def Recip_space(sample): """ Set up general reciprocal space grid for plotting Miller indicies in a general space. Would be cool if returned fig object had a custom transformation so that all data added to plot after it has been created can be given in miller indicies grid for custom transform. """ def tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y - x def inv_tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y + x grid_helper = GridHelperCurveLinear((tr, inv_tr)) fig = plt.figure(1, figsize=(7, 4)) ax = Subplot(fig, 1, 1, 1, grid_helper=grid_helper) rlatt = sample.star_lattice [xs, ys, zs] = sample.StandardSystem fig.add_subplot(ax) ax.grid(True) return
def curvelinear_test1(fig): """ grid for custom transform. """ def tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y - x def inv_tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y + x grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper) # ax1 will have a ticks and gridlines defined by the given # transform (+ transData of the Axes). Note that the transform of # the Axes itself (i.e., transData) is not affected by the given # transform. fig.add_subplot(ax1) xx, yy = tr([3, 6], [5.0, 10.]) ax1.plot(xx, yy) ax1.set_aspect(1.) ax1.set_xlim(0, 10.) ax1.set_ylim(0, 10.) ax1.grid(True)
def curvelinear_test1(fig): """ grid for custom transform. """ def tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y-x def inv_tr(x,y): x, y = np.asarray(x), np.asarray(y) return x, y+x grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper) # ax1 will have a ticks and gridlines defined by the given # transform (+ transData of the Axes). Note that the transform of # the Axes itself (i.e., transData) is not affected by the given # transform. fig.add_subplot(ax1) xx, yy = tr([3, 6], [5.0, 10.]) ax1.plot(xx, yy) ax1.set_aspect(1.) ax1.set_xlim(0, 10.) ax1.set_ylim(0, 10.) ax1.axis["t"]=ax1.new_floating_axis(0, 3.) ax1.axis["t2"]=ax1.new_floating_axis(1, 7.) ax1.grid(True)
def curvelinear_test1(fig): """ grid for custom transform. """ def tr(x, y): x, y = np.asarray(x), np.asarray(y) return x, y-x def inv_tr(x,y): x, y = np.asarray(x), np.asarray(y) return x, y+x grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper) fig.add_subplot(ax1) xx, yy = tr([3, 6], [5.0, 10.]) ax1.plot(xx, yy) ax1.set_aspect(1.) ax1.set_xlim(0, 10.) ax1.set_ylim(0, 10.) ax1.grid(True)
reader = csv.reader(open('dasovich-dates.csv', 'r')) reader.next() # skip header for row in reader: dates.append(datetime.strptime(row[0], '%Y-%m')) # dates.append(row[0]) emails.append(float(row[1])) # PLOT fig = plt.figure() ax = Subplot(fig, 111) fig.add_subplot(ax) ax.axis["right"].set_visible(False) ax.axis["top"].set_visible(False) plt.plot_date(dates, emails, xdate=True, ydate=False, linestyle='-', color='#333333') ax.grid(which='major', color='#999999') plt.xticks(rotation='vertical') plt.title('Monthly Email History for Jeff Dasovich') plt.ylabel('Number of Emails') plt.savefig('foo.pdf', transparent=True)