set_margins()
self.draw_ylabels()
self.set_time_scale()
self.canvas.draw()
def set_margins(self): #==================================================
#---- MARGINS (Inches / Fig. Dimension) ----
left_margin = 0.85 / self.fwidth
right_margin = 0.85 / self.fwidth
top_margin = 0.35 / self.fheight
bottom_margin = 0.75 / self.fheight
if self.title_state == 1:
top_margin = 0.75 / self.fheight
if self.meteoOn == False:
right_margin = 0.35 / self.fwidth
#---- MARGINS (% of figure) ----
x0 = left_margin
w = 1 - (left_margin + right_margin)
if self.meteoOn == True:
y0 = bottom_margin
h = 1 - (bottom_margin + top_margin)
else:
y0 = bottom_margin / 2.
h = 1 - (bottom_margin + top_margin) / 2.
self.ax0.set_position([x0, y0, w, h])
self.ax1.set_position([x0, y0, w, h])
self.ax2.set_position([x0, y0, w, h])
if self.meteoOn == True:
self.ax3.set_position([x0, y0, w, h])
self.ax4.set_position([x0, y0, w, h])
def draw_ylabels(self): #=================================================
labelDB = LabelDatabase(self.language)
#----------------------------------------- Calculate LabelPadding ----
left_margin = 0.85
right_margin = 0.85
if self.meteoOn == False:
right_margin = 0.35
axwidth = (self.fwidth - left_margin - right_margin)
labPad = 0.3 / 2.54 # in Inches
labPad /= axwidth # relative coord.
#-------------------------------- YLABELS LEFT (Temp. & Waterlvl) ----
if self.WLdatum == 0:
lab_ax2 = labelDB.mbgs % self.WaterLvlObj.name_well
elif self.WLdatum == 1:
lab_ax2 = labelDB.masl % self.WaterLvlObj.name_well
#---- Water Level ----
self.ax2.set_ylabel(lab_ax2,rotation=90,
fontsize=self.label_font_size,
verticalalignment='bottom',
horizontalalignment='center')
# Get bounding box dimensions of yaxis ticklabels for ax2
renderer = self.canvas.get_renderer()
bbox2_left, _ = self.ax2.yaxis.get_ticklabel_extents(renderer)
# bbox are structured in the the following way: [[ Left , Bottom ],
# [ Right, Top ]]
# Transform coordinates in ax2 coordinate system.
bbox2_left = self.ax2.transAxes.inverted().transform(bbox2_left)
# Calculate the labels positions in x and y.
ylabel2_xpos = bbox2_left[0, 0] - labPad
ylabel2_ypos = (bbox2_left[1, 1] + bbox2_left[0, 1]) / 2.
if self.meteoOn == False:
self.ax2.yaxis.set_label_coords(ylabel2_xpos, ylabel2_ypos)
return
#---- Temperature ----
self.ax4.set_ylabel(labelDB.temperature, rotation=90, va='bottom',
ha='center', fontsize=self.label_font_size)
# Get bounding box dimensions of yaxis ticklabels for ax4
bbox4_left, _ = self.ax4.yaxis.get_ticklabel_extents(renderer)
# Transform coordinates in ax4 coordinate system.
bbox4_left = self.ax4.transAxes.inverted().transform(bbox4_left)
# Calculate the labels positions in x and y.
ylabel4_xpos = bbox4_left[0, 0] - labPad
ylabel4_ypos = (bbox4_left[1, 1] + bbox4_left[0, 1]) / 2.
# Take the position which is farthest from the left y axis in order
# to have both labels on the left aligned.
ylabel_xpos = min(ylabel2_xpos, ylabel4_xpos)
self.ax2.yaxis.set_label_coords(ylabel_xpos, ylabel2_ypos)
self.ax4.yaxis.set_label_coords(ylabel_xpos, ylabel4_ypos)
#---------------------------------------- ylabels : Precipitation ----
self.ax3.set_ylabel(labelDB.precip, rotation=270, va='bottom',
ha='center', fontsize=self.label_font_size)
# Get bounding box dimensions of yaxis ticklabels for ax3
_, bbox3_right = self.ax3.yaxis.get_ticklabel_extents(renderer)
# Transform coordinates in ax3 coordinate system and
# calculate the labels positions in x and y.
bbox3_right = self.ax3.transAxes.inverted().transform(bbox3_right)
ylabel3_xpos = bbox3_right[1, 0] + labPad
ylabel3_ypos = (bbox3_right[1, 1] + bbox3_right[0, 1]) / 2.
# Take the position which is farthest from the left y axis in order
# to have both labels on the left aligned.
self.ax3.yaxis.set_label_coords(ylabel3_xpos, ylabel3_ypos)
#------------------------------------------ WEATHER STATION LABEL ----
text_top_margin = labelDB.station_meteo % (self.name_meteo,
self.dist)
self.text1.set_text(text_top_margin)
def set_waterLvlObj(self, WaterLvlObj): #=================================
self.WaterLvlObj = WaterLvlObj
def checkLayout(self, name_well, filename): #=============================
with open(filename, 'r') as f:
reader = list(csv.reader(f, delimiter='\t'))
reader = np.array(reader)
# Check if config file is from an old version of Hydroprint
# and if yes, convert it to the new version.
nCONFG, nPARA = np.shape(reader)
if nPARA < len(self.header[0]):
nMissing = len(self.header[0]) - nPARA
col2add = np.zeros((nCONFG, nMissing)).astype(int)
col2add = col2add.astype(str)
reader = np.hstack((reader, col2add))
reader[0] = self.header[0]
if nPARA < 8:
reader[1:, 7] = 'Add A Title To The Figure Here'
if nPARA < 9:
reader[1:, 8] = 20
if nPARA < 10:
reader[1:, 9] = 0
if nPARA < 11:
reader[1:, 10] = 0
with open(filename, 'w') as f:
writer = csv.writer(f, delimiter='\t')
writer.writerows(reader)
msg = ('The "graph_layout.lst" file is from an older version ' +
'of WHAT. The old file has been converted to the newer ' +
'version.')
print(msg)
# Check if there is a layout stored for the current
# selected observation well.
row = np.where(reader[:,0] == name_well)[0]
if len(row) > 0:
layoutExist = True
else:
layoutExist = False
return layoutExist
def load_layout(self, name_well, filename): #=============================
# A <checkConfig> is supposed to have been carried before this method
# is called. So it can be supposed at this point that everything is
# fine with the graph layout for this well.
with open(filename, 'r') as f:
reader = list(csv.reader(f, delimiter='\t'))
reader = np.array(reader)
row = np.where(reader[:,0] == name_well)[0]
reader = reader[row][0]
self.fmeteo = reader[1]
self.finfo = self.fmeteo[:-3] + 'log'
self.WLmin = reader[2].astype(float)
self.WLscale = reader[3].astype(float)
self.TIMEmin = reader[4].astype(float)
self.TIMEmax = reader[5].astype(float)
self.title_state = reader[6].astype(float)
if self.title_state != 0:
self.title_state = 1
self.title_text = reader[7].astype(str)
self.RAINscale = reader[8].astype(float)
self.WLdatum = reader[9].astype(int)
self.trend_line = reader[10].astype(int)
def save_layout(self, name_well, filename): #=============================
#---- load file ----
with open(filename, 'r') as f:
reader = list(csv.reader(f, delimiter='\t'))
reader = np.array(reader)
#---- update content ----
rowx = np.where(reader[:,0] == name_well)[0]
new = [name_well, self.fmeteo, self.WLmin, self.WLscale,
self.TIMEmin, self.TIMEmax,self.title_state, self.title_text,
self.RAINscale, self.WLdatum, self.trend_line]
if len(rowx) == 0:
reader = np.vstack((reader, new))
else:
reader = np.delete(reader, rowx, 0)
reader = np.vstack((reader, new))
reader[0] = self.header[0]
#---- save file ----
with open(filename, 'w') as f:
writer = csv.writer(f, delimiter='\t')
writer.writerows(reader)
def best_fit_waterlvl(self): #============================================
WL = self.WaterLvlObj.lvl
if self.WLdatum == 1: # masl
WL = self.WaterLvlObj.ALT - WL
WL = WL[~np.isnan(WL)]
dWL = np.max(WL) - np.min(WL)
ygrid = self.NZGrid - 10
#----- WL Scale -----
SCALE = np.hstack((np.arange(0.05, 0.30, 0.05),
np.arange(0.3, 5.1, 0.1)))
dSCALE = np.abs(SCALE - dWL / ygrid)
indx = np.where(dSCALE == np.min(dSCALE))[0][0]
self.WLscale = SCALE[indx]
#-----WL Min Value-----
if self.WLdatum == 0: # mbgs
N = np.ceil(np.max(WL) / self.WLscale)
elif self.WLdatum == 1: # masl
#WL = self.WaterLvlObj.ALT - WL
N = np.floor(np.min(WL) / self.WLscale)
self.WLmin = self.WLscale * N
return self.WLscale, self.WLmin
def best_fit_time(self, TIME): #==========================================
# ----- Data Start -----
date0 = xldate_as_tuple(TIME[0], 0)
date0 = (date0[0], date0[1], 1)
self.TIMEmin = xldate_from_date_tuple(date0, 0)
# ----- Date End -----
date1 = xldate_as_tuple(TIME[-1], 0)
year = date1[0]
month = date1[1] + 1
if month > 12:
month = 1
year += 1
date1 = (year, month, 1)
self.TIMEmax = xldate_from_date_tuple(date1, 0)
return date0, date1
def resample_bin(self): #==================================================
# 1 day; 7 days; 15 days; 30 days; monthly; yearly
self.bwidth = [1., 7., 15., 30., 30., 365.][self.bwidth_indx]
bwidth = self.bwidth
if self.bwidth_indx == 0: # daily
self.bTIME = np.copy(self.TIMEmeteo)
self.bTMAX = np.copy(self.TMAX)
self.bPTOT = np.copy(self.PTOT)
self.bRAIN = np.copy(self.RAIN)
elif self.bwidth_indx in [1, 2, 3]: #7 days; 15 days; 30 days
self.bTIME = self.bin_sum(self.TIMEmeteo, bwidth) / bwidth
self.bTMAX = self.bin_sum(self.TMAX, bwidth) / bwidth
self.bPTOT = self.bin_sum(self.PTOT, bwidth)
self.bRAIN = self.bin_sum(self.RAIN, bwidth)
elif self.bwidth_indx == 4 : # monthly
print('option not yet available, kept default of 1 day')
elif self.bwidth_indx == 5 : # yearly
print('option not yet available, kept default of 1 day')
def bin_sum(self, x, bwidth): #============================================
"""
Sum data x over bins of width "bwidth" starting at indice 0 of x.
If there is residual data at the end because of the last bin being not
complete, data are rejected and removed from the reshaped series.
"""
nbin = np.floor(len(x) / bwidth)
bheight = x[:nbin*bwidth].reshape(nbin, bwidth)
bheight = np.sum(bheight, axis=1)
# nres = len(x) - (nbin * bwidth)
return bheight
def draw_waterlvl(self): #=================================================
"""
This method is called the first time the graph is plotted and each
time water level datum is changed.
"""
#------------------------------------------------- Logger Measures ----
time = self.WaterLvlObj.time
if self.WLdatum == 1: # masl
water_lvl = self.WaterLvlObj.ALT - self.WaterLvlObj.lvl
else: # mbgs -> yaxis is inverted
water_lvl = self.WaterLvlObj.lvl
if self.trend_line == 1:
tfilt, wlfilt = filt_data(time, water_lvl, 7)
self.l1_ax2.set_data(tfilt, wlfilt)
self.l1_ax2.set_label('WL Trend Line')
self.l2_ax2.set_data(time, water_lvl)
else:
self.l1_ax2.set_data(time, water_lvl)
self.l1_ax2.set_label('Water Level')
self.l2_ax2.set_data([], [])
#------------------------------------------------ Manual Measures ----
TIMEmes = self.WaterLvlObj.TIMEmes
WLmes = self.WaterLvlObj.WLmes
if len(WLmes) > 1:
if self.WLdatum == 1: # masl
WLmes = self.WaterLvlObj.ALT - WLmes
self.h_WLmes.set_data(TIMEmes, WLmes)
def draw_weather(self): #=================================================
"""
This method is called the first time the graph is plotted and each
time the time scale is changed by the user.
"""
if self.meteoOn == False:
print('meteoOn == False')
return
#--------------------------------- SUBSAMPLE WEATHER DATA TO PLOT ----
istart = np.where(self.bTIME > self.TIMEmin)[0]
if len(istart) == 0:
istart = 0
else:
istart = istart[0]
if istart > 0:
istart -= 1
iend = np.where(self.bTIME < self.TIMEmax)[0]
if len(iend) == 0:
iend = 0
else:
iend = iend[-1]
if iend < len(self.bTIME):
iend += 1
time = self.bTIME[istart:iend]
Tmax = self.bTMAX[istart:iend]
Ptot = self.bPTOT[istart:iend]
Rain = self.bRAIN[istart:iend]
#---------------------------------------------------- PLOT PRECIP ----
TIME2X = np.zeros(len(time) * 4)
Ptot2X = np.zeros(len(time) * 4)
Rain2X = np.zeros(len(time) * 4)
n = self.bwidth / 2.
f = 0.85 # Space between individual bar.
TIME2X[0::4] = time - n * f
TIME2X[1::4] = time - n * f
TIME2X[2::4] = time + n * f
TIME2X[3::4] = time + n * f
Ptot2X[0::4] = 0
Ptot2X[1::4] = Ptot
Ptot2X[2::4] = Ptot
Ptot2X[3::4] = 0
Rain2X[0::4] = 0
Rain2X[1::4] = Rain
Rain2X[2::4] = Rain
Rain2X[3::4] = 0
self.PTOT_bar.remove()
self.RAIN_bar.remove()
self.PTOT_bar = self.ax3.fill_between(TIME2X, 0., Ptot2X,
color=(0.65,0.65,0.65),
alpha=1., edgecolor='none')
self.RAIN_bar = self.ax3.fill_between(TIME2X, 0., Rain2X, color='blue',
alpha=1., edgecolor='none')
self.baseline.set_data([self.TIMEmin, self.TIMEmax], [0, 0])
#--------------------------------------------------- PLOT AIR TEMP ----
TIME2X = np.zeros(len(time)*2)
Tmax2X = np.zeros(len(time)*2)
n = self.bwidth / 2.
TIME2X[0:2*len(time)-1:2] = time - n
TIME2X[1:2*len(time):2] = time + n
Tmax2X[0:2*len(time)-1:2] = Tmax
Tmax2X[1:2*len(time):2] = Tmax
color = [255./255, 204./255, 204./255]
self.l1_ax4.remove()
self.l1_ax4 = self.ax4.fill_between(TIME2X, 0., Tmax2X, color=color,
edgecolor='none')
self.l2_ax4.set_xdata(TIME2X)
self.l2_ax4.set_ydata(Tmax2X)
def set_time_scale(self): #===============================================
#----------------------------------------------- time min and max ----
if self.datemode == 'year':
year = xldate_as_tuple(self.TIMEmin, 0)[0]
self.TIMEmin = xldate_from_date_tuple((year, 1, 1), 0)
last_month = xldate_as_tuple(self.TIMEmax, 0)[1] == 1
last_day = xldate_as_tuple(self.TIMEmax, 0)[2] == 1
if last_month and last_day:
pass
else:
year = xldate_as_tuple(self.TIMEmax, 0)[0] + 1
self.TIMEmax = xldate_from_date_tuple((year, 1, 1), 0)
#---------------------------------------------- xticks and labels ----
#---- compute parameters ----
xticks_info = self.make_xticks_info()
#---- major ----
self.ax1.set_xticks(xticks_info[0])
#---- minor ----
# labels are set using the minor ticks.
# self.ax1.set_xticks(xticks_info[1], minor=True)
# self.ax1.tick_params(which='minor', length=0)
# self.ax1.xaxis.set_ticklabels(xticks_info[2], minor=True, rotation=45,
# va='top', ha='right', fontsize=10)
#--------------------------------------------------------- xlabels ---
# labels are placed manually instead.
#---- Remove labels ----
for i in range(len(self.xlab)):
self.xlab[i].remove()
#---- Redraw labels ----
self.xlab = []
for i in range(len(xticks_info[1])) :
xlab = self.ax1.text(xticks_info[1][i], -0.15,
xticks_info[2][i], rotation=45,
va='top', ha='right', fontsize=10)
self.xlab.append(xlab)
#------------------------------------------- text horiz. position ----
# adjust "climatological station" label and
# title horizontal position
self.text1.set_x(self.TIMEmax)
self.figTitle.set_x((self.TIMEmin + self.TIMEmax) / 2.)
#---------------------------------------------------- axis limits ----
self.ax1.axis([self.TIMEmin, self.TIMEmax, 0, self.NZGrid])
def draw_xlabels(self): #==================================================
# Called when there is a change in language of the labels