def CopyRequiredFilesToGitRepository(ObjectsDirectory,DriverDirectory,TargetDirectory):
# Ensure the directories exist
ObjectsDirectory,DriverDirectory,TargetDirectory,TargetDriverDirectory = CheckFileStructuresForCopy(ObjectsDirectory,DriverDirectory,TargetDirectory)
# Now get the required files
print "\n\n\n================================="
required_files_noduplicates = GetRequiredFilesFromFolder(DriverDirectory)
print "The required files are: "
print required_files_noduplicates
print "================================="
# loop through these files, collecting the filenames and directory names
# first you need to know what directory level the driver files are in
print "\n\n\n======================================"
n_level_of_driver_directory = LSDost.GetPathLevel(DriverDirectory)
for FileName in required_files_noduplicates:
# you need to know what level the file is
ThisPath = LSDost.GetPath(FileName)
ThisLevel = LSDost.GetPathLevel(ThisPath)
#if it is the same level as the driver directory, it is in the driver directory!
if ThisLevel == n_level_of_driver_directory:
CopyDirectory = TargetDriverDirectory
CopyFileName = LSDost.GetFileNameNoPath(FileName)
CopyFileNameWithPath = CopyDirectory+CopyFileName
else:
CopyDirectory = TargetDirectory
CopyFileName = LSDost.GetFileNameNoPath(FileName)
CopyFileNameWithPath = CopyDirectory+CopyFileName
print "The filename is: " + FileName
print "The copy filename is: " + CopyFileNameWithPath
shutil.copy(FileName, CopyFileNameWithPath)
# now copy the files over
print "=============================================="
def TranslateToReducedGeoJSON(self, FileName):
# Parse a delimited text file of volcano data and create a shapefile
import osgeo.ogr as ogr
import osgeo.osr as osr
# set up the shapefile driver
driver = ogr.GetDriverByName("GeoJSON")
# Get the path to the file
this_path = LSDOst.GetPath(FileName)
DataName = self.FilePrefix
FileOut = this_path + DataName + ".geojson"
print "The filename will be: " + FileOut
# delete the existing file
if os.path.exists(FileOut):
driver.DeleteDataSource(FileOut)
# create the data source
data_source = driver.CreateDataSource(FileOut)
# create the spatial reference, in this case WGS84 (which is ESPG 4326)
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
print "Creating the layer"
# create the layer
layer = data_source.CreateLayer("CRNData", srs, ogr.wkbPoint)
#print "Adding the field names"
# Add the fields we're interested in
field_name = ogr.FieldDefn("SampleName", ogr.OFTString)
field_name.SetWidth(48)
layer.CreateField(field_name)
field_region = ogr.FieldDefn("Nuclide", ogr.OFTString)
field_region.SetWidth(48)
layer.CreateField(field_region)
layer.CreateField(ogr.FieldDefn("Latitude", ogr.OFTReal))
layer.CreateField(ogr.FieldDefn("Longitude", ogr.OFTReal))
layer.CreateField(ogr.FieldDefn("EffERate", ogr.OFTReal))
layer.CreateField(ogr.FieldDefn("EffERateU", ogr.OFTReal))
sample_name = self.GetSampleName()
nuclide = self.GetNuclide()
Latitude = self.GetLatitude()
Longitude = self.GetLongitude()
ERateU = self.GetErosionRatesUncert()
ERate = self.GetErosionRates()
#print "lengths are: "
#print "SN: " + str(len(sample_name))
#print "N: " + str(len(Latitude))
#print "Lat: " + str(len(nuclide))
#print "Long: " + str(len(Longitude))
#print "Erate: " + str(len(ERate))
#print "ErateU: " + str(len(ERateU))
# Process the text file and add the attributes and features to the shapefile
for index, name in enumerate(sample_name):
# create the feature
feature = ogr.Feature(layer.GetLayerDefn())
# Set the attributes using the values from the delimited text file
feature.SetField("SampleName", name)
feature.SetField("Nuclide", nuclide[index])
feature.SetField("Latitude", Latitude[index])
feature.SetField("Longitude", Longitude[index])
feature.SetField("EffERate", ERate[index])
feature.SetField("EffERateU", ERateU[index])
# create the WKT for the feature using Python string formatting
wkt = "POINT(%f %f)" % (float(
Longitude[index]), float(Latitude[index]))
# Create the point from the Well Known Txt
point = ogr.CreateGeometryFromWkt(wkt)
# Set the feature geometry using the point
feature.SetGeometry(point)
# Create the feature in the layer (shapefile)
layer.CreateFeature(feature)
# Destroy the feature to free resources
feature.Destroy()
# Destroy the data source to free resources
data_source.Destroy()
def TranslateToReducedGeoJSON(self, FileName):
# Parse a delimited text file of volcano data and create a shapefile
import osgeo.ogr as ogr
import osgeo.osr as osr
# set up the shapefile driver
driver = ogr.GetDriverByName("GeoJSON")
# Get the path to the file
this_path = LSDOst.GetPath(FileName)
DataName = self.FilePrefix
FileOut = this_path + DataName + ".geojson"
print "The filename will be: " + FileOut
# delete the existing file
if os.path.exists(FileOut):
driver.DeleteDataSource(FileOut)
# create the data source
data_source = driver.CreateDataSource(FileOut)
# create the spatial reference, in this case WGS84 (which is ESPG 4326)
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
print "Creating the layer"
# create the layer
layer = data_source.CreateLayer("PointData", srs, ogr.wkbPoint)
#print "Adding the field names"
# Add the field names
for index, name in enumerate(self.VariableList):
print "The variable name is " + name + " and the type is: " + str(
self.DataTypes[index])
if self.DataTypes[index] is int:
layer.CreateField(ogr.FieldDefn(name, ogr.OFTInteger))
elif self.DataTypes[index] is float:
layer.CreateField(ogr.FieldDefn(name, ogr.OFTReal))
elif self.DataTypes[index] is str:
print "Making a sting layer for layer " + name
layer.CreateField(ogr.FieldDefn(name, ogr.OFTString))
else:
layer.CreateField(ogr.FieldDefn(name, ogr.OFTReal))
# Process the text file and add the attributes and features to the shapefile
for index, lat in enumerate(self.Latitude):
# create the feature
feature = ogr.Feature(layer.GetLayerDefn())
for name in self.VariableList:
feature.SetField(name, self.PointData[name][index])
# create the WKT for the feature using Python string formatting
wkt = "POINT(%f %f)" % (float(
self.Longitude[index]), float(self.Latitude[index]))
# Create the point from the Well Known Txt
point = ogr.CreateGeometryFromWkt(wkt)
# Set the feature geometry using the point
feature.SetGeometry(point)
# Create the feature in the layer (shapefile)
layer.CreateFeature(feature)
# Destroy the feature to free resources
feature.Destroy()
# Destroy the data source to free resources
data_source.Destroy()
def PlotERateErrorsRefined(self, CRONUSFileName):
import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib.gridspec import GridSpec
#from scipy.stats import gaussian_kde
label_size = 18
axis_size = 26
# Set up fonts for plots
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['arial']
rcParams['font.size'] = label_size
#safi = 1 # Save figures as png (1 to save, otherwise 0):
#zoom = 1 # zoom in plots activated if value is 1
# Check if you've got the CONUS data: don't read the file if you've already got it
if (self.HaveCRONUSData != True):
self.ReadCRONUSData(CRONUSFileName)
# now get the errors
self.GetErrorsBetweenMethods()
self.GetErrorsBetweenCRONUS()
# FIGURE 1 = ERATE COMPARED TO ERATE
Fig1 = plt.figure(1, facecolor='white', figsize=(12, 9))
# generate a 120,90 grid.
gs = GridSpec(90, 120, bottom=0.1, left=0.1, right=0.95, top=0.95)
Error_string_CR_BERC = '($\epsilon_{CR}$-$\epsilon_{BERC}$)/$\epsilon_{BERC}$ g cm$^{-2}$ yr$^{-1}$'
Error_string_CC_BERC = '($\epsilon_{CC}$-$\epsilon_{BERC}$)/$\epsilon_{BERC}$ g cm$^{-2}$ yr$^{-1}$'
# get the lengths
#print "The lengths are: "
#print len(self.CRNData['AvgProdScaling'])
#print len(self.CRNData['Error_CR'])
#print len(self.CRNData['basin_relief'])
##########################################
# Plot 1 = comparison new_code / cosmocalc
############################################
##
ax = Fig1.add_subplot(gs[0:40, 0:50])
#plt.plot(self.CRNData['AvgProdScaling'],self.CRNData['Error_CR'],"o", markersize=8 )
cax = plt.scatter(self.CRNData['erate_g_percm2_peryr'],
self.CRNData['Error_CR'],
c=self.CRNData['AverageCombinedScaling'],
s=50,
edgecolor='',
cmap=plt.get_cmap("summer"))
cbar = plt.colorbar(cax)
cbar.set_label('Combined Scaling')
# the basin relief data is in self.CRNData['basin_relief']
#plt.plot(self.CRNData['AvgProdScaling'],self.CRNData['Error_CR'],color=cmap(self.CRNData['basin_relief']),"o", markersize=8 )
#plt.errorbar(datazz['erate_cosmocalc']*10, datazz['erate_cmperkyr']*10, xerr=datazz['error_cosmocalc'], yerr=datazz['error_newcode'], fmt='o',color = cmap(colo))
ax.spines['top'].set_linewidth(2.5)
ax.spines['left'].set_linewidth(2.5)
ax.spines['right'].set_linewidth(2.5)
ax.spines['bottom'].set_linewidth(2.5)
# This gets all the ticks, and pads them away from the axis so that the corners don't overlap
ax.tick_params(axis='both', width=2.5, pad=2)
for tick in ax.xaxis.get_major_ticks():
tick.set_pad(10)
plt.xlabel('Erosion rate in g cm$^{-2}$ yr$^{-1}$',
fontsize=axis_size - 2,
verticalalignment='bottom')
plt.ylabel('($\epsilon_{CR}$-$\epsilon_{BERC}$)/$\epsilon_{BERC}$',
fontsize=axis_size - 4)
# this aligns the labels.
# The transform=ax.transAxes means that the coordinate system is the axis coordinate system
# where x = 0.5 is the centre of the x axis
ax.xaxis.set_label_coords(0.5, -0.22, transform=ax.transAxes)
##########################################
# Plot 2 = comparison new_code / cosmocalc
############################################
##
ax = Fig1.add_subplot(gs[0:40, 70:120])
cax = plt.scatter(self.CRNData['AverageCombinedScaling'],
self.CRNData['Error_CR'],
c=self.CRNData['AverageShielding'],
s=50,
edgecolor='',
cmap=plt.get_cmap("hot"))
cbar = plt.colorbar(cax)
cbar.set_label('Average shielding')
ax.spines['top'].set_linewidth(2.5)
ax.spines['left'].set_linewidth(2.5)
ax.spines['right'].set_linewidth(2.5)
ax.spines['bottom'].set_linewidth(2.5)
# This gets all the ticks, and pads them away from the axis so that the corners don't overlap
ax.tick_params(axis='both', width=2.5, pad=2)
for tick in ax.xaxis.get_major_ticks():
tick.set_pad(10)
plt.xlabel('Average shielding', fontsize=axis_size - 2)
plt.ylabel('($\epsilon_{CR}$-$\epsilon_{BERC}$)/$\epsilon_{BERC}$',
fontsize=axis_size - 4)
##########################################
# Plot 3 = comparison new_code / cosmocalc
############################################
##
ax = Fig1.add_subplot(gs[50:90, 0:50])
cax = plt.scatter(self.CRNData['AverageCombinedScaling'],
self.CRNData['Error_CR_em'],
c=self.CRNData['erate_g_percm2_peryr'],
s=50,
edgecolor='',
cmap=plt.get_cmap("YlGnBu"))
cbar = plt.colorbar(cax)
cbar.set_label('Erosion rate (g cm$^{-2}$ yr$^{-1}$)')
ax.spines['top'].set_linewidth(2.5)
ax.spines['left'].set_linewidth(2.5)
ax.spines['right'].set_linewidth(2.5)
ax.spines['bottom'].set_linewidth(2.5)
# This gets all the ticks, and pads them away from the axis so that the corners don't overlap
ax.tick_params(axis='both', width=2.5, pad=2)
for tick in ax.xaxis.get_major_ticks():
tick.set_pad(10)
plt.xlabel('Average combined scaling',
fontsize=axis_size - 2,
verticalalignment='bottom')
plt.ylabel('($\epsilon_{CC}$-$\epsilon_{BERC}$)/$\epsilon_{BERC}$',
fontsize=axis_size - 4)
# this aligns the labels.
# The transform=ax.transAxes means that the coordinate system is the axis coordinate system
# where x = 0.5 is the centre of the x axis
ax.xaxis.set_label_coords(0.5, -0.22, transform=ax.transAxes)
##########################################
# Plot 4 = comparison new_code / cosmocalc
############################################
##
ax = Fig1.add_subplot(gs[50:90, 70:120])
linetest = np.arange(
0,
np.max(self.CRNData['erate_g_percm2_peryr'] +
np.max(self.CRNData['total_uncert'])), 0.01)
print "Here is the line"
print linetest
print "max: "
print np.max(self.CRNData['erate_g_percm2_peryr'] +
np.max(self.CRNData['total_uncert']))
#print "err: "
#print
CRONUS_err = self.CRNData['CRONUS_total_uncert']
BERC_err = self.CRNData['total_uncert']
ax.errorbar(self.CRNData['erate_g_percm2_peryr'],
self.CRNData['CRONUS_erate_g_percm2_peryr'],
yerr=CRONUS_err,
xerr=BERC_err,
fmt='.',
zorder=1)
cax = ax.scatter(self.CRNData['erate_g_percm2_peryr'],
self.CRNData['CRONUS_erate_g_percm2_peryr'],
c=self.CRNData['AverageCombinedScaling'],
s=50,
edgecolor='',
cmap=plt.get_cmap("summer"),
zorder=10)
ax.plot(linetest, linetest, '-k', linewidth=2, zorder=5)
cbar = plt.colorbar(cax)
cbar.set_label('Combined Scaling')
# the basin relief data is in self.CRNData['basin_relief']
axlims = ax.get_xlim()
ax.set_xlim(0, axlims[1])
# This makes all the spines thick so you can see them
ax.spines['top'].set_linewidth(2.5)
ax.spines['left'].set_linewidth(2.5)
ax.spines['right'].set_linewidth(2.5)
ax.spines['bottom'].set_linewidth(2.5)
# This gets all the ticks, and pads them away from the axis so that the corners don't overlap
ax.tick_params(axis='both', width=2.5, pad=2)
for tick in ax.xaxis.get_major_ticks():
tick.set_pad(10)
plt.xlabel('$\epsilon_{BERC}$ g cm$^{-2}$ yr$^{-1}$',
fontsize=axis_size - 2)
plt.ylabel('$\epsilon_{CR}$ g cm$^{-2}$ yr$^{-1}$',
fontsize=axis_size - 4)
figname = LSDOst.GetPath(CRONUSFileName) + 'Erate_comparison.pdf'
plt.savefig(figname, format='pdf')