Returns the matplotlib.pyplot module for convenience. Initialize Matplotlib rc parameters Pyrocko style. Used to map 'auto' mode to '0-max', 'min-0', 'min-max' Guess mode of operation, based on data range. guess_autoscale_mode ( data_min, data_max ) ¶ If override_mode isĭefined, the mode attribute is temporarily overridden by the givenįor ax annotations, give tick increment as x. Returns (minimum, maximum, increment) or (maximum, minimum, -increment), depending on whether data_range is (data_min, data_max) or (data_max, data_min). Get nice minimum, maximum and increment for given data range. make_scale ( data_range, override_mode = None ) ¶ Range of exponent, for which no exponential notation is aallowed. ♦ exp_factor ¶Įxponent of notation is chosen to be a multiple of this value. This parameter has no effect if mode is set to 'off'. If mode is '0-max' or 'min-0', the end at zero is kept fixed at zero. The value given, is the fraction by which the output range is increased on each side. If defined, override automatically determined tick increment by the given value. This parameter has no effect, if mode is set to 'off'. If set to True, snap output range to multiples of increment. If defined, override automatically determined exponent for notation by the given value. The autoscaling process is guided by the following public attributes: ♦ approx_ticks ¶Īpproximate number of increment steps (tickmarks) to generate. Increments for ax annotations, as well as suitable common exponents for Instances of this class may be used to determine nice minima, maxima and Tunable 1D autoscaling based on data range. Similar to 'min-max', but snap and space areĭisabled, such that the output range alwaysĬlass AutoScaler ( approx_ticks = 7.0, mode = 'auto', exp = None, snap = False, inc = None, space = 0.0, exp_factor = 3, no_exp_interval = (-3, 5) ) ¶ Output range shall start at data min and end at Output range shall start at zero and end at data Output range is selected to include data range. Look at data range and choose one of the choices papersize ( paper, orientation = 'landscape', units = 'point' ) ¶ With support for GMT5 and GMT6 pyrocko’s gmtpy exposes GMT’s neat mapping functions to Python 3. _plot Plotting velocities models and ray paths. Quickly generate pretty maps using gmtpy’s powers. , 1.5 ) # or: relative to left/bottom paper edge axes. add_subplot ( 1, 1, 1 ) # positioning of axis labels # mpl_labelspace(axes) # either: relative to axis tick labels labelpos ( axes, 2. top and bottom # margin are set to be 5*fontsize = 45 labelpos = mpl_margins ( fig, w = 7. figure ( figsize = mpl_papersize ( 'a4', 'landscape' )) # let margins be proportional to selected font size, e.g. # in points # set some Pyrocko style defaults mpl_init ( fontsize = fontsize ) fig = plt. From matplotlib import pyplot as plt from ot import mpl_init, mpl_margins, mpl_papersize # from ot import mpl_labelspace fontsize = 9.
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