diff options
| -rw-r--r-- | Makefile | 18 | ||||
| -rw-r--r-- | data.py | 179 | ||||
| -rwxr-xr-x | data/maketables.sh | 5 | ||||
| -rw-r--r-- | python/data.py | 102 | ||||
| -rw-r--r-- | python/deathtable.py | 7 | ||||
| -rw-r--r-- | python/depwid.py | 22 | ||||
| -rw-r--r-- | python/img.py | 4 | ||||
| -rw-r--r-- | python/neighbor.py | 21 | ||||
| -rw-r--r-- | python/table.py | 15 |
9 files changed, 182 insertions, 191 deletions
@@ -10,16 +10,17 @@ all: outputs/posterboard.pdf outputs/report.pdf outputs/logbook.pdf png: outputs/posterboard.png .PHONY: clean clean: - rm -rf imgs graph outputs + rm -rf imgs graph outputs data/tables.tex -$(IMGS): data.py +$(IMGS): python/data.py python/img.py cd imgs && \ - python3 ../data.py img + python3 ../python/img.py -$(GRAPHS): data.py - cd graph && \ - python3 ../data.py depwid && \ - python3 ../data.py nei +graph/depth_width.png: python/data.py python/depwid.py + cd graph && python3 ../python/depwid.py + +graph/nearest_neighbor.png: python/data.py python/neighbor.py + cd graph && python3 ../python/neighbor.py outputs/posterboard.png: outputs/posterboard.pdf gs -sDEVICE=pngalpha -r288 -o outputs/posterboard.png outputs/posterboard.pdf @@ -45,6 +46,5 @@ outputs/qr.png: outputs/qr-source.png: qrencode https://git.hrhr.dev/scifair -o outputs/qr-source.png - -data/tables.tex: +data/tables.tex: data/maketables.sh data/tables.orig.tex data/maketables.sh diff --git a/data.py b/data.py deleted file mode 100644 index 9aead79..0000000 --- a/data.py +++ /dev/null @@ -1,179 +0,0 @@ -# Data - -from scipy.spatial import Voronoi, voronoi_plot_2d, KDTree, distance -import matplotlib.pyplot as plt - -class Pit: - def __init__(self, loc, depth, diam): - self.loc = loc - self.depth = depth - self.diam = diam - - def __repr__(self): - return '%s @ %.1fcm deep, %.1fcm wide' % (str(self.loc), self.depth, self.diam) - - def disp(self): - return '%.1fcm dp\n %.1fcm wd' % (self.depth, self.diam) - - def __getitem__(self,ind): - return self.loc[ind] - -class Date: - def __init__(self, year, month, day): - self.year = year - self.month = month - self.day = day - - def __repr__(self): - return '%d-%d-%d' % (self.year, self.month, self.day) - -class Trial: - def __init__(self, date, intro, dead, size, pits): - self.date = date - self.intro = intro - self.dead = dead - self.size = size - self.pits = pits - self.pitlocs = [pit.loc for pit in self.pits] - - def __repr__(self): - return str(self.date) + ' ' + str(self.pits) - - def plot(self, save=False): - vor = Voronoi([pit.loc for pit in self.pits]) - voronoi_plot_2d(vor) - plt.xlabel('%s (dimension %dx%dcm)' % (str(self.date), self.size[0], self.size[1])) - if save: - plt.savefig(str(self.date)+'.png', bbox_inches='tight') - else: - plt.show() - - def nearest_neighbor(self): - tree = KDTree(self.pitlocs) - sumnn = 0 - return [dists[1] for dists in tree.query(self.pitlocs,2)[0]] - -trials = [ - Trial(Date(2019, 10, 16), 31, 6, [33,32], [ - Pit([4,25],1.3,4.2), - Pit([3,13],1.4,3.7), - Pit([10,25],1.1,3.0), - Pit([18,18],1.8,2.3), - Pit([30,14],2.2,3.1), - Pit([29,11],1.4,2.5), - Pit([27,10],1.2,2.1), - Pit([29,6],2.4,3.9), - Pit([26,5],1.8,3.6), - ]), - Trial(Date(2019, 10, 30), 27, 3, [24,24], [ - Pit([4,21],2.0,7.0), - Pit([7,22],2.5,4.1), - Pit([2,9],0.5,2.0), - Pit([12,18],1.2,2.5), - Pit([12,11],1.2,3.0), - Pit([20,11],1.0,3.0), - Pit([19,2],1.5,4.0), - ]), - Trial(Date(2019, 12, 3), 19, 3, [17, 16], [ - Pit([14,5],1.3,4.1), - Pit([12,2],1.2,3.8), - Pit([5,1],0.9,3.2), - Pit([15,17],2.2,3.8), - Pit([12,17],1.2,2.5), - Pit([7,17],2.0,5.0), - Pit([1,17],1.8,3.6), - ]), - Trial(Date(2019, 12, 5), 10, 0, [17, 16], [ - Pit([17,4],1.3,3.1), - Pit([10,4],1.5,3.1), - Pit([16,9],1.4,2.9), - ]), - Trial(Date(2019, 12, 19), 12, 4, [8,7], [ - Pit([4,7],.8,.9), - Pit([3,5],.9,.8), - Pit([8,2],2,3), - ]), - Trial(Date(2019, 12, 20), 5, 0, [8,7], [ - Pit([6,7],.8,.8), - Pit([2,2],.8,.8), - Pit([8,6],.8,.8), - Pit([2,9],.8,.8), - ]), -] - -from sys import argv -from math import sqrt -from numpy import poly1d, polyfit -from scipy.stats import pearsonr -from collections import Counter - -if len(argv) < 2: - print('You must provide at least one argument to choose the function of this program: `img` or `nei` or `depwid') - quit() - -arg = argv[1] - -if arg == 'img': - for trial in trials: - trial.plot(save=True) - -if arg == 'nei': - x = [] - y = [] - for trial in trials: - size = sqrt(trial.size[0]*trial.size[1]) - nei = trial.nearest_neighbor() - #for n in range(len(nei)): - # nei[n] += n*.05 - #x += [sqrt(trial.size[0]*trial.size[1])]*len(nei) - #y += nei - x.append(size) - y.append(sum(nei)/len(nei)) - fig = plt.figure() - ax = fig.add_subplot(111) - plt.text(0.1, 0.9, 'R^2 = %.3f\np=%.3f' % (pearsonr(x,y)[0]**2, pearsonr(x,y)[1]), ha='center', va='center', transform=ax.transAxes) - plt.xlabel('Square root of Trial Area (cm)') - plt.ylabel('Nearest Neighbor for Individual Pits (cm)') - plt.plot(x, y, 'bo') - plt.plot(x, poly1d(polyfit(x, y, 1))(x)) - plt.savefig('nearest_neighbor.png', bbox_inches='tight') - -if arg == 'depwid': - depths, widths, sizes = [], [], [] - for trial in trials: - size = sqrt(trial.size[0]*trial.size[1]) - for pit in trial.pits: - sizes.append(size) - depths.append(pit.depth) - widths.append(pit.diam) - weights = [20*i for i in Counter(depths).values() for j in range(i)] - plt.scatter([size-.5 for size in sizes], depths, weights, 'b','o', label='depth') - weights = [20*i for i in Counter(widths).values() for j in range(i)] - plt.scatter(sizes, widths, weights, 'r', 'o', label='width') - plt.xlabel('Square root of Trial Area (cm)') - plt.ylabel('Depth/Width of Antlion Pits (cm)') - plt.legend(loc='upper right') - plt.text(10, 7, 'R^2 = %.3f\np=%.3f' % (pearsonr(sizes,depths)[0], pearsonr(sizes,depths)[1]), ha='center', va='center') - plt.savefig('depth_width.png', bbox_inches='tight') - -if arg == 'table': - print('\\vtable{') - table = ['Dimensions (in)', 'Pit Depth (cm)', 'Pit Width (cm)', 'Nearest Neighbor (cm)','']; - lastsize = 0; - for trial in trials: - size = trial.size - table[0] += '&\\multispan{' + str(len(trial.pits)) + '}\\vfil\\line{\\hfil' + '$\\times$'.join([str(el) for el in size]) + '\\hfil}\\vfil\\hrule' - nei = trial.nearest_neighbor() - for pitind in range(len(trial.pits)): - pit = trial.pits[pitind] - table[1] += '&' + '%.1f' % pit.depth - table[2] += '&' + '%.1f' % pit.diam - table[3] += '&' + '%.2f' % nei[pitind] - print('\\cr\\noalign{\\vrule}\n'.join(table) + '}', end=''); - -if arg == 'deathtable': - print('\\table{') - print('Trial Size& Date& Introduced& Deaths& Pits formed\\cr\\noalign{\\hrule}') - for trial in trials: - print('& '.join(['$\\times$'.join([str(el) for el in trial.size]), str(trial.date), str(trial.intro), str(trial.dead), str(len(trial.pits))])+'\\cr\\noalign{\\hrule}') - print('}', end='') diff --git a/data/maketables.sh b/data/maketables.sh index 0f043ad..dffc937 100755 --- a/data/maketables.sh +++ b/data/maketables.sh @@ -2,8 +2,7 @@ export TABLE=`mktemp` export DEATHTABLE=`mktemp` -echo $TABLE -python data.py deathtable > $DEATHTABLE -python data.py table > $TABLE +python python/deathtable.py > $DEATHTABLE +python python/table.py > $TABLE sed -e "/%%DEATHTABLE%%/{r $DEATHTABLE" -e "d}" -e "/%%MAINTABLE%%/{r $TABLE" -e "d}" <data/tables.orig.tex >data/tables.tex rm $DEATHTABLE $TABLE diff --git a/python/data.py b/python/data.py new file mode 100644 index 0000000..de850e8 --- /dev/null +++ b/python/data.py @@ -0,0 +1,102 @@ +# Data +arg = '' +from scipy.spatial import Voronoi, voronoi_plot_2d, KDTree, distance +import matplotlib.pyplot as plt + +class Pit: + def __init__(self, loc, depth, diam): + self.loc = loc + self.depth = depth + self.diam = diam + + def __repr__(self): + return '%s @ %.1fcm deep, %.1fcm wide' % (str(self.loc), self.depth, self.diam) + + def disp(self): + return '%.1fcm dp\n %.1fcm wd' % (self.depth, self.diam) + + def __getitem__(self,ind): + return self.loc[ind] + +class Date: + def __init__(self, year, month, day): + self.year = year + self.month = month + self.day = day + + def __repr__(self): + return '%d-%d-%d' % (self.year, self.month, self.day) + +class Trial: + def __init__(self, date, intro, dead, size, pits): + self.date = date + self.intro = intro + self.dead = dead + self.size = size + self.pits = pits + self.pitlocs = [pit.loc for pit in self.pits] + + def __repr__(self): + return str(self.date) + ' ' + str(self.pits) + + def plot(self, save=False): + vor = Voronoi([pit.loc for pit in self.pits]) + voronoi_plot_2d(vor) + plt.xlabel('%s (dimension %dx%dcm)' % (str(self.date), self.size[0], self.size[1])) + if save: + plt.savefig(str(self.date)+'.png', bbox_inches='tight') + else: + plt.show() + + def nearest_neighbor(self): + tree = KDTree(self.pitlocs) + sumnn = 0 + return [dists[1] for dists in tree.query(self.pitlocs,2)[0]] + +trials = [ + Trial(Date(2019, 10, 16), 31, 6, [33,32], [ + Pit([4,25],1.3,4.2), + Pit([3,13],1.4,3.7), + Pit([10,25],1.1,3.0), + Pit([18,18],1.8,2.3), + Pit([30,14],2.2,3.1), + Pit([29,11],1.4,2.5), + Pit([27,10],1.2,2.1), + Pit([29,6],2.4,3.9), + Pit([26,5],1.8,3.6), + ]), + Trial(Date(2019, 10, 30), 27, 3, [24,24], [ + Pit([4,21],2.0,7.0), + Pit([7,22],2.5,4.1), + Pit([2,9],0.5,2.0), + Pit([12,18],1.2,2.5), + Pit([12,11],1.2,3.0), + Pit([20,11],1.0,3.0), + Pit([19,2],1.5,4.0), + ]), + Trial(Date(2019, 12, 3), 19, 3, [17, 16], [ + Pit([14,5],1.3,4.1), + Pit([12,2],1.2,3.8), + Pit([5,1],0.9,3.2), + Pit([15,17],2.2,3.8), + Pit([12,17],1.2,2.5), + Pit([7,17],2.0,5.0), + Pit([1,17],1.8,3.6), + ]), + Trial(Date(2019, 12, 5), 10, 0, [17, 16], [ + Pit([17,4],1.3,3.1), + Pit([10,4],1.5,3.1), + Pit([16,9],1.4,2.9), + ]), + Trial(Date(2019, 12, 19), 12, 4, [8,7], [ + Pit([4,7],.8,.9), + Pit([3,5],.9,.8), + Pit([8,2],2,3), + ]), + Trial(Date(2019, 12, 20), 5, 0, [8,7], [ + Pit([6,7],.8,.8), + Pit([2,2],.8,.8), + Pit([8,6],.8,.8), + Pit([2,9],.8,.8), + ]), +] diff --git a/python/deathtable.py b/python/deathtable.py new file mode 100644 index 0000000..f393cc8 --- /dev/null +++ b/python/deathtable.py @@ -0,0 +1,7 @@ +from data import trials + +print('\\table{') +print('Trial Size& Date& Introduced& Deaths& Pits formed\\cr\\noalign{\\hrule}') +for trial in trials: + print('& '.join(['$\\times$'.join([str(el) for el in trial.size]), str(trial.date), str(trial.intro), str(trial.dead), str(len(trial.pits))])+'\\cr\\noalign{\\hrule}') +print('}', end='') diff --git a/python/depwid.py b/python/depwid.py new file mode 100644 index 0000000..081167f --- /dev/null +++ b/python/depwid.py @@ -0,0 +1,22 @@ +from data import trials +from math import sqrt +from scipy.stats import pearsonr +from collections import Counter +import matplotlib.pyplot as plt + +depths, widths, sizes = [], [], [] +for trial in trials: + size = sqrt(trial.size[0]*trial.size[1]) + for pit in trial.pits: + sizes.append(size) + depths.append(pit.depth) + widths.append(pit.diam) +weights = [20*i for i in Counter(depths).values() for j in range(i)] +plt.scatter([size-.5 for size in sizes], depths, weights, 'b','o', label='depth') +weights = [20*i for i in Counter(widths).values() for j in range(i)] +plt.scatter(sizes, widths, weights, 'r', 'o', label='width') +plt.xlabel('Square root of Trial Area (cm)') +plt.ylabel('Depth/Width of Antlion Pits (cm)') +plt.legend(loc='upper right') +plt.text(10, 7, 'R^2 = %.3f\np=%.3f' % (pearsonr(sizes,depths)[0], pearsonr(sizes,depths)[1]), ha='center', va='center') +plt.savefig('depth_width.png', bbox_inches='tight') diff --git a/python/img.py b/python/img.py new file mode 100644 index 0000000..177a7a2 --- /dev/null +++ b/python/img.py @@ -0,0 +1,4 @@ +from data import trials + +for trial in trials: + trial.plot(save=True); diff --git a/python/neighbor.py b/python/neighbor.py new file mode 100644 index 0000000..004979a --- /dev/null +++ b/python/neighbor.py @@ -0,0 +1,21 @@ +from data import trials +from scipy.stats import pearsonr +from numpy import poly1d, polyfit +from math import sqrt +import matplotlib.pyplot as plt + +x = [] +y = [] +for trial in trials: + size = sqrt(trial.size[0]*trial.size[1]) + nei = trial.nearest_neighbor() + x.append(size) + y.append(sum(nei)/len(nei)) +fig = plt.figure() +ax = fig.add_subplot(111) +plt.text(0.1, 0.9, 'R^2 = %.3f\np=%.3f' % (pearsonr(x,y)[0]**2, pearsonr(x,y)[1]), ha='center', va='center', transform=ax.transAxes) +plt.xlabel('Square root of Trial Area (cm)') +plt.ylabel('Nearest Neighbor for Individual Pits (cm)') +plt.plot(x, y, 'bo') +plt.plot(x, poly1d(polyfit(x, y, 1))(x)) +plt.savefig('nearest_neighbor.png', bbox_inches='tight') diff --git a/python/table.py b/python/table.py new file mode 100644 index 0000000..1d11779 --- /dev/null +++ b/python/table.py @@ -0,0 +1,15 @@ +from data import trials + +print('\\vtable{') +table = ['Dimensions (in)', 'Pit Depth (cm)', 'Pit Width (cm)', 'Nearest Neighbor (cm)','']; +lastsize = 0; +for trial in trials: + size = trial.size + table[0] += '&\\multispan{' + str(len(trial.pits)) + '}\\vfil\\line{\\hfil' + '$\\times$'.join([str(el) for el in size]) + '\\hfil}\\vfil\\hrule' + nei = trial.nearest_neighbor() + for pitind in range(len(trial.pits)): + pit = trial.pits[pitind] + table[1] += '&' + '%.1f' % pit.depth + table[2] += '&' + '%.1f' % pit.diam + table[3] += '&' + '%.2f' % nei[pitind] +print('\\cr\\noalign{\\vrule}\n'.join(table) + '}', end=''); |